To evaluate main features of donor tissue that may influence clinical outcome or complication rate after deep anterior lamellar keratoplasty (DALK).Donor tissue parameters of 84 consecutive corneal donor grafts used for big-bubble DALK surgery between June 2011 and December 2014 in 84 eyes of 84 patients with disorders of anterior corneal stroma were correlated to clinical outcome parameters of recipient eyes 12 months after surgery and 3 months after total suture removal. Main donor tissue parameters included age), post-mortem time, overall preservation time, preservation time after split and prior to transplantation, and preservation technique. Clinical outcome parameters included best spectacle corrected visual acuity (BSCVA), central corneal thickness (CCT), endothelial cell density (ECD) and complication rates. Pearson’s correlation, linear regression analysis for clinical outcome parameter and logistic regression analysis for postsurgical complication rates were applied.2. Overall preservation time was 16.3 ± 6.3 days. Recipients showed mean BSCVA 12 months postoperatively of 0.60 ± 0.36 logMAR, endothelial cell loss was 4 ± 16%, and central corneal thickness was 571.7 ± 54.2 μm. 3 months after total removal of sutures, BSCVA was 0.20 ± 0.10 logMAR, endothelial cell loss was 17 ± 24%, and central corneal thickness was 590.9 ± 55.5 μm. Loosening of sutures occurred in 20%, and Descemet detachment in 16%. None of the clinical outcome parameters or complication rate after DALK showed a significant association with donor tissue parameters.Corneal donors were mean aged 67.4 ± 12.5 years with a post-mortem time of 20.7 ± 14.7 h and ECD of 2641.0 ± 362.8 cells/mmDonor corneas, independent of excision techniques or preservation method, with donor age ≤ 88 years, post-mortem time ≤ 63 h, overall preservation time ≤ 14 days for cold storaged donor tissue and ≤35 days for organ culture, and preservation time after split prior to grafting ≤96 h, seem to be applicable as safe donor tissue for DALK surgery. Since the introduction of different lamellar keratoplasty techniques the claims to the “perfect” donor graft vary between different indications and methods of corneal transplantation.Traditionally, penetrating keratoplasty (PK) as full-thickness replacement of the cornea has been the standard technique for corneal transplantation in advanced stages of keratoconus, anterior stromal opacity or endothelial failure. Consequently, donor tissue had to be clear without stromal haze, epithelial or endothelial pathologies –3.In 1997 deep anterior lamellar keratoplasty (DALK) was introduced, and there has been a steady increase in its uptake during the last years –6. NowadComparative analyses between DALK and PK for keratoconus report varying results. Graft survival and outcome seem to be affected by several factors, including host and donor factors, improvement in surgical technique, and possibly surgeons experience and learning curve , 8, 9.Most patients with keratoconus are young and therefore have a higher demand on their visual function. Therefore, it is of particular importance to further optimize results of DALK surgery, respectively to find out what can be assigned as important basic requirements of donor tissue.Furthermore, eye banks have to consider carefully about the distribution of donor tissue to potential recipients with various corneal pathologies, especially because of the enormous donor shortage in many parts of the world, including Europe and Asia –13. AccoThe aim of this study was to evaluate retrospectively whether donor tissue features, including donor tissue excision techniques, preservation methods, preservation time and previously performed stripping of the donor button for split cornea transplantation for combined use in Descemet membrane endothelial keratoplasty (DMEK) and DALK may influence the clinical outcome and complication rate of DALK surgery.In this retrospective study, we reviewed the database of the local eye bank of the Department of Ophthalmology, University of Cologne, Cologne, Germany for all donor grafts, that were assessed and distributed for DALK surgery, as well as the corresponding clinical records of 84 eyes of 84 patients who underwent DALK surgery at the Department of Ophthalmology, University of Cologne, Cologne, Germany, between June 2011 and December 2014. The retrospective, nonrandomized, clinical study was approved by the institutional review board (15–301) and was conducted in adherence to the tenets of the Declaration of Helsinki.2), post-mortem time (hours), donor tissue excision technique , preservation technique (organ culture versus 4 °C preservation) and preservation time until grafting (days). If the donor graft was used for split cornea transplantation, the preservation time prior to split (days) and between split and prior to transplantation (hours) was assessed separately.Prior to donor graft distribution and transplantation the following data were assessed: age and gender of donor, cause of death, central corneal thickness (μm), endothelial cell density , and endothelial cell density by phase-contrast microscopy .Prior to surgery, 12 months postoperatively and 3 months after total removal of corneal sutures, standardized eye examinations, including best spectacle-corrected visual acuity (BSCVA), manifest subjective refraction , topographic astigmatism , central corneal thickness , endothelial cell density (Tomey EM-3000 Specular Microscope), slit lamp examination and funduscopy were performed. Intraoperative and postoperative complications were recorded.Exclusion criteria of the local eye bank for cornea donation were: Age ≥ 90 years, as well as post-mortem time ≥ 72 h and positive infectious status in serology or in the anterior chamber probe. Assessment of infectious status in serology was performed in a blood sample which has been taken inbetween 24 h post mortem or in a sample which was still present from the lifetime. Prior to approval for transplantation the following information had to be completed and checked: negative status of serologic screening tests for transmissible diseases, evaluation of donated cornea, commitment to tissue donation by next relatives or the presence of a written commitment of the deceased, and corneal procurement following medical standards.2.The surgeons performing DALK had no further specific demands on the donor lenticule, beside transparency of the graft without stromal scars. If cornea split transplantation, combining DALK and DMEK, was intended, donor tissue was supposed to have at best endothelial cell density ≥ 2000 cells/mmCases in which DALK was intended but conversion to PK was needed due to intraoperative macroperforation were excluded. Further exclusion criteria were history of any keratoplasty in the past, known history of severe ocular trauma, recurrent keratitis of unknown origin, uveitis, significant immunosuppression, steven-johnson syndrome or graft-versus-host-disease.If both eyes in one patient underwent DALK surgery, one eye and respective donor cornea was randomly selected for the study.All donor corneas used for big-bubble DALK surgery meeting in- and exclusion criteria were included consecutively in the present.For statistical analysis concerning BSCVA, partial exclusion criteria were amblyopia or other visual acuity limiting factors such as existence of macular degeneration or advanced stage of glaucoma. 74 eyes could be considered for analysis of BSCVA, 10 eyes were excluded.Donor tissues were allocated by the eye bank staff. Main factors of distribution of donor grafts to recipients were the availability of donor tissue and urgency of corneal transplantation.All patients underwent surgery under full anesthesia and under steady state conditions in the eye hospital. DALK was performed in a standardized fashion using the big-bubble technique as described previously , 15. In If possible, split cornea transplantation was performed. In split cornea transplantation the anterior part of the donor button was used for DALK, the posterior part for DMEK in another patient , 17, 18.The Descemet membrane (DM) was peeled off with fine nontoothed forceps. The donor lenticule was secured with 10–0 monofilament nylon by 16 interrupted sutures or a 16-bite double-running diagonal cross-stitch suture.All patients received routine postoperative management in the form of topical prednisolone acetate 1% in tapering doses over several months and topical antibiotic drops for 1 to 2 weeks (in most cases moxifloxacin). The steroid medication tapered to two times a day after 3 months and discontinued after 1 year. Half of the sutures were removed 12 months after DALK, the remaining sutures after 18 months. Often the time point of suture removal was adapted to factors as wound healing and vascularization, loose sutures or astigmatism.p < 0.05, and adjusted according to the Benjamini-Hochberg correction of multiple testing.Descriptive data for donor tissue and recipients were collected and analyzed by Microsoft Excel 2000 for windows. For further statistical analysis, we used SPSS . The BSCVA results were analyzed in logarithm of the minimum angle of resolution (logMAR) equivalent units. The following statistical tests were applied: exact Fisher test, Mann-Whitney U test, and Pearson’s correlation. The level of significance was defined as Linear and logistic regression analysis were performed using the using the programming language RV 3.2.2 .Donors had a mean ± SD age of 67.4 ± 12.5 years , and a female to male ratio of 28:56. Mean ± SD post-mortem time was 20.7 ± 14.7 h . Eleven (13%) donor corneas were harvested by corneoscleral disc excision and 73 donor corneas (87%) by whole globe enucleation. Eleven donor corneas (13%) were stored at 2–8 °C in Optisol GS  or Life 4 °C , and 73 donor corneas (87%) were organ cultured  at 31 ± 1 °C.2 , mean ± SD central corneal thickness was measured as 617.7 ± 6.3 μm .Mean ± SD overall preservation time was 16.3 ± 6.3 days . Hereby donor corneas stored in Optisol GS or Life 4 °C had a mean ± SD overall preservation time of 11 ± 1.7 days  and organ cultured donor corneas of 17.3 ± 6.4 days . Mean ± SD preservation time after split and prior to transplantation was 6.0 ± 16.8 h , whereas mean ± SD preservation time after split and prior to transplantation was 1.7 ± 1.4 h  for cold storaged donor tissue and 6.6 ± 18.0 h  for organ cultured tissue. Mean ± SD endothelial cell density of donor lenticule was counted as 2641.0 ± 362.8 cells/mmIn 67 eyes (80%) split cornea transplantation could be performed, thereof 9 donor buttons were cold storaged (13%) and 58 were organ cultured (87%). In 9 cases (13%) of split cornea transplantation DALK was performed first so that donor tissues were stripped intraoperatively directly prior to DALK procedure. In 58 (87%) eyes pre-stripped donor tissues were used.n = 1), previously performed cataract surgery (n = 7), amblyopia (n = 9), mild trauma (n = 3), keratoconjunctivitis sicca (n = 2), history of herpetic keratitis (n = 10) and status after laser-assisted in situ keratomileusis (LASIK) (n = 1) or phototherapeutic keratectomy (PTK) (n = 1).In 84 eyes of 84 patients ) DALK was performed. Indications included advanced keratoconus in 67 eyes, corneal scarring in 13 eyes, and lattice corneal dystrophy in 4 eyes. Secondary diagnosis included history of glaucoma .Mean ± SD best spectacle corrected visual acuity was 0.91 ± 0.47 logMAR  prior to corneal transplantation, 0.60 ± 0.36 logMAR  at 1 year follow-up, and 0.20 ± 0.10 logMAR  3 months after suture removal.Changes in mean ± SD spherical equivalent were −3.3 ± 6.3 dpt prior to DALK to −2.6 ± 4.1 dpt after total removal of all sutures. Mean ± SD topographic astigmatism  changed from −6.7 ± 4.0 dpt to −3.45 ± 2.1 dpt, respectively.Mean ± SD central corneal thickness was 442.9 ± 130.1 μm  prior to corneal transplantation, 571.7 ± 54.2 μm  at 1 year follow-up, and 590.9 ± 55.5 μm  at final investigation.2, whereas 12 months postoperatively 2264 ± 350 cells/mm2, and 3 months after suture removal 2040 ± 462 cells/mm2. Mean ± SD endothelial cell loss 12 months after DALK was 4 ± 16%, and 3 months after total suture removal 17 ± 24%.Endothelial cell density preoperatively was 2408 ± 392.1 cells/mmSeventeen eyes (20%) showed loosened sutures during the observation period, and in 13 eyes (16%) Descemet detachment occurred due to intraoperative microperforation of the DM. A poor ocular surface leading to persistent epithelial defect (lasting >2 weeks despite treatment) was seen in 7 eyes (8%). Five of 7 responded to medical treatment and/or bandage contact lens. In 2 of 7 eyes amniotic membrane transplantation and tarsorrhaphy were necessary in cases of ulcerative keratitis. Response to these treatments was seen in 1 eye, but in the other eye only initial response could be observed, subsequently recurrent epithelial defects developed. During the course there was corneal perforation, which required PK à chaud. There was no case of primary graft failure or graft rejection, respectively. Further postoperative complications in recipient eyes are shown in Table p ≥ 0.338; Table None of the clinical outcomes or complication rate after DALK showed a significant association with donor tissue features, including age, gender, post-mortem time, excision technique, preservation time, preservation method, endothelial cell density and central corneal thickness (p ≥ 0.072), respectively.Furthermore, in linear regression analyses for the main clinical outcome parameters including BSCVA and CCT Table , as well2, overall preservation time of ≤14 days for cold storaged donor tissue or ≤35 days in cases of organ culture, and preservation time after split prior to grafting ≤96 h seem to be applicable as safe donor tissue for DALK surgery. Donor tissue quality harvested by corneoscleral disc excision technique is comparable to donor tissue quality after whole globe enucleation. Organ culture method for preservation is suitable as well as 4 °C storage techniques of donor tissues used for DALK. These results may indicate advantages and particularly more feasibility in distribution of donor tissue for DALK recipients for eye banks and in clinical routine.This study revealed no correlation between quality of donor tissue and clinical outcome in deep anterior lamellar keratoplasty. Donor corneas with donor age ≤ 88 years, post-mortem time ≤ 63 h, endothelial cell densities of ≥1000 cells/mmThe selective replacement of the diseased anatomic structure of the cornea under preservation of the healthy tissue in DALK offers distinct advantages over PK. Deep anterior lamellar keratoplasty shows a reduced risk of endothelial cell rejection resulting from the preservation of the recipient endothelium and a reduced rate of intraocular complications , 3, 6. DOur clinical results indicate a good visual outcome with low complication rates, confirming DALK as safe alternative to PK, independent of donor tissue variables.In particular, as new finding, we can outline, that there is no association between preservation method and clinical outcome after DALK surgery and between donor tissue excision technique and outcome parameters. Observations of Feizi et al.  showed, In the literature one can find hints, that a longer post-mortem time and longer storage times may be associated with epithelial defects in the early postoperative period after keratoplasty –22. In oEarly or late loosening of sutures was observed in 17 eyes (20%) and Descemet detachment in 13 eyes (16%). These complication rates appear to be higher than expected. It should be noted, however, that loosening of sutures occur more frequently when interrupted sutures are performed compared to double-running diagonal cross-stitch sutures.Suture loosening was documented as soon as positive Seidel probe of the stitch channel was present or even in case a suture was removed without a retrospectively recognizable reason. Therefore, the rate could be overestimated. As Descemet detachment, any distance of the Descemet membrane was evaluated, even if this was not clinically significant, i.e. even if no stromal edema resulted. To the best of our knowledge, comparative data regarding these complications are rare, therefore a prospective evaluation would be desirable. However, these complications were without relation to clinical outcome parameters. Altogether, none of the outcome parameters revealed statistical significance.Although PK for keratoconus has the highest survival of all indications for corneal transplantation, its main drawback is the risk of endothelial rejection. DALK minimizes the risk of endothelial graft rejection, but patients who received DALK remain susceptible to stromal subepithelial types of graft rejections. The frequency of occurrence differs between rates of 3–21% after DALK surgery , 23, 24.Although some postoperative complications were observed in a few eyes, no graft was lost due to lower tissue quality. Of course, frequent follow-up examinations and appropriate interventions in complicated cases played an important role.Borderie et al. examined 166 patients after anterior lamellar keratoplasty at different time points. None of the main donor characteristics, such as endothelial cell density or preservation time, were correlated to clinical outcome. The only factor that showed influence on outcome parameter was donor age. Donor age > 80 years was associated with lower BSCVA. Borderie et al. recommended to exclude donor grafts of older donors for anterior lamellar keratoplasty . In contIn addition, there was no effect on clinical outcome of preservation time after split and prior to transplantation. Preservation times of the anterior donor lenticule after splitting of up to 96 h were accomplished. Our data are in line with Heindl et al., showing, that splitted donor tissue may be stored safely for up to 1 week in organ culture before use in DALK or DMEK surgery . Also BoThe present study revealed that clinical outcome after DALK surgery is independent of the quality of donor tissue and preservation method. It is based on retrospective collected data, which has both advantages and limitations. One limitation is the heterogeneity of recipient eyes including different corneal pathologies of the anterior corneal stroma. Since DALK surgery is performed less frequently than posterior lamellar keratoplasty in our department, inclusion of a larger more homogeneous cohort of eyes seems to be challenging. Furthermore, clinical outcome parameters i.e. BSCVA results are not entirely dependent on the underlying indication for transplantation but the more on comorbidities. Nevertheless, it would be desirable to additionally examine the impact of donor tissue quality in a more homogeneous cohort including additional assessment of the influence of epithelial status and stromal swelling of the donor grafts at the time point of surgery as well as the parameters that have already been investigated retrospectively in a prospective clinical study to define our presumptions more clearly.In summary our results support expanding inclusion criteria for potential DALK donor corneas. Especially, for DALK older donors up to 88 years, or longer post-mortem times up to 63 h, independent of tissue excision techniques or preservation methods, should be considered as acceptable in the future to counter donor shortage. Whenever it is possible, split cornea transplantation combining DALK and DMEK should be performed, even if, due to logistical problems, a preservation time of the anterior lenticule after split until grafting is needed.


The added value of using a point-of-care (POC) troponin test in primary care to rule out acute coronary syndrome (ACS) is debated because test sensitivity is inadequate early after symptom onset. This study investigates the potential cost-utility of diagnosing ACS by a general practitioner (GP) when a POC troponin test is available versus GP assessment only.A patient-level simulation model was developed, representing a hypothetical cohort of the Dutch population (>35 years) consulting the GP with chest complaints. All health related consequences as well as cost consequences were included. Both symptom duration, selection of patients in whom the POC troponin test is performed, and test performance at different time points were incorporated. Health outcomes were expressed as Quality-Adjusted Life Years (QALYs). The main outcome parameters involve the effect of POC troponin testing on (in)correct hospital referrals, QALYs, and costs.The POC troponin strategy decreases the referral rate in non-ACS patients from 38.46% to 31.85%. Despite a small increase in non-referral among ACS patients from 0.22% to 0.27%, the overall health effect is negligible. Costs will decrease with €77.25/patient (95% CI €-126.81 to €-33.37).The POC troponin strategy is likely cost-saving, by reducing hospital referrals. The small increase in missed ACS patients can be partly explained by conservative assumptions used in the analysis. Besides, current developments in POC troponin tests will likely further improve their diagnostic performance. Therefore, future prospective studies are warranted to investigate whether those developments make the POC troponin test to a safe and cost-effective diagnostic tool for diagnosing ACS in general practices.The online version of this article (doi:10.1186/s12872-017-0647-6) contains supplementary material, which is available to authorized users. Each year almost 200,000 patients in the Netherlands contact their general practitioner (GP) with chest pain . Chest pBesides a patient’s signs, symptoms, medical history, and the information obtained from the ECG, imaging modalities (for example coronary angiography), and laboratory biomarkers of myocardial necrosis (mainly involving high-sensitive troponin), provide additional diagnostic value . As thosIn addition to collecting clinical evidence, proper evaluation of the cost-utility of POC troponin testing in primary care is required. Although randomized controlled trials (RCTs) would provide the best source of evidence, these are commonly very expensive, time consuming, and often do not allow assessment of long-term outcomes or risks , 11. TheWe developed a patient-level simulation model to reflect the diagnostic pathway of chest pain patients presenting to the GP Fig. . This moThe model was populated using data from literature. The following paragraphs present a summary of evidence used, for further details see Additional file In this patient-level model, each hypothetical patient was assigned an age, gender, and disease state (i.e. ACS or no ACS) based on the population distribution derived from a cross-sectional diagnostic study , 13. ForOf all chest pain patients presenting to the GP, 14.7% was immediately referred to the hospital without diagnostic testing, because of a high perceived probability of ACS by the GP  were obtained directly from a systematic review and economic model for STEMI, NSTEMI and UAP patients as well as for healthy patients –26. SepaCosts of both a GP consultation and ambulance transportation to the emergency department were derived from the Dutch cost manual , whereasA probabilistic sensitivity analysis was performed by means of Monte Carlo simulations, using 10,000 iterations of 20,000 hypothetical, unique patients. Distributions were assigned to all parameters under investigation . An overTo determine the value of collecting additional information on this topic, and potentially enhance decision-making on the usefulness of POC troponin in primary care a value of information analysis was performed. The EVPI was calculated to estimate the expected costs of uncertainty in the current model, using a value of information tool developed by the University of Sheffield .To evaluate the probability that the POC troponin strategy is cost-effective, a CEAC was constructed for a willingness-to-pay (WTP) threshold ranging from €0/QALY to €100,000/QALY. A separate CEAC was constructed under the assumption that use of the POC troponin test is only acceptable when it does not lead to health loss (i.e. does not increase the rate of missed ACS patients) and has acceptable cost-effectiveness.The results indicate that the POC troponin strategy costs on average €1144 (95% CI €892 to €1451) per patient, as compared to €1221 (95% CI €955 to €1541) for current practice. The cost savings for the testing strategy are €77 [95% CI €-127 to €-33] per patient. The probability that patients were correctly not referred to the hospital (TNs) would increase from 57.90% to 64.51% (+6.61%). Consequently, unnecessary referrals (FPs) decreased with 6.61% (i.e. from 38.46% to 31.85%). However, the probability of patients being correctly referred to the hospital (TPs) showed a very small decrease from 3.42% to 3.37% (i.e. -0.05%), which in turn resulted in an increase of patients incorrectly not referred (FNs) from 0.22% to 0.27% . In turn, this results in a very small increase in the probability of patients dying of ACS , as well as a small increase in the incidence of heart failure . The overall change in QALYs from POC troponin use is negligible ..Given the negligible impact on health outcomes, it is not useful to calculate an incremental cost utility ratio (ICUR), as this outcome is very unstable for tiny differences in health outcomes as estimated in this study. When combining differences in health outcomes with differences in costs, an incremental net monetary benefit of €69 was found. In the POC strategy, the POC troponin test was used in approximately 40% of all chest pain patients presenting to their GP. This strategy could result in annual cost savings in the Netherlands of approximately €14 million [More specifically, the average cost savings of €77.25 per patient are mainly attributable to a decreased referral rate, resulting in a reduction in costs in primary care with €28.41 per patient , accompanied by a decrease in costs of hospital treatment of €47.62 per patient. Although the lifetime costs per patient are slightly higher (i.e. +€6.58), which is mainly attributable to a small increase in heart failure rates, those higher costs are compensated by a decrease in productivity loss per patient (−€7.80), caused by a decrease in hospital referral rates.Results indicate that the overall EVPI per person presenting with chest pain in primary care is estimated to be €0.22. Based on a decision relevance of ten years, and an estimated 182,897 individuals presenting with chest pain in this period, this results in an overall EVPI per year of €403,364 in the Netherlands [The CEAC indicates that the probability of the POC troponin strategy to be cost-effective ranges from 100.0% to 52.7%, for a WTP threshold of €0 to €200,000/QALY. For a WTP of €20,000/QALY, this probability was 98.4% Fig. . Thus, wUsing a POC troponin test in primary care is expected to increase the probability at which the GP is able to correctly exclude ACS (TNs), accompanied by a decrease in unnecessary hospital referrals (FPs). However, the rate of correct referrals (TPs) decreases slightly, while the rate at which ACS patients are incorrectly not referred (FNs) shows a small increase. Despite this, the average per patient effect on QALYs is very small (i.e. -0.0004). Costs per chest pain patient are expected to decrease with approximately €77, indicating that the POC troponin strategy is likely cost-saving as compared to current practice.The main strength of the current study is that it was designed to accurately represent the current work-up of GPs, in chest pain patients. To achieve this, three real decisions were built into the model, in which the POC troponin test is unlikely to be used: 1) when the GPs considers a patient at high risk of ACS, 2) when the GP diagnoses STEMI using an ECG, or 3) when a patient presents <4 h after symptom onset. Consequently, the POC troponin test is only used in approximately 40% of all chest pain patients presenting to the GP. Furthermore, as it is unlikely that GPs base their referral decision solely on a POC troponin test result, the probability of GPs adhering to this result was also incorporated. Although those assumptions inevitably limit the potential impact of the POC troponin test, they are crucial to obtain a realistic estimate of the test’s potential cost-utility.Secondly, the use of a patient-level model has several advantages. First of all, probabilities of ACS are both age and gender specific, allowing to estimate costs, QALYs and productivity losses at the individual patient level. In addition, a duration of symptoms was assigned to each patient, allowing to incorporate time-dependent sensitivities and specificities, which is an important characteristic of the POC troponin test .Furthermore, all assumptions used in the analysis were conservative regarding the potential impact of POC troponin, which may have led to underestimating both cost savings and health benefits. First, the delay by POC troponin testing was set at 10 min, thereby assuming that the test is performed after the consultation by the GP, whereas it is likely that the test can already be performed during the patient’s anamnesis and physical examination. Besides cost savings, this work-up would also prevent the potential negative health impact caused by a delay in treatment. Second, it was assumed that GPs would perform the test in all remaining chest pain patients, and therefore also in patients that are not actually suspected of having ACS. However, GPs can probably exclude ACS with certainty in some patients without using the POC troponin test, thereby saving costs. Third, it was assumed that the 14.7% of patients that are perceived to be at high risk of ACS by their GP (and who are immediately referred), corresponded to the patients with the highest actual probability of ACS. This assumption most likely overestimates the ability of the GP to identify high-risk patients.There are two limitations to be mentioned. First, evidence on the correlation between several input parameters were lacking. For example, no evidence was available on the relationship between a) the pre-test probability of ACS, b) diagnostic accuracy of the GP in current practice, and c) the diagnostic accuracy of the POC troponin test. Similarly, no evidence was available on the potential influence of patient’s characteristics, such as age and gender, on the probability that the GP revises his or her initial referral decision following a discordant POC troponin result. Therefore, changes in referral decisions made in practice may concern different patients than those with a change in referral decision in our model. However, results of a systematic review and meta-analysis indicate that it was not possible to define an important role for signs and symptoms in diagnosing AMI or ACS . AccordiSecond, as this study is based on a hypothetical cohort of patients, the impact of POC troponin testing on health outcomes is dependent on the literature used in the model. However, evidence regarding the diagnostic performance of GPs (without the use of POC) is limited. The drawback of the study used in the current analysis, is that the sensitivity of the GP was based on their ‘action in daily practice’ in chest pain patients. This definition however, included besides referral to the hospital, also exercise testing, prescribing medication, and requesting a second opinion . In addiResults from a previous study indicate that GPs’ main requirements regarding POC troponin tests are a) test result within 10 min, b) a test performed with a finger prick, and c) reimbursement of the POC analyzer . RecentlOwing to the expected reduction in hospital referrals, the POC troponin strategy is likely cost-saving. The potential (accompanying) small increase in missed ACS patients can partly be explained by conservative assumptions used in the analysis. In addition, ongoing developments in POC troponin tests will likely further improve their diagnostic performance. Therefore, the use of a POC troponin testing strategy is likely to become cost-effective in the nearby future. When data from new prospective (randomized) studies into the safety and diagnostic accuracy of the use of POC troponin tests become available, the health economic model presented here allows rapid reassessment into the benefits of such a diagnostic tool for diagnosing ACS in general practices.Additional file 1:Model input parameters. This file contains an overview of all model input parameters, including the value used in the model, the 95% confidence interval, the distribution used, and the data source (DOCX 73 kb)Additional file 2:Overview of model assumptions. This file contains an overview of all assumptions that have been used in the health economic analysis (DOCX 18 kb)Additional file 3:Results of partial perfect value of information analysis. This file contains an overview of the results of the partial perfect value of information analysis (DOCX 13 kb)


Most of the objective and quantitative methods proposed for spasticity measurement are not suitable for clinical application, and methods for surface electromyography (sEMG) signal processing are mainly limited to the time-domain. This study aims to quantify muscle activity in the time–frequency domain, and develop a practical clinical method for the objective and reliable evaluation of the spasticity based on the Hilbert–Huang transform marginal spectrum entropy (HMSEN) and the root mean square (RMS) of sEMG signals.Twenty-six stroke patients with elbow flexor spasticity participated in the study. The subjects were tested at sitting position with the upper limb stretched towards the ground. The HMSEN of the sEMG signals obtained from the biceps brachii was employed to facilitate the stretch reflex onset (SRO) detection. Then, the difference between the RMS of a fixed-length sEMG signal obtained after the SRO and the RMS of a baseline sEMG signal, denoted as the RMS difference (RMSD), was employed to evaluate the spasticity level. The relations between Modified Ashworth Scale (MAS) scores and RMSD were investigated by Ordinal Logistic Regression (OLR). Goodness-of-fit of the OLR was obtained with Hosmer–Lemeshow test.2 = 8.8060, p = 0.2669; retest: χ2 = 1.9094, p = 0.9647). The prediction accuracies were 85% (test) and 77% (retest) when using RMSD for predicting MAS scores. In addition, the test–retest reliability was high, with an interclass correlation coefficient of 0.914 and a standard error of measurement of 1.137. Bland–Altman plots also indicated a small bias.The HMSEN based method can precisely detect the SRO, and the RMSD scores and the MAS scores were fairly well related (test: χThe proposed method is manually operated and easy to use, and the HMSEN based method is robust in detecting SRO in clinical settings. Hence, the method is applicable to clinical practice. The RMSD can assess spasticity in a quantitative way and provide greater resolution of spasticity levels compared to the MAS in clinical settings. These results demonstrate that the proposed method could be clinically more useful for the accurate and reliable assessment of spasticity and may be an alternative clinical measure to the MAS. Spasticity is a serious and potentially disabling complication of stroke . In the At present, the dominant clinical method for assessing spasticity is the Modified Ashworth Scale (MAS), which provides for great simplicity in clinical assessment, but nonetheless represents a semi-quantitative method that depends on subjective physiotherapists evaluations based on experience –11. MoreThe subjective and imprecise assessments of spasticity are not sensitive enough to slight changes of patient’s status . They maMany studies have reported on the inaccurate and unreliable results obtained in the clinical assessment of spasticity, demonstrating the need to improve assessment accuracy and reliability –16. HoweAmong the proposed methods, the tonic stretch reflex threshold (TSRT) seems to be the most promising approach . The strHowever, no consensus has yet been attained regarding the detection of the SRO . In clinThe nature of sEMG signals presents numerous processing challenges. sEMG signal is sparsely distributed in the time–frequency domain, and current detection approaches only expand signal in the time domain. The more detailed information in each frequency component is absent . As suchThe Hilbert–Huang transform (HHT) is a relatively new time–frequency analysis approach, which is well suited for processing non-linear, non-stationary signals such as sEMG signals . HHT marThis study proposes a new practical clinical assessment method based on the HMSEN and the root mean square (RMS) of sEMG signals. The method detects the SRO based on the HMSEN of sEMG signals, and directly assesses spasticity quantitatively based on the difference between the RMS of a fixed-length sEMG signal obtained after the SRO and the RMS of a baseline sEMG signal.The objectives of this study are to determine (1) the ability of the HMSEN to detect the SRO, (2) the relationship between the spasticity levels obtained clinically based on the MAS and the RMS difference measured from sEMG signals, (3) the test–retest reliability of the proposed method between days, and finally to (4) develop a clinical practical method of spasticity assessment, which is simple to operate and could provide greater resolution of spasticity level and better treatment and rehabilitation programs in clinical settings.Twenty-six patients  with stroke participated in the study . All the subjects were from Anhui Provincial Hospital. The study was approved by the ethics committee of Anhui Provincial Hospital. All subjects gave written informed consent approved by Anhui Provincial Hospital. For assuring confidentiality, the subjects were identified through the use of an Arabic numeral code, and no identifying information was recorded .Subjects were included if they had (a) sustained a stroke; (b) elbow flexor spasticity; (c) at least a 90° passive range of motion in the elbow joint; (d) good awareness and no serious cognitive, visual, or auditory disorders.Subjects were excluded if they had (a) other concurrent central nervous system disorders that may lead to myodystonia, e.g., Parkinson’s syndrome or multiple sclerosis; (b) other concurrent diseases that may compromise movement of the upper limb elbow joints, e.g., upper limb fracture or pain.Each subject’s eligibility was carefully reviewed by an attending physician. The clinical characteristics of the 26 participants are listed in Table Acquisition of the sEMG signal from the biceps brachii was accomplished using three electrodes via a three-point differential input. The patient’s skin at the points of electrode application was first wiped with an alcohol-soaked cotton swab to remove surface grease and dander. Two electrodes corresponding to the sEMG differential input were placed over the motor point of the biceps brachii muscles along the direction of the muscle fibers. The centers of the two electrodes were separated by 20 mm. The remaining electrode was designed as a reference point and was placed over the skin without any muscle activity.The acquired sEMG signals were first filtered and amplified. The sEMG acquisition system consisted of a 10 Hz notch filter and a 500 Hz low-pass filter to remove the noise of the sEMG signals, and the filtered signals were amplified by a factor of 1000. The sEMG signals were then converted via a 12-bit analog to digital converter (ADC)  at a sampling rate of 1 kHz, and transferred to a personal computer via USB ports. To store and analyze the data obtained during the study, data acquisition software were developed using Microsoft Foundation Classes (MFC). The trace of sEMG signals was continuously displayed on a monitor, and simultaneously stored on the computer. The data were employed to detect the SRO for each subject tested and investigate the correlation between the RMSD and MAS scores.Each subject was tested in a seated position with the upper limb stretched toward the ground. Prior to assessment, a professional physiotherapist manually stretched the upper limb of each subject to assist the subject in adapting to the extension activity to avoid inaccuracy of spasticity assessment due to sudden extension. Subsequently, the physiotherapist performed a standard MAS scoring for each subject at a proper stretch velocity based on his professional experience. Here, we define elbow extension as a motion from full flexion, which represents the maximum flexion allowed by the upper arm and forearm without making contact between them, to full extension, representing the maximum extension allowed by the arm and the forearm. An MAS testing session consisted of a single elbow extension Fig. . For purPatients with spasticity have suffered damage to their upper motor neurons. The central lesion disrupts the balance of supraspinal inhibitory and excitatory inputs directed to the spinal cord, leading to a state of disinhibition of the stretch reflex. Decreased postsynaptic inhibition is involved in the hyperexcitability of the stretch reflex, which ultimately changes the electrophysiological output, manifesting as an increased complexity of sEMG signals in the time and frequency domain , 32. Thix(t) provides n intrinsic mode functions (IMFs) ci(t) and a residue signal rn(t) as follows:The fundamental component of HHT  is the eci(t), its Hilbert transform H(ci(t)) is defined as:For any ai(t) and φi(t) are the amplitude and instantaneous phase, which are respectively given asTo construct the analytic signal:x(t) can be expressed asfi(t) is the instantaneous frequency, which is defined asCorrespondingly, The Hilbert–Huang spectrum is then defined to represent the frequency–time distribution of the amplitude:t to generate the Hilbert marginal spectrum of the signal:Then, Eq.  is subjeh(i) for discrete frequency points f = iΔf:n represents the number of discrete frequency points within each analytic frequency band.The marginal spectrum offers a measure of total amplitude (or energy) contribution from each frequency value. Equation  can be rpi = h(i)/∑h(i), and pi is the probability of occurrence of an event and here it refers the probability density of the spectrum and the occurrence probability of amplitude corresponding to the i th frequency.Correspondingly, the HMSEN is expressed according to the definition of information entropy asN represents the sequence length of h(i).The HMSEN values are then normalized in the range , yielding the new HMSEN as follows:k points) with a frame shift of m points. The HMSEN of each signal frame was calculated and denoted as MsEn. Subsequently, an adaptive threshold Th was set according to minimum and maximum values of MsEn  as follows:λ is the sensitivity factor of Th. Here, the MsEn values were adjusted according to Th, where MsEn values less than Th were reassigned as 0, and MsEn values greater than Th were retained. The adjusted MsEn values are denoted as En. If, at a given point in time, an En value was greater than 0 and all n consecutive En values afterward were greater than 0, that point in time was determined to be the SRO. Considering a reasonable tradeoff between the computational burden and the desired level of accuracy, the values of these parameters were set as k = 90, m = 3, n = 50, and λ = 0.3 or 0.35.The HMSEN of sEMG signals obtained from the biceps brachii of patients was employed to detect the SRO according to the following procedure as shown in Fig. The detection algorithm is outlined in Fig. t0 − 50, t0 + 50] to obtain the recognition rate of the algorithm. The recognition rate is defined asTD and FD represent the number of true detection and false detection, respectively. A classification is counted as TD if the detected onset time is within the interval , and classifications are counted as FD if the detected onset time is outside the interval . Here, t0 is the onset time obtained by the physiotherapist using VI.Activity bursts of short duration (25–40 ms) are considered to have little effect on the resulting kinetic output . TherefoThe most cited method proposed by Calota A to measure TSRT , in whicThe performance of the proposed method was evaluated using semi-synthetic sEMG signals where the onset time was artificially set. To construct the semi-synthetic sEMG signals employed for testing, we collected actual sEMG signals of the biceps brachii of elbow flexor spasticity patients, and two types of experimental signals were first identified. The first type represents quiescent baselines obtained during passive stretching. The second type represents clear sEMG signals where SRO occurred during passive stretching. The duration of each segment was 1000 ms.The SRO is accompanied by an excessive reflex activation of α-motoneurons, and the number of excitatory motoneurons and the electric activity are both increased. As a result, the RMS values of the sEMG signals increase with increasing muscle tension . Hence, Xi is the i th sampling value of sEMG signals.The RMS is as follow:generalhoslem [p = 0.05.The relations between MAS scores and RMSD are investigated by Ordinal Logistic Regression (OLR) using R software. The quality of the RMSD in spasticity assessment was evaluated by how well the classes of the MAS test were predicted by the RMSD based on confusion matrix. Goodness-of-fit of the OLR was assessed with Hosmer–Lemeshow test with the R package alhoslem . The tesalhoslem , implemealhoslem , implemealhoslem . We emplalhoslem . All staThe data processing results based on the developed detection algorithm for subjects 1, 2, 7, and 19 with varying MAS levels are shown in Figs. Figure The RMSD of each subject is listed in Table 2 = 8.8060, p = 0.2669). Regarding the retest, the RMSD scores and the MAS scores are also fairly well related , which demonstrates that the RMSD can quantitatively assess the level of upper limb spasticity.An OLR was performed with the three levels of the MAS score as outcome measure and RMSD test as a predictor. The Hosmer–Lemeshow test Table  shows siThe confusion matrix Table  shows ho2 = 7.3070, p = 0.3976; retest: χ2 = 3.8367, p = 0.7984), and overall accuracy of the test and retest are 0.77 and 0.62 predicted predicting MAS scores with the RMSD respectively. These results mean the RMSD can achieve improved performance over the RMS in spasticity assessment, and decrease the individual difference effect to some degree.However, the goodness-of-fit of the OLR when considering only the RMS of sEMG signals after the SRO are (test: χThe results of the test–retest reliability study are listed in Table p = 0.089) were not significant.Through a post hoc analysis by means of the Bonferroni test, it was found that the differences between the RMSD values of the MAS 1 group and that of the MAS 1+ group  or no movement possible (score 4) . TherefoWe note that the recognition rate of 96.3% obtained by the HMSEN is considerably greater than the recognition rate of 87.5% correspondence with VI using the Teager-Kaiser Energy Operator method . Hence, While this study provides some evidence for the good test–retest reliability of the system, Rankin and Stokes  have recp = 0.089). Hence, this supports the questionability of the MAS due to its subjectivity and the equivocal descriptions employed, where the rate of change in passive resistance and the joint angle at the onset of stretching are what physiotherapists actually examine based on their experience [No significant differences of the average RMSDs between the MAS1 and MAS1+ groups were detected  to assess the spasticity levels of patients. In a future study, we plan to equip our device with extra force sensors and use multiple parameters to assess spasticity level, such as the mean power–frequency of sEMG signal, the joint resistance and the SRT.A quantitative method to measure spasticity may provide physiotherapists with accurate understanding of spasticity and optimal treatment plans for patients. The proposed method takes the advantages of the MAS and portable manual system and is easy to operate. Hence, the proposed method permits physiotherapists to assess the level of spasticity reliably, easily and unrestrictedly. Compared with the clinical scales for spasticity assessment, which are not sensitive enough to status changes of patients, it can provide clinicians with a greater resolution of spasticity level. Another advantage is that RMSD values can also provide clinicians with insight into the etiology of spasticity in the future, for it mainly demonstrates the neural response to the muscle stretch . From a This report presented a novel framework for upper limb spasticity assessment based on the analysis of sEMG signals for detecting the SRO and for the direct quantitative assessment of spasticity. Experimental results demonstrated that the HMSEN based method could precisely detect the SRO. The statistical analysis results demonstrated a strong correlation between the RMSD and the MAS scores obtained for spasticity patients, and good test–retest reliability. This method is manually operated and easy to use, so it can make quantitative spasticity assessment readily available in clinical practice, and therefore enhancing diagnostic and recovery of patients. The preliminary results suggest that the proposed method could potentially provide useful clinical information, and may be viewed as an alternative clinical measure to the MAS in clinical settings.


The designing, collecting, analyzing, and reporting of psychological studies entail many choices that are often arbitrary. The opportunistic use of these so-called researcher degrees of freedom aimed at obtaining statistically significant results is problematic because it enhances the chances of false positive results and may inflate effect size estimates. In this review article, we present an extensive list of 34 degrees of freedom that researchers have in formulating hypotheses, and in designing, running, analyzing, and reporting of psychological research. The list can be used in research methods education, and as a checklist to assess the quality of preregistrations and to determine the potential for bias due to (arbitrary) choices in unregistered studies. From the inception of the first study idea to the final publication, psychological studies involve numerous choices that are often arbitrary from a substantive or methodological point of view. These choices could affect the outcome of significance tests applied to the data, and hence the conclusions drawn from the research. These choices are also called researcher degrees freedom  in formuCortex, Comprehensive Results in Social Psychology, and Perspectives on Psychological Science (for Registered Replication Reports).Among many potential solutions to counter inflated effects and elevated chances of finding false positive results caused by researcher degrees of freedom, one solution has received most attention: preregistration . Preregispecific, precise, and exhaustive plan of the study. That is, the ideal preregistration should provide a detailed description of all steps that will be taken from hypothesis to the final report (it should be specific). Moreover, each described step should allow only one interpretation or implementation (it should be precise). Finally, a preregistration should exclude the possibility that other steps may also be taken (it should be exhaustive). Hence, a preregistration specifies the project in such a way that all potential contingencies in formulating hypotheses, and designing, running, analyzing, and reporting are covered. For instance, the syntax for the statistical analyses should preferably be created in advance to be run (once) on the collected data to yield the final statistical results. Our own experiences with preregistration taught us that this specification is no easy task and that maneuverability remains if preregistrations are not sufficiently specific, precise, or exhaustive. For instance, just indicating one’s use of a certain scale as the main outcome measure in an experiment typically does not preclude the researcher to attempt many different ways in how to score the items of the scale in his or her pursuit for statistical significance. A preregistration should also be exhaustive because the stipulation that one will test Hypothesis A in a certain way does not preclude the possibility that one can also test Hypothesis B in the study. Therefore, for confirmatory aspects of the study, the word “only” is key .To disallow researchers to still use researcher degrees of freedom, it is crucial that preregistrations provide a The goal of this paper is to present a list of researcher degrees of freedom that can be used in research methods education, as a checklist to assess the quality of preregistrations, and to determine the potential for bias due to (arbitrary) choices in unregistered studies. By pointing out many different researcher degrees of freedom, we hope to raise awareness of the risk of bias implicit in a lot of research designs in psychology and beyond. The list enables a charting of what Because NHST is by far the most used statistical framework used in psychology and related fields, we created the list of researcher DFs with NHST in mind. Other possible statistical frameworks are based on confidence intervals , precisiWe created the list in a qualitative manner; we as a group of methodologists studying researcher DFs, publication bias, meta-analysis, misreporting of results, and reporting biases, came up with a large list of researcher DFs, discussed these, and created a manageable list in several rounds of revision. We are aware that our list may not be exhaustive, but believe the list is a good starting point for a checklist that serves the purpose to assess the degree to which preregistrations truly protect against the biasing effects of researcher DFs. Most of the researcher DFs have been described in previous publications . The resTable 1. We focus on experiments as the most basic design used to study the  effect(s) of independent variable(s) on the dependent variable(s). This design is the most widely used in psychology and entails a good archetype to discuss the many researcher DFs in a multitude of research designs, including quasi-experimental studies and correlational studies aimed to explain dependent variables on the basis of one or more predictor variable(s).We discuss the different researcher DFs categorized under headers that refer to different phases in a study from its early theoretical underpinnings to its final publication , and indicate links between different researcher DFs at the different phases. Each researcher DF will be coded according to its phase. All researcher DFs are listed in a priori theorizing on  relations. Such exploratory studies are virtually guaranteed to yield support for something interesting  patterns in the data often lack eresting . Since meresting , it is teresting . The relhe study . Note thT2: Studying a vague hypothesis that fails to specify the direction of the effect. Note that specifying the direction of the hypothesized effect is relevant for the decision to use a one- or two-tailed test. One-tailed tests can only be used to reject the null hypothesis when the a priori hypothesis was directional and the result was in the predicted direction. Testing hypotheses requires specificity and precision regardless of whether one uses one- or two-tailed tests. Consequently, a preregistered hypothesis needs to specify the direction of the effect or relation. Because of the need for proper power analyses (discussed below under D6), it is also important to have a prior sense of the size of the effect or strength of the relation.However, even if there is a vague prior notion about the relation between the independent and dependent variables, hypotheses that fail to indicate the direction of an effect (or relation) enable later flexibility in the analysis and interpretation of results . If the Although most researcher DFs discussed in the literature pertain to the analysis of the data, both the theoretical predictions and the design of an experiment (or other types of studies) already allow the researcher to create options for flexible analyses in later phases of the study. A psychological experiment can be set up to have a certain degree of redundancy in the design that creates maneuverability in the collection of data, analysis of data, and reporting of results. This redundancy applies to both independent variables and dependent variables.We distinguish here between manipulated and non-manipulated independent variables. Manipulated independent variables are those manipulated in the design of the experiment, and typically involve randomization. In contrast, non-manipulated independent variables are based on measures of behavior or individual differences that (could) pertain to the research question. These independent variables are the main focus in correlational studies, but are also widely used in studying (moderation of) experimental effects. Moreover, additional measures taken after the manipulation or in correlational studies could later be used as mediators in explaining variance in the dependent variable, but an underspecified preregistration enables researchers to use these variables as primary dependent variable as well (see our Discussion of D4).: D1 creating multiple manipulated independent variables and conditions. Like all researcher DFs, this researcher DF becomes more relevant as the number of scoring options increases, like with complex mixed designs involving multiple between-subject and within-subject factors featuring multiple levels. Consequently, preregistrations of such studies should specifically and precisely delineate how independent variables are later used in testing the focal hypotheses.Experiments can involve multiple manipulated independent variables , that are often crossed and that researchers can select or discard in later analyses based on particular (preferred) outcomes. Dropping of experimental conditions has been found to be quite common in a survey among psychological researchers  and in aD2: Measuring additional variables that can be selected later as covariates, independent variables, mediators, or moderators. Obviously, adding more measures offers multiple ways to find interesting patterns in later stages of the study. Just as manipulated independent variables can often be operationalized in different ways, many non-manipulated independent variables, once selected, offer flexibility in how they will be used in the analyses. Participants can be assigned to different levels of those independent variables on the basis of flexible thresholds or category assignments  as in ANCOVA. For instance, measured age can assume any of these roles in later analyses: e.g., for studying age differences, for testing whether age moderates the effects of any of the other independent variable(s), or as a control variable to explain some of the within-condition variation in the dependent variable. Moreover, measures taken after the manipulations can be used in later mediation analyses to explain variance in the dependent variable. This entails ignments . For insIn sum, a research design that is littered with research DFs related to independent variables is complex and offers room for selecting and operationalizing these variables in multiple ways. An ideal preregistration, then, specifically and precisely specifies which manipulated independent variables and non-manipulated independent variables will be used in the analyses and also indicates how both types of variables are to be operationalized, and that no other variables are to be used in the confirmatory analyses. We again emphasize that these specifications are only necessary for the confirmatory analyses; a potential exploratory analyses section of a paper is not at all problematic, as long as the preregistration and the paper clearly distinguish between these very different types of analyses.D3: Measuring the same dependent variable in several alternative ways. For instance, anxiety can be measured with various self-report scales, or with physiological measures .The measurement of human behavior is often complex and is seldom done in a single predefined manner. A design prone to bias due to researcher DFs offers multiple dependent measures of the same construct. This enables the researcher to choose among different outcome measures the one(s) that offer(s) statistical significance. The relevant researcher DF in the design phase is different constructs in cases where the originally targeted primary outcome failed to show statistically significant effects. Among the research practices studied by D4: Measuring additional constructs that could potentially act as primary outcomes.Another particularly flexible design allows the researcher to choose among several dependent variables that concern not specific and precise enough to avoid p-hacking during analyses, because often the scores on such measures can be computed in different ad hoc ways.Thus in the design of studies, the researcher can already create many researcher DFs that allow for opportunistic use in later phases of the research process, relating to using multiple measures of the same construct (D3), and creating opportunities to find additional effects by adding measures of additional constructs besides the one(s) that were the original focus of interest (D4). D4 allows HARKing , whereasad hoc manner from the analysis. For instance, a researcher might decide to exclude older-aged participants for some reason that might actually not be independent of the effect of the exclusion on the final analysis. Such exclusion of cases on the basis of measured variables often comes across as ad hoc because if that decision rule had been a priori, these older-aged participants should not have completed the study in the first place.Adding numerous measures besides the main independent and dependent variables to the design offers yet another researcher DF: background variables  or other individual differences can be used to later discard participants in an D5: Measuring additional variables that enable later exclusion of participants from the analyses . Therefore, an ideal preregistration specifically and precisely describes which types of participants will be excluded from the analyses, and also explicates that the stated rules of exclusion will be the only ones that will be used to discard participants (it should be exhaustive). The reason is that only stating a particular exclusion rule in the preregistration does not preclude the possibility to also exclude participants on other ad hoc grounds.Other types of measures that can be used to discard participants include awareness checks, as often used in priming research  small studies.A rigorous preregistration not only provides a good rationale for the sample size in the form of a power analysis, but also should describe the complete sampling plan, i.e., the targeted sample size, when the data collection starts and ends, and how the participants are to be sampled. The sampling plan should specify the population from which is sampled, the procedure of sampling, and the end point of data collection. The sampling plan should also specify when additional participants are to be sampled in cases where the targeted sample size is not met . The sampling plan should be specific and precise to disallow researchers to conduct intermediate tests during data collection. If not, a researcher can decide to collect more data after witnessing a non-significant result or to cease data collection earlier than planned if the result is already significant , both of which affect the Type I error rate. The sampling plan should also preclude the researcher to conduct a particular study multiple times, and only present the “best” study . The use of multiple small studies instead of a larger one is an effective (yet problematic) strategy to find at least one statistically significant result  and smalt result . Hence, During the collection of experimental data, it is possible to act in certain ways that enhance the probability of finding a statistically significant result. Most of the issues are methodological, although some are statistical and bear on issues of multiple testing and sequential analyses. In our discussion, we assume that the design itself is internally valid and that the measures are construct valid, in the sense that the experiment does not involve any confounds or artifacts and uses appropriate measures. This, of course, does not always mean that the actual study does not suffer from threats to internal validity or construct validity.C1: The failure to randomly assign participants to conditions.Although methodological textbooks are clear on the benefits of random assignment, the randomization techniques used to assign participants to conditions are often not specified in research articles. Using non-random assignment could greatly affect differences between conditions in personal characteristics or other factors that could affect the outcome. For instance, an experimenter might (purposively or not) only run treatment participants in the evening, thereby creating a potential confound, or the assignment could be based on observable personal characteristics that might bear on the outcome measure . In other words, the randomization technique should be specifically and precisely stipulated in advance and followed throughout the experiment, thereby avoiding C2: Insufficient blinding of experimenters and/or participants could potentially introduce bias. For instance, experimenters could use non-naïve participants  or (in)avertedly convey information about what is expected from participants in a given condition. The preregistration study should specifically and precisely describe the procedure of how participants and experimenter(s) are blinded, if applicable.It is widely recommended to employ double-blinding techniques to avoid demand characteristics and placebo effects on part of participants as well as experimenter expectancy effects during data collection . ParticiC3: Correcting, coding, or discarding data during data collection in a non-blinded manner.If experimenters are involved in coding or other ways of data handling, incomplete blinding concerning condition assignment or hypotheses could introduce bias. Working with participants is a social process in which experimenters has information about participants or their behavior that might enable them to predict scores on the dependent variable for individual participants. For instance, an experimenter may witness a slowly working student in a condition that is expected to yield quick responses and might decide to discard that participant for not participating seriously even though there is no clear experimental protocol that dictates such a decision. This creates biases during the data collection, and such biases are particularly problematic in experiments involving coding of behavior in a non-blinded manner. Similarly, missing values or incorrectly filled out answers on a questionnaire or test could also be corrected or filled out during data collection by someone who is not blind to condition (or the hypotheses) and hence might make biased decisions. For instance, the experimenter could decide to correct or fill in the answer of a participant who indicated the incorrect gender or no gender on a questionnaire. Although making such corrections or imputations deliberately might go beyond questionable and so might entail falsification (a violation of research integrity), doing this without awareness in a poorly structured research setting might nonetheless cause considerable bias. A specific, precise, and exhaustive research protocol can help avoid this researcher DF. C4: Determining the data collection stopping rule on the basis of desired results or intermediate significance testing. A specific and precise a priori sampling plan could ameliorate this, and so this researcher DF is related to D7 described above.The decision whether or not to continue with data collection could be dependent on intermediate analyses of the data. This is reflected by the common practice to continue data collection after witnessing a statistically non-significant result or by quitting data collection earlier than planned after witnessing a statistically significant result . It is wIn the analysis phase, the researcher directly witnesses the effects of choices on the statistical outcome. It is surprising that blinding to conditions and hypotheses of experimenters, coders, and observers is considered to be crucial during data collection, while in practice, the analyses are typically conducted by a person who is not only aware of the hypotheses, but also benefits directly from corroborating them (commonly by means of a significance test). Together with the many researcher DFs during the analyses, these factors do not entail the most optimal mix for objective and unbiased results.A1: Choosing between different options of dealing with incomplete or missing data on ad hoc grounds.Before running the focal analyses, experimental data often need to be cleaned and prepared for analysis. Data cleaning involves many choices related to missingness, outliers, or violations of the distributional assumptions. Because of potential drop-out, data collection problems, or a lack of full responses for other reasons , some data might be missing entirely for participants or for some or many of the variables of interest. Missing data can be dealt with by listwise deletion, pairwise deletion, multiple imputation, full information methods, and other methods . This chA2: Specifying pre-processing of data  in an ad hoc manner.Neuroimaging techniques  and other data-intense measurement procedures require extensive pre-processing steps that entail considerable maneuverability in the analysis of the data . For insF-family of parametric tests is that the data are independently normally distributed and that variances of different groups are homogenous. There are various ways to deal with violated assumptions of such statistical tests: one could use non-parametric analyses, transform the data in various ways to approach normality or simply ignore the violations. Moreover, violations of variance homogeneity in ANOVAs or t-tests, non-normality, non-linearity in linear models, or heteroscedasticity in regression could be dealt with in several alternative ways . While running the analysis, the researcher can choose between different measures or operationalizations of the same construct implemented in the design of the study in an effort to find the measure that shows the preferred or best results. This practice, which is paired with the use of various measures in the design (D3), concerns the following researcher DF: A6: Trying out different ways to score the chosen primary dependent variable.The dependent variable, once selected, can often be scored or operationalized in various ways. There also exist degrees of freedom even if there is only one overall measure or scale. Discarding, weighting, selecting, or redefining scoring rules of individual items can offer flexibility in analyses even if the items are based on a commonly used scale. For example, items of a scale that are originally measured on a five-point Likert scale can be dichotomized, or some items might be discarded from the scale score for showing low or negative item-rest correlations. Moreover, the scale score can be based on an unweighted sum of item scores or on weighting of items based on an item response model, or by running a principal components analysis and choosing among alternative ways to estimate the factor scores. So even for existing scales, flexibility exists in operationalizing the scores in the analyses. The use of response time data involving responses to many stimuli also involves many choices in dealing with slow response times, and how to summarize the major outcome variable. The researcher DF is A7: Selecting another construct as the primary outcome.Finally, researchers can choose to measure additional constructs next to the one(s) originally targeted as the main dependent variable (or primary outcome) in the design (see D4). During the analyses this creates A8: Select independent variables out of a set of manipulated independent variables (paired with D1). Similarly, even for a given manipulated variable, the researcher can often choose to discard or combine different levels of factors, which creates A9: Operationalizing the manipulated independent variables in different ways .If we consider the ANOVA as a regression model, the use of independent variables means selecting among numerous predictors and/or interaction terms to predict the outcome, and hence different regression models. Without specific preregistration, a researcher often has numerous options to choose between different regression models. The researcher can also typically operationalize the non-manipulated and manipulated in various ways, particularly in flexible designs. During the analysis, the researcher can employ A10: Choosing to include different measured variables as covariates, independent variables, mediators, or moderators in the analysis. The number of different analytic options considered for finding some statistically significant result  on the basis of measured variables can be quite large. For instance, adding big five personality measures to a simple one-way experimental design enables the researcher to seek for the moderation of effects by all of these personality traits. However, these big five traits can also be used as covariates, or simply as independent variables to help explain variance in the outcome measure(s). More degrees of freedom are added if the researcher does not specifically and precisely describe in advance how these measured variables are to be used and scored in the analysis , as well as possible mediator variables measured during the study, thereby creating analysis . For exaAn exceptionally flexible analysis involves many different regression models based on a host of different combinations of predictors , and alternative ways to operationalize these predictors, leading to a very large number of regressions  in some A12: Use of alternative inclusion and exclusion criteria in selecting participants for use in the analysis. This researcher DF is paired with D5, i.e., the design choice to include many additional variables related to manipulation checks or awareness checks or any other personal characteristics that can be used as selection criteria. There are many bases to select or deselect participants for the analysis, including performance , awareness questions, or any personal characteristics. A specific, precise, and exhaustive plan to not include particular participants in the final data analyses not only avoids this researcher DF, but could also spare resources by simply not collecting any  data for participants who fail to meet the inclusion criteria. For instance, if a linguistics researcher is not interested in participants who are not native speakers of the language of interest, he or she would be better off not running these participants at all, instead of excluding their data only at the analysis phase.One can also change the analysis by altering the sample size on the basis of different criteria to (de)select participants. This yields A13: Choice of the statistical model. However, choosing the statistical model , often does not preclude additional statistical choices. Specifically, statistical models need to be estimated and this can frequently be done in several ways. Even with a given estimation method, the researcher can choose between different corrections to the standard errors (SEs) of parameters. For instance, one could choose for robust SEs instead of the standard SEs. Moreover, different statistical software packages  often implement the same estimation techniques and correction methods in slightly different ways, leading to diverging results. These alternative estimation methods, software packages, and correction methods might lead to different outcomes and hence entail a researcher DF: A14: The choice for estimation method, software package, and computation of SEs. To wit, even a standard ANOVA requires a choice between different types of sum of squares, three of which are available in SPSS . This problem is particularly vexing for more advanced analyses, that can be estimated with Maximum Likelihood, Ordinary Least Squares, Weighted Least Squares, Mean and Variance Adjusted Weighted Least Squares, Partial Least Squares, or Restricted ML, with or without robust SEs (to name just a few options).Even for relatively straightforward experiments, many different statistical models can be used to analyze experimental data, including linear regression, ANOVA, MANOVA, or robust or non-parametric analyses. Hence, an obvious researcher DF is A15: Choosing inference criteria  is another researcher DF. For instance, a researcher can choose to use a one-sided test if this is the only way to obtain significance, or employ more lenient corrections for multiple testing if the need arises. Preregistrations should explicate these criteria.Finally, without a specific and precise registration, a researcher can choose inference criteria  in different ways, and on the basis of analytic outcomes. Thus a priori hypotheses, design, data collection, and analysis of the study. Here, the potential exploitations of the many researcher DFs discussed above can or cannot be reported, which renders the reporting of such details crucial . The preferred way to assure reproducibility is to share data and analytic details (computer syntaxes/code) in or alongside the paper . Although both reproducibility and enabling replication are considered matters of reporting here, a preregistration of the study could already specifically and precisely indicate what information is going to shared and in what manner.The exploitation of researcher DFs creates bias, which might lower replicability of earlier results in novel samples . To alloR3: Fail to mention, misrepresent, or misidentify the study preregistration. Studies of preregistrations of randomized clinical trials highlight that preregistrations in the medical literature are often not followed in the final report  could l report . This prR4: Failing to report so-called “failed studies” that were originally deemed relevant to the research question. Note that failed studies are often those that showed no statistically significant results, which is a main reason for authors for not publishing the results . They can falsely present results of data explorations as though they were confirmatory tests of hypotheses that were stipulated in advance  could p-values , for insp-values . Second, advance , which i advance . Both tyWe created a list of 34 researcher DFs, but our list is in no way exhaustive for the many choices that need be made during the different phases of a psychological experiment. Some of the researcher DFs are clearly related to others, but we nonetheless considered it valuable to list them separately according to the phase of the study. One can envision many other ways to create bias in studies, including poorly designed experiments with confounding factors, biased samples, invalid measurements, erroneous analyses, inappropriate scales, data dependencies that inflate significance levels, etc. Moreover, some of the researcher DFs on our list do not apply to other statistical frameworks and our list does not include the specific DF associated with those frameworks . Here we focused on the researcher DFs that are often relevant even for well-designed and rigorously conducted experiments and other types of psychological studies that use NHST to test their hypotheses of interest.could but not necessarily will use these researcher DFs in an opportunistic manner. What matters is that the data could be collected and analyzed in different ways and that the final analyses reported in the research article could have been chosen differently if the results  had come out differently. The issue, then, is not that all researchers try to obtain desirable results by exploiting researcher DFs but rather that the researcher DFs have strong potential to create bias. Such potential for bias is particularly severe for experiments that study subtle effects with relatively small samples. Hence, we need an appropriate way to deal with researcher DFs. One way to assess the relevance of choices is to report all potentially relevant analyses either as traditional sensitivity analyses or as a multiverse analysis  choices in unregistered studies. Presently, we are conducting a study focusing on the quality of a random sample of actual preregistrations on the Open Science Framework in which we use a scoring protocol based on our checklist to assess the degree to which these preregistrations avoid any potential p-hacking. The protocol assesses the preregistration’s specificity, precision, and completeness at the level of each researcher DF; a score of 0 is assigned if the DF is not limited, whereas 1 and 2 are assigned if the description is partly or fully specific and precise, respectively. A score 3 is assigned if it is also exhaustive, i.e., if it excludes other steps. By applying the protocol, authors can also score their own preregistration, enabling them to improve their preregistration, and reviewers of registered reports and registered studies can use the protocol as well. Both authors and reviewers can thus use the protocol to limit potential p-hacking in planned studies.The ideal preregistration of a study provides a We suggest a few avenues for future research. First, while most of the researcher DFs in our list are relevant to other statistical frameworks as well, the list should be adapted for studies planning to use confidence intervals and certain precision of effect size estimates , or BayeJW, MB, CV, MvA conceived of the study idea. JW, MB, CV, MvA, HA, RvA wrote sections of the paper and made revisions. JW, MB, CV, MvA, HA, RvA approved final version of the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Due to damage of the nervous system, patients experience impediments in their daily life: severe fatigue, tremor or impaired hand dexterity, hemiparesis, or hemiplegia. Surface electromyography (sEMG) signal analysis is used to identify motion; however, standardization of electrode placement and classification of sEMG patterns are major challenges. This paper describes a technique used to acquire sEMG signals for five hand motion patterns from six able-bodied subjects using an array of recording and stimulation electrodes placed on the forearm and its effects over functional electrical stimulation (FES) and volitional sEMG combinations, in order to eventually control a sEMG-driven FES neuroprosthesis for upper limb rehabilitation. A two-part protocol was performed. First, personalized templates to place eight sEMG bipolar channels were designed; with these data, a universal template, called forearm electrode set (FELT), was built. Second, volitional and evoked movements were recorded during FES application. 95% classification accuracy was achieved using two sessions per movement. With the FELT, it was possible to perform FES and sEMG recordings simultaneously. Also, it was possible to extract the volitional and evoked sEMG from the raw signal, which is highly important for closed-loop FES control. Neurological disabilities are caused by damage of the nervous system ; this damage results in the loss of capacity to move and manipulate things, especially if fine movements are required . The effBiomedical signals, such as surface electromyography (sEMG), play a significant role in the measurement of the electrical muscle contraction. Plus, its analysis is one of the standard procedures used to identify muscle actions in normal and pathologic conditions. sEMG signals can be used for various applications, which include identifying neuromuscular diseases, controlling signals for orthotic or prosthetic devices , anticipsEMG patterns during movements exhibit a great deal of intersubject, intermuscle, and context-dependent variability. Understanding the sEMG interactions in hand movements is a challenge . SeveralsEMG patterns are used for neuromuscular biofeedback , robot-aSeveral techniques have been employed for addressing human hand movement patterns from sEMG signal. Techniques, such as an adaptive neuro-fuzzy inference system integrated with a real-time learning scheme and time-frequency features, have been used to identify hand motion commands suitable for hand prosthesis control . OrdinalRecognizing sEMG signals with the aim of controlling assisting devices is not only concerned about feature extraction and classification of signals but the acquisition site is also of major importance.M-wave is an electrophysiological response evoked by electrostimulation detected in standard sEMG. It has been studied widely in order to verify the functionality of the stimulation site measurement over the target muscle, which closely relates to muscle fiber recruitment. This electrophysiologically driven approach is expected to lead to the identification of selective electrode configurations of an array for functional movements . HoweverThis paper is related to the acquisition and analysis of sEMG signals for active movements and to obtaining usable hand patterns with simultaneous placing of recording and stimulation electrodes on the forearm, for the eventual control of a neuroprosthesis to aid in motor neurorehabilitation of patients suffering from a stroke aftermath.The presented technique is based on an array of recording and stimulation electrodes on the forearm, used to acquire sEMG signals from five hand motion patterns from six able-bodied subjects, and the effects of this technique over functional electrical stimulation (FES) and volitional sEMG combinations.The first step was to find the best electrode positioning for sEMG recording. This position was found at the belly of the muscle, on the upper part of the forearm, which is formed by the following muscles: brachioradialis, palmaris longus, flexor carpi radialis, flexor carpi ulnaris, extensor carpi radialis longus, and extensor carpi ulnaris. Stimulation is performed at the ends of the same muscles.In order to make sure that the electrodes were placed on the same positions for the different trials for each subject, a personalized template was made. This template was created as follows: for bipolar channel placement, eight spots, where the electrodes would be placed, were allocated and marked on a piece of acetate paper. Then, the unique physical characteristics of the individual and the positions of five stimulation bipolar electrodes were marked on the same paper. Once the places were allocated and the personalized template was designed, sEMG acquisition was carried out.Six able-bodied subjects were included for the acquisition of sEMG signals, their age ranged from 21 to 33 years old, three males and three females. The subject was sitting in a comfortable position with his/her right arm supinated and leaning on the table. The subject was asked to perform an isometric contraction for five movements: hand open, power grasp, fine pinch, pronation, and supination. While contraction was active, the forearm muscles that participate in the motion were palpated and located.The subject's skin was cleaned using an alcohol swab in order to reduce impedance and have a better coupling for the skin-electrode interface. Afterwards, the template was placed on the subject's forearm and marked; these were the spots where the electrodes should be placed. Electrodes were connected to an open-source platform called OpenViBE. This acquired the sEMG signal through a compatible open hardware acquisition device (OpenBCI) which was connected to a designer space, where an algorithm was designed for trial tasks .OpenViBE configuration was 24 for gain, 250 Hz for sampling rate, and eight channels for sEMG. The subject was asked to perform the movement shown in a cue image while it was on the screen. The task started with a rest of 10 seconds, and it continued with a ten-second isometric contraction of hand open, power grasp, fine pinch, pronation, or supination, depending on the trial. Cue images were shown alternatively until the subject completed ten repetitions of the motion. A session was considered completed when two movement tasks were finished . All subFrom all the personalized positions, which were based on common regions found for each subject, a universal template that kept the array for recording and stimulation electrodes was designed. It was called forearm electrode set (FELT).Each sEMG record was imported into MATLAB® environment for processing. From the .csv files, information of eight channels and a time vector was extracted. As seen in After acquisition, data were conditioned using discrete wavelet transforms (DWT). An eight-level decomposition using mother wavelet Daubechies-4 was applied, and the reconstructed signal was subtracted in order to eliminate baseline drift ; this waThen, the DWT was applied, again, to an eight-level decomposition, but this time a mother wavelet Haar was used in order to find the envelope of the signal, which was obtained from its reconstruction. This envelope was used to find the parts of the sEMG signal that represented a movement, in this case open hand or power grasp; then it was converted to a logic signal .In order to find the characteristic features of the five target movements, the following parameters were calculated: mean absolute value—MAV , wave leFrom these parameters, a subset was selected for classification based on separability between movements and classification accuracy. The new set of parameters were used for classification.For the classification of sEMG signals, feature and window length analysis were performed for the eight channels. The sEMG envelope signal was used for selection of active patterns at the processing stage. From this ~10 s of sEMG activity, windows of 20 ms, 50 ms, 100 ms, 300 ms, and 500 ms and 1 s and 3 s length, with a 25% overlap, were used to calculate the seven features described in , (5), 66, and 77.For each subject and each analysis window value, the seven features were extracted for the eight channels; for hand open task and power grasp task.The resulting 56 features obtained from each window were considered as a single trial for each movement.All available trials from the first session (one task per movement) of all subjects were concatenated movement-wise and randomized afterwards.Label classes for each trial were set as 1 for hand open and 2 for power grasp.For each window length value, the analysis was performed ten times.All trials were divided in 70% for a training set and 30% for a testing set.A LDA classifier was trained with the training set.The trials on the testing set were classified with the LDA classifier, and its classification accuracy was calculated as the ratio of correctly classified trials versus the total number of trials.A linear discriminant analysis (LDA) was executed for sets of two movements following the process described ahead, in this case for hand open and power grasp:All subjects' data from the first session  that obtained a classification accuracy higher than 90% were chosen as the subset of features used to train the final LDA classifier. Data from the second session, which consisted of hand open and power grasp for each subject, was processed in the same way and was used to test the LDA classifier.For the trials of sEMG signal acquisition during FES application, the acquisition was performed using the OpenViBE platform and OpenBCI device with the same configuration mentioned above. For FES application, a RehaStim 2 electrical stimulator  was used and programmed in an interface developed in Simulink®/MATLAB Environment.Three able-bodied subjects out of the six that performed the previous trials without FES, age range from 22 to 34 years old, two males and one female, were included for sEMG acquisition. Their skin was cleaned with alcohol and the FELT was placed accordingly. For each target motion, there was a pair of self-adhesive stimulation electrodes  placed within the FELT, positioned as presented in Five isometric contractions of the selected movement, each lasting one second with three seconds rest (except pronation and supination: 1.8 active to 2.2 second rest)Five FES stimulations of the selected movement, each lasting one second with three seconds restFive isometric contractions during FES stimulations of the selected movement, each lasting one second with three seconds restThe subject was asked to perform an isometric contraction for five movements: hand open, power grasp, fine pinch, pronation, and supination, but this time the trial consisted of three parts :Five isThe algorithm in The new records were analyzed for processing the sEMG data because these signals included evoked and/or volitional sEMG as well as the FES stimulus. In order to extract the sEMG evoked/volitional sEMG from the stimulus artifact, a comb-type filter was applied to eliminate the 30 or 50 Hz signal of the stimulus, by means of a Butterworth filter, order two, with a 29 to 31 Hz or 49 to 51 Hz bandwidths, accordingly. All data processing is designed and performed in MATLAB environment. The parameters calculated for these signals are MAV  to compaA personalized template was designed for each subject. These templates were used to successfully locate muscle sites and place electrodes for the second trial, with the advantage of a tenfold reduction in location time, approximately. Then, the FELT was designed as a universal array from all the individual templates.The main purpose of the FELT was to simplify recording and stimulation electrode placing, for a future FES-based neuroprosthesis clinical application for stroke aftermath rehabilitation at upper limb and hand. There are not standardized designs for sEMG recording and FES application. The sEMG signals acquired for open hand and power grasp were used to evaluate the right position of the recording electrodes at the FELT.One of the objectives of this work was to allocate all electrodes keeping the balance between having available positions to acquire eight sEMG channels and enough place for five bipolar stimulation channels. It is important to mention that since the forearm is a small area, it was difficult to find the right allocation for all the electrodes (stimulation electrodes are 5×5 cm and recording electrodes are 1 cm in diameter) and still have useful signals that could be processed and classified.Due to this critical disposition, the electrode locations from the personalized templates were assessed through the sEMG signals obtained by means of signal processing and classification of movements.A baseline drift-free signal was obtained from the raw sEMG signal during the preprocessing stage . All sesThe preprocessing analysis and processing method showed that no matter the 60 Hz noise and drifting baseline, the signal could be isolated for feature extraction and classification. It is important to mention that if the acquisition signal was less contaminated, this process could be faster and closer to real time for control applications, which emphasizes the need to design and build a specialized acquisition stage in order to start with the best version of a raw sEMG signal .From the analysis of the combinations of features, channel, and window length for all subjects, it was found that only 5 features  yield enough information for classification, above 90% accuracy . In FiguFrom this analysis, using 9 out of 10 repetitions of each movement per session and considering session 1 for training and session 2 for testing, it was found that MAV, WL, and SD features and a 0.50 seconds' window length were the best combinations for the classifier to perform with only 4 channels  at a 95.83% classification accuracy. The results from all combinations can be seen in This study and analysis was performed to minimize inputs for the classifier, with the aim of getting a closer approach to a real-time application. This analysis is a classification method for multisubjects, used to generate a sEMG-driven control for a FES neuroprosthesis application.An example of the sEMG signals obtained for subject 1 using FELT, for channels 1 and 2, is shown in The RMS and MAV values for each repetition were calculated; The design of a personalized template presented in this paper replicates the sEMG signal between sessions. Also, the forearm electrode set (FELT) resulted from the need to find the correct place for eight sEMG bipolar channels and five bipolar stimulation channels  in the forearm, which is a small area for so many electrodes .Signal processing yielded a very clean signal that preserved sEMG components by using DWT and allowed to differentiate between movements through feature extraction and classification.We found an optimal combination between window length and number of channels and features, at 0.5 seconds, with four channels and three features , which allowed a more efficient classification in terms of time and channels.The stimulation parameters were selected in order to generate a complete movement without subject discomfort; however, range of movement is yet to be evaluated. As for signal processing, knowing the stimulus frequency beforehand allows the use of a filtering technique feasible for offline and online application. From Using the FELT, it was possible to perform sEMG recording and FES simultaneously. Moreover, it was possible to extract the volitional and evoked sEMG from the raw signal, which was accomplished without blanking the signal allowing better control techniques to be implemented. This is highly important for closed-loop FES control.In the evoked/volitional sEMG and FES trials, the FES stimulus was successfully eliminated from the recorded signal leaving a usable sEMG signal for FES control and other applications as orthosis, prosthetics, neuroprosthesis, and other rehabilitation and assistive devices.