Distal radius fractures are a common type of fracture. For patients treated with closed reduction with splinting, a period of rehabilitation is still required after the removal of the splint. However, there is a general lack of attention and low compliance to rehabilitation training during this period, so it is necessary to build a rehabilitation training monitoring system to improve the efficiency of patients’ rehabilitation.A wearable rehabilitation training wristband was proposed, which could be used in the patient’s daily rehabilitation training scenario and could recognize four common wrist rehabilitation actions in real-time by using three thin film pressure sensors to detect the pressure change curve at three points on the wrist. An algorithmic framework for classifying rehabilitation training actions was proposed. In our framework, an action pre-detection strategy was designed to exclude false detections caused by switching initial gestures during rehabilitation training and wait for the arrival of the complete signal. To classify the action signals into four categories, firstly an autoencoder was used to downscale the original signal. Six SVMs were then used for evaluation and voting, and the final action with the highest number of votes would be used as the prediction result.Experimental results showed that the proposed algorithmic framework achieved an average recognition accuracy of 89.62%, an average recognition recall of 88.93%, and an f1 score of 89.27% on the four rehabilitation training actions.The developed device has the advantages of being small size and easy to wear, which can quickly and accurately identify and classify four common rehabilitation training actions. It can easily be combined with peripheral devices and technologies  to build different rehabilitation training scenarios, making it worthwhile to use and promote in clinical settings. FracturRehabilitation training assistance monitoring system for the patient’s terminal equipment puts forward the requirements of physiological signal acquisition, rehabilitation training action recognition and evaluation, of which rehabilitation training action recognition is the main research direction, because this technology is the key to build a bridge of joint supervision between doctor and patient for distal radius fracture, and a large number of researches have existed for this task. The means of rehabilitation training action recognition fall into two broad categories, namely computer vision (CV) based and sensor based approaches . The comSensor-based rehabilitation training devices have unique advantages due to their ability to detect multimodal physiological parameters directly or indirectly. These systems place multiple types of sensors on different carriers, and the data is collected and analyzed by a central processor . Common However, the main applications of these studies on hand rehabilitation assistance systems are for stroke and Parkinson’s patients, and these application scenarios do not limit the pressure at the radius. In addition to proper rehabilitation, patients with distal radius fractures should also ensure that the pressure on the affected area of the radius is within the appropriate range, otherwise excessive splint pressure will likely bring about various syndromes as a result of vascular compression of the affected area, while too little pressure on the splint may result in secondary dislocation of the fracture. Therefore, rehabilitation equipment for patients with distal radius fractures should have the ability to monitor skin pressure on the affected area in addition to supervised rehabilitation. At the same time, the variety and number of sensors deployed in rehabilitation training gloves  inevitaWe proposed a wearable rehabilitation training wristband for distal radius fractures, which provided rehabilitation training actions recognition and detection functions, and opened up a Bluetooth interface that allowed simple connection to computers, cell phones, and other upper computers and the development of a variety of rehabilitation training software.A rehabilitation training action classification algorithm based on an autoencoder and SVM classifier was designed, which could run on a microcontroller and classified action signals quickly and accurately.An action signal pre-detection strategy was proposed to determine whether the window signal was a complete action signal, which reduced the false detection rate of the algorithm.2.2.1.2.1.1.Thin-film pressure sensors are used to detect three channels of pressure on the palmar, radial and dorsal sides of the wrist. A three-channel thin-film pressure sensor designed by our own structure is used as the detection element of the wristband, and presents a T-shaped structure. On the crossbeam of the T, three pressure-sensitive zones are distributed from left to right for the above-mentioned palmar, radial, and dorsal pressure detection. On the arm of the T, there are four copper wires leading out and connected to the control box through the MicroUSB interface, one of which is connected to one of the pins of the three pressure-sensitive zones to form a common terminal. The T-shaped structure design avoids the problem of cable stacking when wearing the wristband. The design structure and object diagram of the thin film pressure sensor are shown in 2.1.2.The rehabilitation wristband is composed of an inner bandage core and an outer magic stick layer. The inner bandage core consists of two layers of medical bandages and film sensors pressed together, with the upper layer of bandages for the elastic self-adhesive bandages, longer length, for wearing around the fixed, and the lower layer of bandages for inelastic bandages. Both sides of the thin-film sensor are in contact with the upper and lower bandages by circular silicone pads with a thickness of 1 mm. The structural schematic of the inner bandage core is shown in 2.1.3.The control box circuit is composed of four parts: a power supply circuit, STM32 microcontroller minimum system, pressure acquisition system, and BLE Bluetooth transmission circuit. The power supply circuit is used to charge the lithium battery and to regulate the input voltage of the lithium battery to the voltage required by other chips. It uses the PW5410A charge pump chip to regulate the input voltage of the lithium battery to 5 V, which is then stepped down to 3.3 V by the PW6566 LDO chip. 5 V is supplied to the operational amplifier in the system, and 3.3 V is supplied to the STM32 microcontroller, BLE Bluetooth transceiver module, and other chips. The STM32 microcontroller minimal system is used to detect the analog signal output from the pressure acquisition system, detect the transceiver signal of the Bluetooth module and run the classification algorithm of the rehabilitation action signal, which uses its own ADC peripheral to convert the analog voltage to digital, and uses the BLE Bluetooth module to send the detected action signal or receive the control signal from the upper computer. The pressure acquisition system consists of three Wheatstone bridges cascaded with differential amplification circuits, each of which is used to detect the pressure sensor information of one channel, and the output voltage of the pressure acquisition system is 0–3.3 V, which is received by the STM32 microcontroller. The BLE Bluetooth transmission module serves as a wireless communication medium between the control box and the upper computer, automatically converting serial signals and Bluetooth RF signals to each other, which simplifies the system development difficulty. The circuit system structure and module circuits are shown in 2.1.4.Although it is now clinically recognized that appropriate functional exercises have a positive effect on the rehabilitation of distal radius fractures, there is no uniform standard for the details of the actions of rehabilitation training . Often h2.2.2.2.1.The thin-film pressure sensors we used are resistance-strain sensors, whose resistance decreases gradually as the applied pressure increases. After conversion by the sensor data acquisition circuit, the change in applied pressure will be reflected as a change in the output analog voltage of the circuit, which is converted into a digital quantity by the analog-to-digital conversion module of the microcontroller . Since it is not possible to calculate the applied pressure directly from the AD value, we conducted pressure calibration experiments of the sensor with the aim of finding the mapping between the pressure applied to the sensor and the corresponding output AD value.We first placed the pressure sensor on the pressure calibration platform, which consisted of a push-pull force gauge with a 3 kg range and 1 g resolution and a hand-cranked fixture. The push-pull gauge was fixed on a stationary frame and different pressures were applied to the pressure sensors by turning the rocker, and the AD values of the corresponding channels of the pressure sensor and the pressure measurements of the push-pull gauge were simultaneously collected by our computer. A total of 10 rounds of raw data were collected, with each round collecting 300 sets of data at a frequency of 3 Hz, in which the applied pressure was gradually increased to 500 gf during the first five rounds of collection, and gradually decreased to 30 gf during the last five rounds of collection (not reduced to 0 because the push-pull gauge had a 30 gf pressure dead zone). The acquisition results are shown in 2.2.2.i = 1, 2, 3, j = 1, 2, 3,…, 30, and We use our own QT-based software platform for rehabilitation action acquisition. Five subjects were recruited for training set data collection, with two rounds per subject, and 50 reps of each of the four rehabilitation training actions were collected in turn. The type of raw data collected is the AD value. The sampling frequency of the software platform is 15 Hz, and since the rehabilitation training action is basically completed within 2 s, the number of sample collections is set to 30 times for each group. Thus the data structure of each action sample is The initial state pressure varied slightly from subject to subject because the tightness of the rehabilitation wristband was not exactly the same each time the subject was strapped in. We bind an initial reference AD value i = 1, 2, 3 and j = 1, 2, 3,…, 30, which maintains the same data structure as the action sample and is calculated by the following equationSubsequently, each action sample data collected by the subject will be transformed into a normalized value As we can see, 2.2.3.Since the input data is a 90-dimensional 2.2.4.The classification algorithm will be deployed to the STM32 microcontroller to run after the training is completed. According to the input data requirements of the classification algorithm, after the user finishes installing the wristband and prepares the posture for rehabilitation training, the user first keeps the hand relaxed and the upper computer sends initialization instructions to the microcontroller, which continuously acquires 30 sets of three-channel AD values at a frequency of 15 Hz and automatically calculates three average AD values as the initial reference AD value 3.3.1.We carried out two rounds of pressure calibration test experiments, each round of the first gradually increasing pressure on the sensor to reach the full range and then gradually reduce the pressure, the computer to store the process of pressure prediction of the microcontroller and the real readings of the push-pull gauge. The pressure error is calculated by 3.2.In order to find the most suitable autoencoder structure for accurate feature extraction of the input data, we tested the effect of different numbers of neurons in hidden layers and output neurons on the validation error of the autoencoder. k-fold cross-validation, as an efficient method to test the performance analysis of networks with different hyperparameters, randomly disturbs the sample set and divides it equally into k subsets. In k times of loops, a different subset is selected as the validation set and the remaining subsets are used as the training set, and the error of the network completed by this loop training on the validation set is evaluated. After k loops, the average of the k test errors is used as a measure of the generalization ability of the network at the current hyperparameter setting. We choose a 10-fold cross-validation approach and let the number of neurons in the hidden layer increase from 10 to 60 in step of 10 and the number of neurons in the output layer increase from 5 to 40 in step of 5. The test results for all combinations are shown in 3.3.To further determine the appropriate size of the hidden layer and output layer of the autoencoder, we tested the effect of the number of neurons in the hidden layer and output layer on the SVM classification results for the above combination. In this test, we also use 10-fold cross-validation, and for each autoencoder structure, we encode all the original data using the autoencoder after training, then train 6 SVM classifiers using the encoded data, which do not use the kernel trick and have a C-value of 1. Finally, the final prediction of the algorithm is determined using the voting results of all SVMs on the encoded data. We use the prediction error rate as a measure of the algorithm’s classification performance, which is expressed as the proportion of samples with incorrect predictions for all samples. The test results are shown in The results show that the number of hidden layer neurons shows a negative correlation with the recognition error rate. When the hidden layer is 30 neurons or more, the recognition error rate decreases and then increases with the increase of output layer size, and as the output layer size continues to increase, the error rate tends to saturate. The algorithm performs better with a larger hidden layer and a smaller output layer. As can be seen, the scale of the hidden layer plays a key role in the final performance of the algorithm. At the same time, as we expected, too small or too large an output layer leads to a reduced degree of linear separability after encoding the raw data, which is not entirely determined by the encoding performance of the autoencoder; for example, the autoencoder exhibits a high validation error when the number of neurons in the hidden layer and output layer is 50 and 15, respectively, but performs well in the final classification, and the opposite is true at their number of 60 and 25, respectively, although overall it remains that the lower encoding error leads to better classification performance.3.4.Considering the computing power of the microcontroller and the generalization capability of the model, we choose a final autoencoder structure with a hidden layer size of 40, an output layer size of 10, the Tanh function as the hidden layer activation function, and no activation function for the output layer. With this parameter setting, we randomly divide the original data into training and test sets according to 8:2, use Adam as the optimizer with each mini-batch size of 200, and select MSE as the loss function. The variation of the training set error and the test set error of the autoencoder with the training batch is shown in 3.5.After the autoencoder training is completed, we encode all the original data. According to our strategy, we are going to use six SVMs to vote on the categories of the encoded samples. Each SVM classifies two of the four classes of actions, such that the six classifiers are denoted as 3.6.We deployed the entire classification algorithm trained on a microcontroller and tested it in practice. In addition to the five persons involved in the training set collection, we called five additional subjects to participate in the actual test, with each subject performing one round of testing. After the subject has tied the wristband and placed the elbow on the table with the arm upright and keeping the palm facing inward, the microcontroller first asks the user to stay relaxed and follow the instructions from the phone for the data acquisition of resting state, followed by the average calculation of the three-channel AD values. Thereafter, the microcontroller determines whether a rehabilitation action is coming according to the above action pre-detection strategy, and if so, classifies the action category, and if it is recognized as a rehabilitation action, sends a response message to the phone. Each subject performed 100 sets of each of the four types of rehabilitation training, with a supervisor counting manually on the side, and finally counting the number of differences between the rehabilitation training actions detected by the microcontroller and the actual actions performed. The confusion matrix was plotted based on the experimental results of each subject, and finally, the accuracy and recall of each rehabilitation training action recognition for each subject were counted.The confusion matrix of 10 subjects is shown in For the rehabilitation training action X, TP denotes the number of times the network correctly recognized X, FP denotes the number of times other actions were recognized as X, and FN denotes the number of times X was recognized as other actions or not recognized as any one action. The results show that the test results of the subjects who participated in the training set acquisition were generally good, indicating the effectiveness of the algorithm in classifying the four actions. Subjects who did not participate in the training set acquisition had slightly worse test results than the former but also showed sufficiently high generalization ability, indicating that the algorithm is generalized for feature extraction of the four actions.The average precision and recall of the participants who participated in the training set acquisition and those who did not participate in the acquisition were counted separately on the four actions, and the results are shown in 4.With the development of computers and the Internet, the medical system is gradually showing the trend of intelligence and digitalization. With the support of the Internet and smart devices, rehabilitation treatment is gradually evolving from the previous face-to-face communication between doctors and patients to a new mode of remote monitoring and management. For example, mHealth , definedOur developed wristband for rehabilitation training of distal radius fracture directly detects the force on the palmar side, radial side, and dorsal side of the affected limb by means of a three-channel thin film pressure sensor with tying a rigid magic stick band around the outside. After the sensor is connected to the circuit, the rehabilitation training movement detection of the distal radius fracture recovery period can be performed. The measured data showed that the system achieved an f1 score of 89.27% for the recognition of the four rehabilitation actions. The demands placed on splint tightness in patients with distal radius fractures necessitated the use of a pressure sensor to quantitatively assess splint tightness. Pressure sensors can be categorized into piezoresistive, capacitive, optical fiber, resonant, and piezoelectric types based on different principles , and allIn addition, the rehabilitation wristband can be used independently in a variety of splinting  immobilization situations in the early stages of fracture patients. Its pressure sensor can accurately assess the degree of splint tightness by direct contact with the affected limb, which can largely reduce the dependence of splint fixation on physician experience. This gives the wristband the flexibility of application as it can alert users to the loosening of the splint during fixation The original contributions presented in the study are included in the article/XS and GZ designed and planned the study concept. QZ and ZX completed the system construction and algorithm and design drafted the manuscript. XC provided medical guidance. All authors jointly revised the content of the study and agreed to submit the manuscript.This work was supported by Science and Technology Program of Suzhou, China (No. SYG202019) and Science and Technology Program of Jiangsu Province, China (No. BE2021662).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Objectives: The goal of this project is to explore the views, expectations and preferences of patients with an unruptured intracranial aneurysm regarding the use of AR in patient education.Methods: To gain an in-depth understanding of the patients’ perspective, a face-to-face interview study was conducted using an interview protocol with a predefined topic list. All interviews were audio-recorded and transcribed verbatim afterwards. Transcripts were analyzed using thematic content analyses. Coding was performed using Atlas.ti software.Results: Seventeen interviews were conducted. The views, expectations and preferences of patients regarding patient education with AR could be subdivided into 15 categories, which could be grouped into 4 general themes: 1) experiences with current patient education, 2) expectations of AR in patient education, 3) opportunities and limitations of AR, and 4) out-of-hospital use of an AR application. Patients’ expectations were predominantly positive regarding improving patients’ understanding of their medical situation and doctor-patient communication.Discusssion: This study suggests that patients with unruptured intracranial aneurysms are open to receive patient education regarding their disease with AR. Patients expect that AR models can help patients with intra-cranial aneurysms better understand their disease, treatment options and risks. Additionally, patients expect AR could improve doctor-patient communication. An intracranial aneurysm is a dilation in the wall of an artery of the brain. This increases the chances of the blood vessel rupturing, which can cause severe bleeding. However, aneurysm treatment is associated with possible complications. Therefore, the risk of spontaneous rupture has to be balanced against the risks of procedural complications. Clinical decision making is therefore complicated and for patients with unruptured, often asymptomatic, intracranial aneurysms, the process of information transfer needs to be in-depth and detailed. Physicians have the responsibility to inform patients about the aneurysm itself, the different treatment options  and the associated risks. This process of clinical decision making can be challenging. Survey studies reported that there was low agreement between patients and neurosurgeons regarding the “best” treatment option for each individual patient . FurtherAR is a form of 3D technology which overlays a computer-generated image on a user’s view of the real world, providing additional data and context . AlthougHowever, before implementing AR in the education of unruptured intracranial aneurysm patients, it is important to ask these patients if and how they would like to see AR used in the clinic. Patients’ views on the current patient education process and their expectancies of the usage of AR, can provide valuable insights into effective AR implementation. Previous work has shown that including patients through qualitative research can result in identifying facilitators and barriers from the patient perspective, and positive and negative effects of new educational tool usage .This qualitative study aimed to provide more insight in the expectations and wishes of patients suffering from unruptured intracranial aneurysms on AR in patient education. These insights could provide indications for AR in patient education, and thus form a basis for developing a suitable AR application and for further research.To obtain an in-depth understanding of the subject and to explore patients’ views, expectations and preferences, a qualitative research design was used. Ethical approval was not required for this type of study under Dutch law, and an exemption was obtained by the local Medical Ethics Committee “CMO Regio Arnhem-Nijmegen” (registration number: 2020-7206). Written informed consent was obtained from all participants. Data were collected using semi structured interviews to obtain a nuanced understanding of the patients’ expectations and wishes concerning AR in patient education.Based on a literature study, an interview protocol was constructed based on a topic list. In collaboration with a radiologist and neurosurgeons and 3D technicians, the topic list was finetuned. The interview protocol provided structure for the interview to ensure that all necessary topics were covered. Interviews were conducted from May 2021 until December 2021.The interviews were conducted by two trained researchers (JU and/or D.H.). Each participant was interviewed once, at a time and place suitable for the patient. The setting of this interview was informal and was conducted as a conversation. Based on patients’ preferences, close relatives attended the interview and were allowed to assist patients during the interviews. The researchers made explicit that they had no involvement in the medical care of the participants.Interviews were conducted face-tot-face or by use of video call programs due to the COVID-19 pandemic and its subsequent restrictions . All interviews were audio-recorded and transcribed verbatim after conducting the interview. Additional interviews were conducted until data saturation was suspected , after which two additional interviews were held to confirm this.Open‐ended questions were used as starting points for the interview. The first part of the interview consisted of three topics: 1) general/demographics, 2) experiences with current patient education, and 3) context (friends and family). Then, to clearly illustrate augmented reality technology to the participants, two videos were shown during the interviews. These videos can be viewed in Patients were eligible for inclusion if they had a diagnosis for an intracranial aneurysm or they were already treated for their intracranial aneurysm. Patients were identified through the outpatient clinic of the Radboud university medical center, Nijmegen, Netherlands, or the weekly neurovascular interdisciplinary meeting of the first 3 months of 2021 of this hospital. Patients were first approached by a neurosurgeon or nurse practitioner. If patients were interested to participate in this project, their contact details were passed on to the researchers who then provided more information on the study. To seek in‐depth information from a wide range of patients, purposive sampling was conducted based on gender, age and educational background. Only patients with a sufficient understanding of the Dutch language were included in the study.http://atlasti.com; ATLAS.ti Scientific Software Development GmbH, Berlin, Germany). The first interviews were independently coded by two authors (JU and DH). The assigned codes were compared and discussed until consensus was reached on the codes for the codebook. Analysis took place via an inductive iterative process using the constant comparative method. This means that data analysis started after the first interview was completed. As the study continued, codes derived from the previous interview(s) were used as a starting point for coding the next interview, adding additional codes where and whenever needed.The data from these interviews were analysed using thematic content analysis. This was done using Atlas. ti software version 22 Windows  experiences with current patient education, 2) expectations of AR in patient education, 3) opportunities and limitations of AR, and 4) out of hospital use of an AR application. Details are summerized in This theme describes experiences patients have with current patient education, which can provide valuable insights into effective AR implementation.Participants mentioned that creating clarity and providing assurance was the most important goal of patient education. They indicated that this could be achieved by providing complete, though concise and understandable information. Additionally, it was mentioned that it was very important for patients to be able to trust their physician and that the education is approached positively, i.e., not just focusing on the risks. This is important because emphasizing the risks of an intracranial aneurysm could cause patients to feel overly anxious.When discussing which information, they valued the most, interviewees reported that detailed information about aneurysm location, size and origin was important to them. The participants described they needed this information to understand the explanation of different treatment options, the advantages and disadvantages, the associated risks and the possible consequences of rupture or treatment failure.It was expressed by participants that they had forgotten a great amount of information that was given during the first consultation. The reasons that people gave for this memory loss were pre-existent memory problems, being nervous and/or the excessive amount of information given during their first visit. Interviewees told us that they therefore learned most about their aneurysm by reading information provided by their physician or information they found online.Participants stated that they found it difficult to formulate the right questions during the first consultation due to shock and the amount of information provided at this first consultation. Therefore, most questions arose after their hospital visit.Two tools were described by the interviewees which were used to help them visualize the aneurysm: radiological data and a sketch made by the physician. A mentioned disadvantage of the radiological data was that participants found it too difficult to understand. They mentioned that they needed a lot of explanation from their physician to fully comprehend what they saw when looking at scans. One patient even stated that imaging was interesting for physicians, but not for patients.“A neurologist explained to me that there were at least two aneurysms in there and she also showed them on a scan but well, all you see are a few gray spots. You can't do much with that. (P14)”Patients expressed that they were more satisfied with the sketches made by the physician. The reasons patients gave for this preference was that these sketches gave them more insight in their diagnosis and possibilities for treatment in a simple way. Additionally, the physician showing a stent when explaining treatment options was well appreciated by patients.“They also showed it on the MRI or CT, but that is less clear. It is more difficult to understand. With a sketch, it was just a blood vessel with a ball on top and then he drew some coils in it. (P4)”The biggest benefit patients expected from AR was that it could increase patients’ understanding of the location and size of their aneurysm. In addition, patients believed AR could be a valuable addition to help explain treatment options and the associated risks. They expected that, especially the attractive visualization used in AR would help patients better understand the information given by their physician. This might also make the information easier to remember. Moreover, patients expected that increased understanding could also lead to patients making more well-educated decisions on their treatment. Participants believed this visualization and the increased understanding that could come with it would make it easier to live at ease with their intracranial aneurysm.“Then I can see what they’re really talking about. Because I try to understand what they are telling me, but if you really just have a clear image, it's just a lot easier. Then it becomes easier to remember and you can also explain it to others more easily. (P9)”It was also expressed that seeing an aneurysm in AR would give more insight in possible complaints due to their aneurysm.‘Very clear, nice to see. You understand it a little better. I suppose that if I could see this of my own head, then I would know precisely where my aneurysm is located. So, when I feel pain elsewhere, I don’t have to be afraid. But then, if I feel pain on the location of the aneurysm, I’d think, oh, could there be something wrong there? (P10)”With regard to AR in the consultation room, views were that the use of AR would be suitable in a consultation with their physician. Patients differed in their view whether using AR would lead to discussing extra topics during a consultation. One view was that the use of AR would not change what is being discussed in the consultation room. The contrasting view was that, because patients can see exactly what the physician is talking about, AR could lead to patients asking more questions.Before viewing the video of the AR aneurysm model, patients expected that viewing their aneurysm in AR could be emotionally confronting and even scary. However, after watching the AR video, none of the participants expressed feelings of this kind. Patients did not find the AR model scary because it was clear and informative and because it did not look too ‘real’. Having a good doctor-patient relationship was expected to make it less scary to watch the AR model, emphasizing the guiding role of the physician.Generally, patients thought the AR aneurysm model used in this study was clear and that it gave insight in the anatomy and the location of the aneurysm. Participants were happy with an innovation like this in patient education and mentioned they would like to see a personalized AR model. The adaptability of AR was seen as an advantage. Unlike with a sketch, with AR you can easily remove and add different layers of the model, which provides patients with a more detailed explanation. However, several points for improvement and wishes for AR emerged during the interviews. Concerning the current model, patients stated that the aneurysm in the model should be presented larger or more striking. Thereby, it was stated that more details should be incorporated in the AR model, such as cranial nerves, white matter and the thickness of blood vessels. Additionally, it was suggested that a brain should be incorporated in the AR model to make it clearer where the blood vessels are in relation to the brain. Also indicating the front and back of the model could be helpful.When receiving information using AR, patients stated that the model should be used to explain potential causes of the aneurysm and causes of complaints provoked by their aneurysm or perceived treatment. One patient stated that they would like their physician to use AR every consult to update them on the state of their aneurysm.Participants stated that they would like to see their treatment options depicted in AR. Some patients stated they would like AR to be used to create more insight in treatment risks, whereas others disclosed that treatment risks should not be visualized in AR because it would be too confronting.Concerns were expressed regarding the accuracy of AR. Participants were afraid details would get lost when transferring data from a scan to an AR model or that the model will show a distorted reality.Another problem that was raised was that patients need time to get used to the new technology, which could be difficult at an older age. Proper guidance when using AR and a physician well-trained in using the device were therefore considered necessary by patients. Additionally, patients specifically stated that when using AR, medical education provided by a specialist will always stay necessary, preferably by a physician.“My physician could explain it in great detail with a drawing, or at least well enough, and that gave a soothing feeling. You know that the physician understands everything about it and that he will fix it. That feeling should stay if you’re going to do it that way. (P4)”Views on preferred AR device were divided. One view was that using a phone to view AR would make is easy to watch AR at home and prevent having to purchase a new device. Several patients were inconclusive about which AR device they would prefer, because they did not have any experience in using AR. When discussing the potential disadvantages of AR in patient education, patients stated that although they would like education using AR, they were afraid it would not work in practice, because it would consume too much time during the consultation.Several perspectives on patients’ need for AR arose during the interviews. Patients told us they expected that it depends on the patient’s coping strategy whether someone wants education with AR or not. For example, some patients just do not want to know everything about their condition. It was suspected that AR might be too confronting when a patient has a more severe diagnosis or needs to undergo a treatment with more risks. It was specifically expressed that therefore you should always ask the patient whether they would like to see an AR model. Additionally, it was stated that AR would be most favorable for patients with a low understanding of their condition.The necessity of AR in patient education was questioned during the interviews. Participants reported that AR gave them more insight in their condition, but that it was not necessary for patient education. Additionally, it was stated that AR would be more beneficial for conditions that are more difficult to understand than having an aneurysm.Participants advised not to provide AR when a patient first hears about having an aneurysm, but at a later stage. This way, patients would have time to let the news sink in before further patient education takes place with AR. However, not all patients agreed: one patient stated that he would not mind receiving AR patient education in the acute moment.Several patients mentioned that they would like to be able to watch an AR model of their aneurysm at home, for example, by using an AR-application on a phone or tablet. This would allow them to rewatch information in a comfortable environment with relatives. One patient expressed that they wanted to gather as much information at home as possible. A suggestion that was made by participants was that an AR recording at home should include the physician’s explanation that they received at their hospital visit.AR could also be used for relatives. A reason patients mentioned to do this was that using AR could make talking about aneurysms easier for patients. Another reason was that it would be beneficial that one would not have to explain everything repeatedly, because they could instead show their relatives using AR. Reasons mentioned against using AR for relatives were that AR could make relatives uncomfortable or that relatives would not be interested in AR.This study explored the views, expectations and preferences with regard to the use of AR in educating patients about their intracranial aneurysms. In general, participants expressed that AR could be useful in this setting, particularly with regard to improving patients’ understanding of their medical situation. Also, AR was suggested to improve the communication between doctor and patient. It was preferred to use AR later in the educational process  and most interviewees saw opportunities regarding the use of AR at home and in explaining their disease to their relatives. Nevertheless, interviewees disclosed that AR could be too time-consuming during consultation and that a physician trained in using AR is necessary. Also, AR was believed to be emotionally confronting, although none of the participants experienced this after viewing the here described AR system.The few previous studies that have been carried out on the use of AR in patient education, rarely involved patients in the process of designing and implementing AR applications . For a rThe previous studies comprised patients suffering from a diverse spectrum of chronic diseases . These studies showed benefits of AR such as (perceived) knowledge gain and increased patient satisfaction . These bAdditionally, inter-individual differences in visuospatial abilities significantly impacted student performance when working with AR .Furthermore, it was noted that patient-specific factors, such as conditions like strabismus that affect three-dimensional vision, could affect the choice of the most suitable AR device for patient education . NeverthPatients in this study emphasized the ongoing necessity of medical education provided by a specialist, preferably a physician, when augmented reality (AR) is utilized. This finding corresponds with the existing literature on the use of visualization tools for patient education. Previous research on alternative methods such as videotaped instructions or computer-aided information systems has produced mixed results. However, existing evidence shows that providing a combination of spoken and written or visual information is best .Furthermore, patients expressed their preference to utilize AR later in the educational process as this would give patients the time to process their diagnosis before further patient education takes place. We know evidence exists, indicating that attentional narrowing occurs when events are perceived as stressful or emotional . In suchSimilar to the expectations of patients in our study that AR could help in communicating with relatives, it was found that an AR intervention helped parents to talk about a planned procedure with their children and that it significantly decreased anxiety in parents whose children were undergoing invasive procedures . In anotFinally, patients in our study expressed their worries about needing time to get used to the new technology and that this could be difficult at an older age. Proper guidance when using AR and a physician well-trained in using the device were considered necessary. When looking at the existing literature however, most studies reported a high usability and likability of the AR applications used . These sThis study is the first to present the expectations and wishes concerning the use of AR for patient education among patients with unruptured intracranial aneurysms. It has been shown in other aspects of medical treatment that the patient’s expectations and wishes can be different from those of physicians . The ideTo seek in‐depth information from a wide range of patients purposive sampling was conducted in this study. As a result, the participant group comprised patients with varying genders, ages, and educational backgrounds. It is worth noting that there were more female participants than male participants, which aligns with the epidemiology of unruptured intracranial aneurysms, as these are more commonly observed in females .A limitation of this study was that all study participants were treated in the same hospital located in the Netherlands. Patients might perceive AR differently depending on the health resources in a country. This partially limits the transferability of these findings to other patient populations.Another limitation is that we opted for videos to illustrate AR instead of an AR application or AR-glasses due to practical considerations. This made it possible to conduct the interviews online, which was necessitated by the interviews being conducted during the COVID-19 pandemic. It is possible that this resulted in a less immersive experience compared to an application or AR glasses.This study suggests that patients with unruptured intracranial aneurysms are open to receive patient education regarding their disease with AR. Patients expect that AR models can help patients with intra-cranial aneurysms better understand their disease, treatment options and risks. Additionally, patients expect AR could improve doctor-patient communication. The views, expectations and preferences of patients identified in this study can contribute to improving information provision and communication using AR applications by providing insights into patients’ perceptions.Future studies on AR in patient education should take these expectations and wishes into account and evaluate the extent to which the use of AR models could positively influence the quality of patient education.


We all agree that healthcare is complex, but most studies, although using this kind of sentence to introduce their background, do little to effectively deal with such complexity in their analyses. Holmström et al proposed a methodological approach to tackle healthcare complexity by integrating system dynamics (SD) into action research (AR). This commentary highlights three touch points that makes the combination of AR and SD feasible, namely the epistemological ground, the use of experimentation and the collaborative approach. The proposed approach addresses some of the key sources of the complexity characterizing healthcare settings. These characteristics defines what literature calls ‘wickedness,’ ie, a set of conditions that prevent an agreement on problems definition and the related solutions.2 To cope with such wickedness, the adoption of a collaborative and systemic view of problems is desirable.2 Healthcare is complex, and we may all agree with such a statement. However, in modern science, there is little universal agreement on how to define and frame complexity.3 to cope with complexity in the healthcare sector is based on the integration of two methodological approaches that both allow coping with the above-mentioned sources of complexity. In particular, Holmström et al,3 suggest integrating system dynamics (SD) into action research (AR) strategies to conduct research in the healthcare policy and management realm . The intuition beyond the paper of Holmström and colleagues4 who defined it as “a comparative research on the conditions and effects of various forms of social action and research leading to social action.” AR was proposed so as to cope with the perception that traditional science was not helping in the resolution of critical and complex social problems. In AR, practitioners and social scientists experiment on social systems to find ways to bring about needed changes. This research strategy is thus aimed at contributing to both the theoretical domain – ie, etic – and to the practical domain – ie, emic – closing the gap between theory and practice often characterizing social sciences research5 and natural ones.6 Applications of AR thus responded to the inability of traditional reductionist approaches to grasp and take into account the complexity of certain social systems. This explains why AR has been largely applied in the health policy and management domain. The term AR was first coined by Lewin4 In this sense, AR gives floor to the integration of various research techniques and approaches that may support experimentation. Being AR a pragmatic research methodology, there are no specific indications on how interventions and changes should be put in place in order to experiment on the social system analysed. What is given is the process, which is conceived as “a spiral of steps, each of which is composed of a circle of planning, action, and fact-finding about the result of the action.”8 Thanks to the systemic and dynamic view intrinsic to this technique, SD has been widely applied to deal with complex health policy and management problems.9 SD is a methodological approach developed by Jay Wright Forrester for modelling and simulating complex physical and social systems and experimenting with the models to design strategies for management and change.3 – as an approach to cope with the complexity characterizing policy and management improvements in healthcare. This commentary critically analyses the integration of SD into AR – proposed by Holmström et al3 integration of SD into AR in healthcare, it is possible two identify three key touch points that allow the integration of the two approaches. These are: the epistemological ground; the use of experimentation; and the collaborative approach to research. From Holmström et al One of the reasons why AR and SD can be successfully integrated in healthcare studies is identified in the epistemological ground that both share.10 while we refer to SD as a research technique, ie, a tool to collect and analyse data and information in order to produce the research output. As such, while AR can be carried out through the support of other research techniques, SD can also support other research strategies . What makes the integration of SD into AR feasible, favourable and even desirable, is that both fit well within the pragmatism research philosophy.12 Pragmatism focuses on the practical understanding of real-world issues. According to this philosophy, research strategies, methods and techniques should be chosen in order to provide useful answers to practical problems – as represented in the research questions.10 Pragmatism may also be considered an adequate epistemological ground to host studies and researches dealing with complexity and with complementarity – according to which no single research technique, theoretical position, or modelling strategy provides a complete account of all system’s features – as it allows to acknowledge multiple viewpoints and distinct levels of explanation of healthcare dynamics.13 AR can be defined as a research strategy,3 are all referred to healthcare organizational improvement processes and learning. As both AR and SD have been widely used to address research objectives in this domain , the suggested approach fits well in order to tackle Holmström et al3 research aim. The five improvement cases reported by Holmström and colleagues3 as a touch point between SD and AR is related to the production of research results through experimentation. Another feature that clearly emerged from the article of Holmström et al AR is indeed based on the implementation of changes within an organization  to tackle a real problem. This takes the form of experimentation in which researchers and practitioners evaluate the proposed changes once implemented in order to produce new knowledge about the system analysed.8 As reported by Holmström et al,3 during the AR process, “the simulation model and user interface were adapted to allow for the testing of a multitude of suggestions and clarified what could work in reality.” In this sense, SD provides a valuable contribution to AR since it allows one to experiment with the social system – eg, the healthcare organization – before implementing costly changes (in terms of money and effort). SD is also experimentation friendly as it allows to simulate the behaviour of the modelled system under different conditions. Simulation is a valuable tool to experiment and discover how complex social systems work and where high leverage points may lie.14 As such, shared understanding on problems and agreement on solutions should not be taken for granted. The third touch point refers to the orientation toward the involvement and engagement of multiple actors and stakeholders that both AR and SD share. As previously mentioned, healthcare systems and organizations’ complexity derives, among other factors, from pluralism and institutional fragmentation. Healthcare services are indeed delivered through the collaboration of different professionals and organizations that may have different values, interests and objectives.3 On the other hand, an important branch of application of SD is aimed to define the shared mental model of a group of people with respect to a dynamic problem and to translate this into a simulation model.15 This is called Group Model Building. Both AR and SD consider the engagement of the relevant stakeholders as a key moment of the research process. In fact, AR is a research strategy “that is based on actively engaging participants that are willing to share their own perspective on a problem, to collaborate so as to find a mutually accepted solution on a problem.” Even in this case, thus, SD supports and facilitates AR processes since it fosters the definition of shared mental models related to the problems to be addressed and makes these explicit.3 allowed us to better explore the advantages that integrating SD in AR may bring when doing research in the healthcare domain. The analysis of the three touch points emerging from the article of Holmström and colleagues The integration of SD into AR is allowed by interesting synergies. First of all, the AR strategy provides SD with an important epistemological support. SD has been criticized by researchers producing knowledge following positivism and neo-positivism paradigms with regards to SD models’ ability to mimic reality, their validation, and the use of prediction. Using SD within AR processes may strengthen the positioning of SD as a technique that supports (though non-exclusively) research belonging to the pragmatism philosophy realm. On the other hand, SD provides AR with two key features that may improve the production of knowledge in terms of efficiency and effectiveness. The first one is related to simulation. SD simulation allows us to experiment with complex social systems  and to test solutions and changes before their actual implementation. This fosters learning processes, as multiple solutions can be easily and rapidly tested, saving also effort in terms of time and money as only well-performing changes tested through simulation would be implemented. The second one refers to the systematization of the knowledge emerging from the multiple mental models of the people involved in the action and the elicitation of the shared mental model through Group Model Building. As such, SD results being a valuable tool to improve the collaboration within the group of stakeholders called to contribute to the action. Moreover, the elicitation of the shared mental model may better clarify and represent the contribution to knowledge produced by the AR process. Not applicable. Author declares that he has no competing interests. GN is the single author of the paper.


Our case report highlights the importance of understanding various mechanisms of an atrioventricular block (AVB) and recognizing potential iatrogenic culprits. Despite the prevalent use of second-generation antipsychotics and the growing popularity of long-acting formulations, it is not routinely recognized as a cause for AVB. Second-generation antipsychotics such as risperidone have a dose-dependent pro-arrhythmic effect and are known to cause first-degree AVB. Our case presents an opportunity to recognize an unappreciated cause for AVB and switch to safer alternatives. In the era of long-acting injectables, it is important to monitor for these effects prior to escalating doses and risking high-degree AVB. While non-adherence to medications is seen across all disciplines of medicine, it is particularly common in psychiatric patients due to the lack of awareness of their illness (anosognosia). For such reasons, long-acting psychotropic formulations, with high-loading doses are often favored. Herein, we present a case of a 31-year-old male who presented with a new onset second-degree atrioventricular block (AVB) following a recent loading dose of a long-acting second-generation antipsychotic.A 31-year-old African American male with schizophrenia, hyperthyroidism, and marijuana use disorder presented with complaints of auditory hallucinations and intermittent headaches, which had been ongoing for the past week. He denied any fever, chills, dyspnea, chest pain, palpitations, or feeling of missed beats. Physical exam revealed an anxious affect but otherwise unremarkable. The metabolic panel and complete blood count were within normal limits. Ethanol levels were less than 10mg/ml, Urine drug screen was positive for cannabinoids, and his TSH levels were 2.3mIU/L. Telemetry and electrocardiogram (ECG) showed new onset second-degree Mobitz type 1 AVB (Figure Common reversible causes of AVB were evaluated. He had no ischemic heart disease, cardiomyopathy, or myocarditis. TSH and electrolytes were within the normal range. His recent initiation on Invega Sustenna, a second-generation antipsychotic containing the active ingredient Paliperidone combined with palmitate to provide a long-acting formulation was of concern . He alsoOur case and a few others have shown that second-generation antipsychotics can be associated with AVB. Our case highlights a concerning risk of higher degree AVB with increased doses. This presents an opportunity to recognize a potential unappreciated cause for AVB, and switch to safer alternatives before further progression. In an era of long-acting injectables, it is important to monitor for these effects prior to initiating or escalating doses. Concurrent use of long-acting and short-acting formulations of Paliperidone, or with other pro-arrhythmic agents should be done with caution.


There is increasing effort in both the inpatient and outpatient setting to improve care, function, and quality of life for children with congenital heart disease, and to decrease complications. As the mortality rates of surgical procedures for congenital heart disease decrease, improvement in perioperative morbidity and quality of life have become key metrics of quality of care. Quality of life and function in patients with congenital heart disease can be affected by multiple factors: the underlying heart condition, cardiac surgery, complications, and medical treatment. Some of the functional areas affected are motor abilities, exercise capacity, feeding, speech, cognition, and psychosocial adjustment. Rehabilitation interventions aim to enhance and restore functional ability and quality of life for those with physical impairments or disabilities. Interventions such as exercise training have been extensively evaluated in adults with acquired heart disease, and rehabilitation interventions for pediatric patients with congenital heart disease have similar potential to improve perioperative morbidity and quality of life. However, literature regarding the pediatric population is limited. We have gathered a multidisciplinary team of experts from major institutions to create evidence- and practice-based guidelines for pediatric cardiac rehabilitation programs in both inpatient and outpatient settings. To improve the quality of life of pediatric patients with congenital heart disease, we propose the use of individualized multidisciplinary rehabilitation programs that include: medical management; neuropsychology; nursing care; rehabilitation equipment; physical, occupational, speech, and feeding therapies; and exercise training. In the United States, survival in the first year of life for children with critical CHD  is 75.2% vs. 97.1% for those with non-critical CHD , neurodeThere are only a few pediatric cardiac rehabilitation programs and there is little published research about their effectiveness. Recent research showed that almost half of patients that undergo surgery for CHD required some sort of rehabilitation therapy in the acute postoperative period . In contRehabilitation management of pediatric cardiac patients frequently starts in the inpatient acute setting, especially for children with severe cardiac defects who spend a significant amount of time in the hospital, and it continues in the outpatient setting . Of thos“Neurodevelopment” refers to the neurologic and developmental trajectory of a child.“Functional outcomes” refer to the neurodevelopmental trajectory of children as well as their reported re-integration into their communities, ability to gain independence, and overall quality of life.“Function” is a key tenet in rehabilitation and encompasses all aspects of daily life, including mobility, communication, feeding, and other activities of daily living.“Rehabilitation management” includes an interdisciplinary approach to improving function as defined previously. We include key components of this rehabilitation team further in this paper.In this paper, we briefly discuss the functional deficits in CHD and then explore the potential role of each member of the multidisciplinary pediatric cardiac rehabilitation team in addressing them : In this period, the aim is to decrease the acute functional impact of the surgical intervention and possible post-surgical complications, and facilitate the transition home. Acute post-surgery care can take place in the acute medical setting, acute inpatient rehabilitation or a long-term acute care setting. This phase is more relevant in CHD vs. adults with acquired heart disease.Post-surgery (Phase II): This subacute phase, which is analogous to the same phase in acquired heart disease, includes exercise training for older pediatric patients and cardiovascular risk factor management adapted to the functional needs of the pediatric patient population. Additional outpatient rehabilitation therapy services may also be needed.Our goal is to provide a framework for developing a multidisciplinary rehabilitation program to improve long-term function and quality of life for pediatric patients with CHD. In the course of this paper we will:with CHD .Acute p3.3.1.Children born with complex CHD have smaller and more immature brains at birth compared to children without CHD . This brLonger-term abnormal neurodevelopment outcomes have been extensively described in patients with CHD , 13. TheAs more neurodevelopmental follow-up programs are established and refined, neurologists, psychologists, neuropsychologists, and other health providers have outlined their experiences and recommendations for the care of children with congenital heartdefects , 18. In 3.2.Feeding difficulties are not uncommon in patients with CHD . Up to 53.3.In CHD, speech and language difficulties include delays and/or impairments in the motor and cognitive aspects of communicative functioning –31, whic3.4.An active lifestyle plays a critical role in health outcomes. As noted above, neurological and cognitive impairments can also impact exercise capacity and physical activity. Thus, it is important to consider all aspects of health-related fitness. This is important because exercise and physical activity are two different constructs (the former is a subcomponent of the latter) and each can result in different outcomes, all of which are important to long-term health in complex CHD.2), the gold standard measurement of peak aerobic exercise capacity , the use of AAC strategies may be required to establish reliable communication during hospitalization . The SLP4.1.5.Regardless of cardiac anatomy, all patients with CHD are at risk for feeding difficulties , failureFeeding assessment and management both for the in- and outpatient setting are further detailed in 4.1.6.4.1.6.1.Children in ICUs and those in inpatient medical and rehabilitation units can benefit from systematic and focused psychological and neuropsychological consultation to: identify those with the highest risk of developmental, cognitive, and psychosocial concerns; aid with connecting patients and families with needed support; prepare children and families for the next stages of recovery; and provide guidance on additional neuropsychologic and developmental evaluation throughout recovery , 59. ForA portion of children in cardiac ICUs display delirium, a clinical syndrome with acute disturbance in consciousness and cognition that can fluctuate throughout the day . In many4.1.6.2.Families of infants with CHD need family-centered care in cardiac ICUs, as the stress of hospitalization can have long-lasting developmental and psychosocial implications . Pediatr4.1.7.Patients may require additional rehabilitation support upon discharge, depending on the complexity of their cardiac disease and their medical needs, skilled nursing needs, and functional level at discharge. This additional support may include acute inpatient rehabilitation, outpatient interventions, or home-based care.•Discharge to acute inpatient rehabilitation, in which the focus is on the continued delivery of acute medical management, required skilled nursing care, and intensive attention to function. Patients receive three hours of rehabilitation therapy per day.•Discharge to long-term acute care (LTAC), where the goal is to provide medical management and necessary skilled nursing care. There is no minimum amount of required therapy.Outpatient options:•Discharge to early intervention services or school-based therapies, pending qualification for such services.•Discharge to an outpatient rehabilitation therapy program.•School-based rehabilitation therapies and accommodations.Inpatient options:4.2.Outpatient rehabilitation for children is equivalent to Phase II of Cardiac Rehabilitation in Adults with Acquired Heart Disease. However, since surgery in pediatric patients can occur in infancy or early childhood, outpatient rehabilitation may need to be initiated several years after the initial surgery. This is because certain functional difficulties or disabilities may not be recognized until several years after initial surgery and/or the patients might be too young to participate in certain types of rehabilitation therapy. However, when feasible, interventions should start early and be adapted to the appropriate developmental needs of each CHD patient.This phase of rehabilitation should include aspects of the more classical cardiac rehabilitation program suggested by the American Heart Association (AHA)  and Amer4.2.1.Physical and occupational therapy are an essential part of the outpatient rehabilitation program. The goals, assessments, and interventions of both physical and occupational therapy are similar in the inpatient and outpatient settings. These have been extensively detailed in our recommendations for inpatient care and would similarly apply to the outpatient setting –4.4.2.2.2 after CHD surgery in children and adolescents  is to not only improve exercise capacity and physical activity but also provide the patient with tools and support to become as functional and independent as possible and to improve their overall quality of life. Over the past few years, there has been a major effort to develop more structured cardiac rehabilitation/exercise training programs , 80, 81 4.2.3.4.2.3.1Throughout their childhood, children with CHD often require periodic monitoring of their speech and language development on an outpatient basis . Assessm4.2.3.2The typical goal of speech and language intervention is to optimize overall communicative function, thereby supporting social and academic potential, enhancing emotional well-being, reducing frustration, and improving overall quality of life. Treatment frequency and intensity may change over time based on the number and types of skill areas targeted and the consolidation of learned skills –98. Outp4.3.4.3.1.Evaluation of feeding and swallowing function is based on current skills, age, nutritional needs, and parental preferences/concerns. Those who required assisted feeding preoperatively are at greater risk of being discharged with a feeding tube . For inf4.3.2.Outpatient feeding and swallowing intervention plans are determined based on the evaluation of patients’ skills, areas of need, age, and service availability. Infant feeding treatment typically targets changes in the feeding environment, positioning during feeding, nipple flow rate, or other therapeutic interventions to improve the feeding dynamic. As indicated, treatment may also target oral aversion and feeding difficulties for infants who do not yet accept oral feeding. Therapeutic interventions are recommended when aspiration is observed during the instrumental assessment. When patients do not respond to these interventions, altered liquid consistencies may be trialed with close monitoring and in collaboration with the medical team due to potential gastrointestinal morbidities.Children may present with feeding difficulties that are multi-factorial, including oral-motor delays, sensory-based difficulties, learned behavioral difficulties, and ongoing or newly acquired aspiration. Longer-term intervention plans may be established to support these needs. Given the sometimes slow and gradual progression of skills and potentially complex difficulties demonstrated by children, caregiver education and counseling are also typically provided .4.4.4.4.1.Patients with CHD should be screened for developmental, neuropsychological, and psychosocial concerns in the outpatient setting; this can help the rehabilitation team individualize targets and services for each patient. For guidelines on the recommended timing of follow-up evaluations, assessment tools, and special testing considerations, readers are referred to the guidelines for neurodevelopmental follow-up clinics with children with congenital heart defects , 18, 19 4.4.2.Psychologists and neuropsychologists in outpatient rehabilitation programs can provide cognitive rehabilitation designed to teach specific cognitive skills and establish compensatory mechanisms for impaired cognitive domains . PsycholPsychological care may improve not only psychosocial health but also physical health. In a meta-analysis of 23 randomized controlled trials involving adult cardiac patients, psychological care reduced emotional distress and improved systolic blood pressure, heart rate, and cholesterol levels . In a st5.Rehabilitation needs in pediatric patients with CHD are very different from those of adults with acquired heart disease. As such, rehabilitation programs for patients with CHD should be designed to support the array of functional difficulties described here, and this article provides a valuable framework for developing such programs. Given the lack of available literature and data on pediatric cardiac rehabilitation, we developed this framework based on expert recommendations regarding best practices. The individuals contributing to this article respectively have expertise in rehabilitation, cardiology, cardiac surgery, and neuropsychology, all with a specific focus on our target pediatric population. Our framework addresses rehabilitation in both the inpatient and outpatient settings and incorporates roles for a multidisciplinary pediatric cardiac rehabilitation team. Further research is needed to quantify the impact of these multidisciplinary interventions and help us continue to tailor these programs to the specific needs of the pediatric cardiac population.


Assistive and rehabilitation robots aid individuals with physical, cognitive, or sensory impairments, providing these individuals with opportunities for improved quality of life and independence. These robots make the life of a physically weak person more comfortable and are thus beneficial to society. Assistive robots possess exceptional abilities to recognize their surroundings, analyze sensory information, and carry out actions that are invaluable to individuals with disabilities. Furthermore, these robots play an important role in facilitating rehabilitation by understanding and enhancing the rehabilitation process. These robots aid a wide array of sensorimotor functions, provide therapeutic training, and evaluate the sensorimotor performance of patients with the highest precision.In recent years, these systems have been developed, expanding the robotics field and its applications in a user-friendly manner. Furthermore, recent literature shows that many studies have been carried out to investigate the possibility of using biosignals to control assistive robots. Electromyography (EMG) and electroencephalography (EEG) signals of wearers have been extensively used to control assistive and rehabilitation robots since those signals can specifically be used to identify the motion intention of the wearer. Since EMG and EEG signals can represent the wearer's motion intention the wearer is free of actuating any additional device to control the assistive robot. However, the EMG and EEG derived from individuals with neurological impairments demonstrate different patterns when contrasted with those of their healthy counterparts.Research on assistive robots integrates advanced mechatronics and intelligent sensing to restore weak sensorimotor functions. Assistive robots such as exoskeleton robots have been applied for tremor assessments and suppression and neurorehabilitation in recent studies. Furthermore, in the last few decades, many significant contributions have been made in this field. These robots still have a margin for development and advancement to enable a synergetic interaction with the user and to generate human-like motions.The articles in the first volume of this Research Topic underlined both the promise and the challenges faced by the field of assistive and rehabilitation robots. The articles further recognized the need for additional perspective on the control of these robotic devices. Considering the significant responses received from the research community for the first volume of this Research Topic, the second volume also aims to create a multidisciplinary forum of discussion on the recent advances in controlling assistive and rehabilitation robots, such as exoskeleton robots. Authors have been invited to contribute high-quality articles containing original research findings, as well as systematic, narrative, or scoping reviews presenting relevant analysis and discussion on the current state of the art. Our main focus was topics that include but are not limited to developments of controllers for the upper limb/lower limb assistive/rehabilitation robots, biomechanical investigations of exoskeleton robots and other assistive/rehabilitation robots, novel sensors for assistive/rehabilitation robots to generate human-like motions, processing of EMG/EEG signals, EMG/EEG signals-based assistive/rehabilitation robot control, mathematical and physical algorithms for control of assistive/rehabilitation robots, assessment and benchmarking of assistive/rehabilitation robots' functionality, and clinical studies of assistive robot control.The Research Topic received remarkable interest among researchers in the field. In this volume, a Research Topic of five meticulously selected articles that investigate various aspects of the subject are presented following a rigorous and thorough peer-review process. Among these articles, three articles discuss the utilization of EMG signals for the control of assistive and rehabilitation robots.Exploring surface electromyography (EMG) as a feedback variable for the human-in-the-loop optimization of lower limb wearable robotics by Grimmer et al.A CW-CNN regression model-based real-time system for virtual hand control by Qin et al.LST-EMG-Net: long short-term transformer feature fusion network for sEMG gesture recognition by Zhang et al.Another article is dedicated to developing an EEG-sEMG hybrid strategy for prolonged active rehabilitation.A low-cost and portable wrist exoskeleton using EEG-sEMG combined strategy for prolonged active rehabilitation by Yang et al.A robot-assisted therapy to increase muscle strength in hemiplegic gait rehabilitation by Gil-Castillo et al.” presents the feasibility of using a robot-assisted therapy methodology based on the Bobath concept to perform exercises applied in conventional therapy for gait rehabilitation in stroke patients.The article titled “First, we discuss the contributions of articles that present the development of EMG-based control methods for assistive and rehabilitation robots.Exploring surface electromyography (EMG) as a feedback variable for the human-in-the-loop optimization of lower limb wearable robotics by Grimmer et al.This research investigates whether lower limb sEMG could be an alternative feedback variable to overcome time-intensive metabolic cost-based exploration. Human-in-the-loop (HITL) optimization with metabolic cost feedback has been proposed to reduce walking effort with wearable robotics. An experiment was designed to elicit changes in the effort by loading and unloading pairs of weights in three randomized weight sessions for 13 subjects during treadmill walking. EMG of seven lower limb muscles was recorded for both limbs. Mean absolute values of each stride before and following weight loading and unloading were used to determine the detection rate for changing between loaded and unloaded conditions. The use of multiple consecutive strides and the combination of muscles to improve the detection rate were assessed and estimated the related acquisition times of diminishing returns. EMG drift was evaluated during the warm-up and the experiment to conclude on possible limitations of EMG for HITL optimization. The results suggest using EMG feedback of multiple involved muscles and from at least 10 consecutive strides to benefit from the increases in detection rate in HITL optimization.A CW-CNN regression model-based real-time system for virtual hand control by Qin et al.Many strategies for motion classification or regression prediction tasks based on sEMG signals have been proposed. However, most of them are limited to offline analysis only. This article proposed a channel-wise-convolutional neural network (CW-CNN) regression model-based real-time control system for virtual hand control. An adaptive Kalman filter was designed to smooth the joint angles output before sending them as control commands to control a virtual hand. Three sessions of experiments were carried out with eight healthy subjects. The joint angles estimation accuracy and computational latency were analyzed during the real-time experiments. The experimental results show that the proposed control system has high precision for 3-DOF motion regression simultaneously, and the system remains stable and has low computational latency.LST-EMG-Net: long short-term transformer feature fusion network for sEMG gesture recognition by Zhang et al.sEMG signal gesture recognition is widely used in rehabilitation therapy, human-computer interaction, and in many other fields. Deep learning has gradually become the mainstream technology for gesture recognition. It is essential to consider the characteristics of the surface EMG signal when constructing the deep learning model. However, current deep learning models usually extract features from single-length signal segments. This can easily cause a mismatch between the amount of information in the features and the information needed to recognize gestures. This is not conducive to improving the accuracy and stability of recognition. Therefore, in this research, a long short-term transformer feature fusion network (LST-EMG-Net) was developed. The network considers the differences in the timing lengths of EMG segments required for the recognition of different gestures. The researchers successfully fused the features using a feature cross-attention module and output the gesture category. The LST-EMG-Net was evaluated on multiple datasets based on sparse channels and high density.A low-cost and portable wrist exoskeleton using EEG-sEMG combined strategy for prolonged active rehabilitation by Yang et al.”. This article proposes a low-cost, portable wrist rehabilitation system with a control strategy that combines sEMG and EEG signals to encourage patients to engage in consecutive, spontaneous rehabilitation sessions. Furthermore, a detection method for muscle fatigue based on the Boruta algorithm and a post-processing layer is proposed. This method significantly improves the accuracy of fatigue detection for four distinct wrist motions.Hemiparesis is a common consequence of stroke and has a serious impact on the quality of life of patients. Active training is an important factor in achieving optimal neurological recovery, but current wrist rehabilitation systems pose challenges in terms of portability, costs, and muscle fatigue risks during long-term use. The article on an EEG-sEMG hybrid control method presents developing an EEG-sEMG hybrid strategy for prolonged active rehabilitation. The article is titled “A robot-assisted therapy to increase muscle strength in hemiplegic gait rehabilitation by Gil-Castillo et al.The above article examines the feasibility of using robot-assisted therapy based on the Bobath concept to perform exercises applied in conventional therapy for gait rehabilitation in stroke patients. The therapy aims to improve postural control and movement through exercises based on repetitive active-assisted joint mobilization, which is expected to produce strength changes in the lower limbs. Robotic assistance is gradually reduced as therapy progresses, and the patient's burden increases to achieve a certain degree of independence. The results showed a significant increase in hip abduction and knee flexion strength on both sides, although there was a general trend of increased strength in all joints. However, the range of motion at the hip and ankle joints was reduced.This Research Topic provides a comprehensive overview of current research on the control of assistive and rehabilitation robots through EMG/EEG signals. The highlighted articles shed light on both the potential advancements and the limitations within the field of assistive and rehabilitation robotics. Furthermore, these articles recognize the need to provide further perspectives on the control methods of these robots. The researchers and practitioners should further concentrate on practical case studies, giving precedence to investigations and experiments that involve patients with neurological impairments. In this way, the quality of life for those requiring neuro-rehabilitation involvement can be enhanced.Overall, the articles presented on this Research Topic not only contribute to clarifying the existing knowledge but also open the way to a new paradigm in the field of EMG/EEG signals-based control of assistive and rehabilitation robots. Through these articles, we aim to foster a deeper understanding of the role played by EMG/EEG signals in empowering assistive and rehabilitation robotic systems to improve human lives.RG: Writing—original draft, Writing—review and editing. TL: Writing—review and editing. DZ: Writing—review and editing.


Schizophrenia is a debilitating mental disorder with a high disability rate that is characterized by negative symptoms such as apathy, hyperactivity, and anhedonia that can make daily life challenging and impair social functioning. In this study, we aim to investigate the effectiveness of homestyle rehabilitation in mitigating these negative symptoms and associated factors.A randomized controlled trial was conducted to compare the efficacy of hospital rehabilitation and homestyle rehabilitation for negative symptoms in 100 individuals diagnosed with schizophrenia. The participants were divided randomly into two groups, each persisting for 3 months. The primary outcome measures were the Scale for Assessment of Negative Symptoms (SANS) and Global Assessment of Functioning (GAF). The secondary outcome measures included the Positive Symptom Assessment Scale (SAPS), Calgary Schizophrenia Depression Scale (CDSS), Simpson-Angus Scale (SAS), and Abnormal Involuntary Movement Scale (AIMS). The trial aimed to compare the effectiveness of the two rehabilitation methods.T = 2.07, p = 0.04). Further analysis using multiple regression indicated that improvements in depressive symptoms  and involuntary motor symptoms  were associated with a reduction in negative symptoms.Homestyle rehabilitation for negative symptoms was found to be more effective than hospital rehabilitation, according to the changes in SANS (Homestyle rehabilitation may have greater potential than hospital rehabilitation in improving negative symptoms, making it an effective rehabilitation model. Further research is necessary to investigate factors such as depressive symptoms and involuntary motor symptoms, which may be associated with the improvement of negative symptoms. Additionally, more attention should be given to addressing secondary negative symptoms in rehabilitation interventions. Negative symptoms, which include reduced emotional expression and avolition, have been identified as core symptoms of schizophrenia . The sevRehabilitation training has been recognized as an important method for ameliorating the negative symptoms of schizophrenia, as demonstrated in various studies , 15. AmoThe aim of this study is to examine the effectiveness of home rehabilitation as a mode of rehabilitation, specifically its impact on negative symptoms and associated factors . Thus, the study makes three assumptions: (1) home rehabilitation is an effective mode of rehabilitation, (2) home rehabilitation produces better results in reducing negative symptoms compared to hospitalization rehabilitation, and (3) negative symptoms are influenced by several factors, among which positive symptoms, depression, and extrapyramidal symptoms are the most significant.A total of 100 inpatients with schizophrenia were recruited from September 2021 to November 2021 at the Haidian Mental Health Center, Beijing. A total of 100 patients with schizophrenia were randomly divided into the homestyle rehabilitation group and the hospital rehabilitation group, with 50 cases in each group . A computer-generated random number generator was used to assign each participant to either the intervention or control group. If the random number generated is an even number, the participant is assigned to the intervention group. If the random number generated was an odd number, the participant was assigned to the control group.Both groups were assessed at baseline at the time of discharge from the homestyle rehabilitation group. Subsequently, three participants dropped out . Ultimately, 49 people in the homestyle rehabilitation group and 48 people in the hospital rehabilitation group completed the interventions. All inpatients included were aged between 18 and 55 and diagnosed with schizophrenia according to the ICD-10 by at least two psychiatrists. We obtained participants’ written informed consent along with their demographic and clinical information. Participants who were discharged from the hospital according to the informed consent  could no longer participate in the study. This study was approved by the ethics committee of the Mental Health Center of Haidian in Beijing (no. 109) .Importantly, the two groups of participants underwent standardized rehabilitation training with the same contents and procedures but in different locations. The same assessment tools were used to assess all participants before the intervention and after the 3-month intervention. The two groups underwent the same standardized rehabilitation training at different locations, which mainly included (1) medication management training; (2) psychoeducation interventions; and (3) self-care ability and social skill training. The intervention period was 3 months, and the intervention frequency was three times per week. The specific content of the intervention can be found in It is noteworthy that both groups of participants received standardized rehabilitation training with identical contents and procedures, albeit in separate locations. All participants were assessed using the same evaluation tools before and after the 3-month intervention. The rehabilitation program comprised three main components, namely, medication management training, psychoeducation interventions, and training in self-care ability and social skills. Both groups underwent this standardized rehabilitation training three times a week for 3 months. Please refer to Inclusion and exclusion criteria were as follows: In this study, inclusion criteria consisted of individuals who met the following criteria: (1) a diagnosis of schizophrenia according to the International Classification of Diseases, 10th edition (ICD-10); (2) stable medication for at least 2 months; (3) age between 18 and 55 years; (4) completion of junior high school or higher education; and (5) a duration of illness of at least 5 years. The exclusion criteria were as follows: (1) people with serious physical diseases; (2) people with a history of organic brain disease or head trauma, marked intellectual disability or other serious, uncontrolled physical disease; and (3) people with mental disorders caused by substance abuse such as alcohol and drugs.All participants underwent assessment with standardized scales before and after the 3-month intervention, which were primarily evaluated by two experienced psychiatrists. The interrater agreement was determined to be good (ICC = 0.80).The SANS  was utilThe GAF scale was employed to measure the adaptive functioning of participants, with scores ranging from 0 to 100. It is commonly used to assess the effectiveness of psychiatric treatments. A higher score indicates milder disease symptoms . The GAFThe PANSS  is a widThe Assessment of Positive Symptoms (SAPS) Scale  assessest-tests or analysis of variance (ANOVA), and for nonnormal data, we used nonparametric analyses such as the Kruskal–Wallis test. For categorical data, we used chi-square tests. Second, we performed paired t-tests to compare pre- and post-intervention data between the two groups if the data were normally distributed. If the data were nonnormal, we used the Related-Samples Wilcoxon Signed Rank Test. Third, we used independent sample t-tests and the Kruskal–Wallis test to compare the efficacy of the two types of rehabilitation. Fourth, we conducted multiple regression analysis to identify factors that accounted for significant changes in negative symptoms. We set the significance level at 0.05.First, we compared the baseline clinical symptoms and social function between homestyle rehabilitation and hospital rehabilitation. We assessed the normality of the data distribution using the Shapiro–Wilk test. For normally distributed data, we used t-test or Kruskal–Wallis test or chi-square tests). All indexes were not significantly different. The baseline level comparison of the two groups is shown in Data distribution using the Shapiro–Wilk test and the results are summarized in W = −5.40, p < 0.001), PANSS-G , SANS , and GAF . A significant difference in CDSS  also manifested; however, no difference in other symptom scores was significant. For the hospital rehabilitation group, the results showed significant improvement on the PANSS-N , SAPS , SANS , and GAF .Before and after intervention, the results showed that participants in the homestyle rehabilitation group demonstrated significantly lower scores on the PANSS-N , as well as the SANS . On the other hand, the homestyle rehabilitation group had higher scores on changes in social function than the hospital rehabilitation group based on the assessment of GAF .By comparing the difference between the two groups of participants before and after the intervention, the results showed that in terms of PANSS-N, the homestyle rehabilitation group yielded more positive results than the hospital rehabilitation group  and involuntary motor symptoms  contributed significantly to the improvement of negative symptoms . The results show that both depressive symptoms . The patients/participants provided their written informed consent to participate in this study.JC, FL, NH, WH, HL, LL, and HW were involved in the interpretation of results and manuscript preparation. XL and YL were involved in the conceptualization and design of the study. JC and FL contributed equally to this article. All authors contributed to the article and approved the submitted version.This work was supported by the National Natural Science Foundation of China (NSFC) under grant nos. 82001445 and 82171538, the Natural Science Foundation of Beijing Municipality under grant no. 7212035, and Beijing Hospitals Authority Youth Programme grant no. QML20211203.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.