This study investigated how small and medium enterprises (SMEs) in a country perceive major global risks. The aim was to explore how country attributes and circumstances affect SME assessments of the likelihood, impacts, and rankings of global risks, and to find out if SME risk assessment and rankings differ from the global rankings. Data were gathered using an online survey of manufacturing SMEs in Turkey. The results show that global economic risks and geopolitical risks are of major concern for SMEs, and environmental risks are at the bottom of their ranking. Among the economic risks, fiscal crises in key economies and high structural unemployment or underemployment were found to be the highest risks for the SMEs. Failure of regional or global governance, failure of national governance, and interstate conflict with regional consequences were found to be among the top geopolitical risks for the SMEs. The SMEs considered the risk of large-scale cyber-attacks and massive incident of data fraud/theft to be relatively higher than other global technological risks. Profound social instability and failure of urban planning were among the top societal risks for the SMEs. Although the global environmental and disaster risks were ranked lowest on the list, man-made environmental damage and disasters and major natural hazard-induced disasters were ranked the highest among this group of risks. Overall, the results show that SMEs at a country level, for example Turkey, perceive global risks differently than the major global players. Small and medium enterprises (SMEs) face many small and large internal and external risks. While they can better control much of the internal risks through risk management and treatment measures, they are more vulnerable to external risks because these risks are often beyond their control, influence, radar, and capacity to manage. The World Economic Forum (WEF) has created, assessed, and monitored 30 global risks since 2005, using a survey of about 1000 major global stakeholders and players. By the WEF definition, a global risk is “an uncertain event or condition that, if it occurs, can cause significant negative impact for several countries or industries within the next 10 years”  to examine whether country attributes and circumstances affect SME assessments of the likelihood, impacts, and rankings of global risks; and (2) to find out if SME risk assessment and rankings differ from global rankings. Small and medium enterprises in manufacturing in an emerging economy with global footprints were selected because, unlike the WEF that takes its samples from large international players, the sample SMEs are small individual players in the global economy and it is important to see how they view the global risks.The 2019 Global Risk Report by the World Economic Forum  are weakened by unilateralism, there is little evidence that new and better multilateralism agreements are replacing them , with several potentially failing neighboring states, and as a member of various types of regional agreements, has a unique situation in terms of geopolitical risks. Turkey has been suffering from terrorism and dealing with regional conflicts, both of which have had various impacts on the SMEs. The presence of terrorist activities has impacted the emergence and growth of SMEs and the overall economic performance in the country. Bilgel and Karahasan  found thGlobal societal risks have specific implications for SMEs. Failure of urban planning leads to declining cities, informal urban growth or sprawl, and poor and fragile infrastructure with significant social, environmental, and health issues  are at high risk of being automated over the next 20 years, especially in manufacturing, logistics, and administrative support  have higher likelihoods and impacts. These risks are very critical and need to be controled. Risks that are in the lower (colored in green) and middle part (colored in orange or yellow) of the matrix should be monitored and checked regularly. Although the risk matrix method has been criticized by scholars and professionals Cox , it is aData were collected from a sample of manufacturing SMEs in Turkey. Small and medium enterprises in Turkey are categorized into three groups of micro, small, and medium-sized enterprises based on their employee numbers and annual revenues. Micro firms are those with less than 10 employees and less than USD 430,000 annual turnover. Small firms are those with less than 50 employees and less than USD 3.4 million annual turnover, and medium-sized firms are those with less than 250 employees and less than USD 17.2 million annual turnover Karadag .6.Review the following global economic risks and give your opinion on the likelihood of these risks occurring in the manufacturing sector in Turkey over the next 10 years.Critical infrastructure failure:very unlikelyunlikelysomewhat likelylikelyvery likely7.Please review the following global economic risks and give your opinion about the potential impacts/consequences of these risks on the manufacturing sector in Turkey over the next 10 years.Critical infrastructure failure:minimalminormoderateseverecatastrophicTo assess and evaluate the risks, a questionnaire survey, including 19 questions, was developed. Several questions collected general information about the production type, years in operation, city of operation, position of responder in the business, percent of production for export, percent of imported production materials, and export countries. In two sets of questions SME representatives provided their opinion about the consequences and likelihoods of global risks. Samples of a risk likelihood question and a risk consequences question are:The questionnaire was designed and distributed using Google Form. Small and medium enterprises operating in the manufacturing sector (NACE Revision.02 in C Class through 10–33) were included in the population framework. These are SMEs in the NACE classes that are registered with the KOSGEB  and had an approved KOBİ (SME) certificate in 2017. The survey link was emailed to about 40,000 SMEs on 19 April 2019. Potential respondents were asked to complete the online survey by 3 May 2019. By the deadline, 217 completed responses had been received.The sample covers SMEs in different manufacturing areas. After the unspecified “Other” manufacturing subgroup (39), SMEs in food products (22), textiles (22), machinery and equipment (22), furniture (20), fabricated metal (13), basic metal (9), wood products (9), rubber and plastic (9), electrical equipment (8), and chemical products (8) had the highest number of participants in this study. The questionnaire was completed by various individuals within each sample business, including managers (36), owners (20), accounting managers (13), financial managers (9), business partners (10), board members (3), engineers (6), and other employees (9). Sample SMEs are operating in 50 different cities and 7 geographic regions in Turkey, including Marmara (72), Central Anotolia (47), Aegean (29), Black Sea (24), Mediterranean (23), Eastern Anotolia (11), and Southeastern Anotolia (11).The majority of the sample businesses (132) have been in operation for less than 10 years, only 34 have been in operation for 11 to 20 years, 29 between 21 and 30 years, and the rest (22) have been in business for more than 31 years. About 39.6% of the sample businesses were micro businesses, 37.8% small businesses, and about 22.6% were medium-sized enterprises. More than 60% of the SMEs export their products to varying degrees. They export to a large list of neighboring and European countries in particular. The sample SMEs also import some of their raw materials and equipment, and about 85% use imported products in their productions.Using the methodology on collected data respondents perceived likelihood of the global risks and their impacts were identified and risk values were calculated, and risk matrix was generated using the risk values. This section presents the key findings.Almost all global economic risks are perceived to have very high and high likelihoods by the sample Turkish SMEs Fig. a. HoweveGlobal environmental risks seem to have relatively lower likelihoods to the sample SMEs, compared with the global economic risks Fig. a. Man-maFigure Among global societal risks failure of urban planning and profound social instability were perceived to have the highest likelihood and impact averages among the sample businesses Fig. a, b. WhiFigure Risks can be calculated as the multiplication of likelihood by impacts Table .Table 2MUsing the mean values of each risk category, economic and technological risks are perceived to have the highest likelihood levels followed by geopolitical risks Fig. a. In terUsing the qualitative risk analysis methodology and perceived likelihood and impact data, a risk matrix was generated. Although the horizontal and vertical axes take the values 1 to 5, the matrix axes have been rescaled for better visualization. This risk matrix displays the means of stated likelihoods and consequences for each risk. Risks at the top right and in the red colored area are risks with higher than average likelihoods and consequences. Risks in the lower left part of the matrix and colored green are considered to be low.Figure This study examined the global risks from the perspective of manufacturing SMEs with global footprints in the emerging economy of Turkey. The main aim was to understand whether and to what extent country- and industry-specific contexts and conditions affect SMEs perceptions of the global risks. Key findings are discussed here.First, overall the results suggest that regardless of the ranking, the global risks are of high concern for SMEs in Turkey. The average likelihood for all global risks is 3.56 and the average impact is 3.1. The minimum perceived likelihood (infectious desease) is 3.05 and the minimum perceived impact (severe weather events) is 2.7. These figures confirm that all global risks are of concern for the SMEs and have significant implications for them, particularly those in the manufacturing sector  significantly varied from those perceived by the global companies in the global risk report (World Economic Forum Third, it is not surprising that SMEs’ highest perceived risks are economic and geopolitical risks. Studies demonstrate that financial and economic crises cause substantial downturn in the formation of new SMEs and the performance and survival of the existing ones in the market (Gregory et al. Fourth, failure of regional or global governance and failure of national governance are the geopolitical risks that are among the top perceived risks by the SMEs in this study. These risks have been largely felt by Turkish SMEs in recent years. Turkey has been in close proximity to a number of regional conflicts with potential impacts on the SMEs (Omay et al. Fifth, the sample SMEs also consider the likelihood of large data fraud/theft and large-scale cyber-attacks to be high. This is possibly due to the increasing dependency of the SMEs to the internet and the increasing number of cyber attacks and data theft in recent years (Mbuyisa and Leonard Finally, the relatively lower perceived likelihoods and impacts of the global risks by the sample SMEs can be attributed to the fact that small businesses may not be directly and highly impacted by distance environmental risks such as major natural hazard-induced disasters and that the awareness about some of the environmental risks among the SMEs may be lower than other risks. Moreover, Turkey has not experienced a major natural hazard-induced disaster in the past 20 years, and major weather events have been very local.The results of this study indicate the importance of addressing global risk assessments by SMEs. As more and more SMEs are connected with the national and global economies, their awareness about theses risks and the impacts that they could have for them will increase. This awareness can help SMEs to take these risks into consideration and prepare themselves for such risks. This study highlighted that SMEs’ perceptions of the global risks are different from the businesses that operate at large scale at the global level. It also demonstrated that country’s circumstances can affect SMEs’ assessments of the likelihood, impacts, and rankings of global risks. It demonstrated that SMEs are more concerned about economic risks and risks that directly impact economic systems and variables, particularly geopolitical risks. Environmental risks, while important, are not at the top of the list for SMEs. Considering the significant role that SMEs play in local and national economies and the fact that they are concerned most about global economic and geopolitical risks, it can be argued that efforts towards lowering global economic and geopolitical risks can significantly benefit SMEs.Since Turkey’s SMEs have been in a relatively unique situation in the past two decades with respect to some of the major global risks, similar studies in countries in other parts of the world may shed more light on how country contexts and type and size of businesses impact SMEs’ perceptions of global risks. It was beyond the scope of this study to examine the SMEs’ risk and business continuity actions taken to manage and mitigate the risks. Future studies can also investigate whether and how SMEs prepare themselves for global risks.


This paper provides a solution for fast haptic information gain during soft tissue palpation using a Variable Lever Mechanism (VLM) probe. More specifically, we investigate the impact of stiffness variation of the probe to condition likelihood functions of the kinesthetic force and tactile sensors measurements during a palpation task for two sweeping directions. Using knowledge obtained from past probing trials or Finite Element (FE) simulations, we implemented this likelihood conditioning in an autonomous palpation control strategy. Based on a recursive Bayesian inferencing framework, this new control strategy adapts the sweeping direction and the stiffness of the probe to detect abnormal stiff inclusions in soft tissues. This original control strategy for compliant palpation probes shows a sub-millimeter accuracy for the 3D localization of the nodules in a soft tissue phantom as well as a 100% reliability detecting the existence of nodules in a soft phantom. During the last decade, the human-robot or robot environment interactions have been one of the main foci of research in robotics. Advances in tactile sensing , 2, compRobot-assisted palpation aims to use a robot to perform haptic examinations of a patient in place of a medical practitioner. Often used as an early-stage examination, the goal of this haptic investigation is to estimate the mechanical properties such as the texture, the stiffness, or the consistency of an organ. It can also help to track the size and the position of a nodule or a tumor in soft tissues .In such physical examinations, the compliance of the robotic probe plays an important role due to several reasons such as safety and stability under tissue uncertainty. Since the compliance is defined as the inverse of the stiffness, we mean by compliant system a physical system with low stiffness. By opposition, a stiff system is a system with low compliance. We will deliberately use the two words compliance and stiffness inconsistently in this paper since some ideas are more intuitive when expressed using the stiffness, while some others are more intuitive with the compliance. However, a stiff robotic probe to explore patient tissues relies only on compliance of the tissues which increases the risks of hurting the patient. Our previous study has shown that the compliance of the probe can be used to maximize haptic information gain during hard nodule depth estimation in soft tissue exploration . There hIn the past, most approaches to robotics treated perception (sensing) and action (actuation) as decoupled phenomena. It seems clear that in the context of haptic exploration or robotic interaction with an uncertain environment, actions taken by the robot directly affect haptic perception. Our approach presented in this paper is inspired by recent studies that provide a better insight into the interaction between perception and action , 21. In The remainder of the paper is organized as follows. In the next section, the previous research done on robot-assisted palpation are presented. We will give an insight into the research we accomplished on variable stiffness palpation along with other approaches addressed in the literature. Then, we describe the methods used to study the effect of the stiffness of the VLM probe on the perception and detection of a hard nodule embedded in a soft tissue phantom. In particular, we detail the VLM probe’s hardware, the phantom characteristics, the lateral and longitudinal sweep experiments, and the Finite Element (FE) simulation. The next section discusses the experimental and simulation results we obtained. The following section presents the likelihood functions obtained experimentally and from the FE simulations. The new algorithm to condition haptic perception and localize stiff inclusion in soft tissues is then detailed and tested in another section. Finally, we discuss and conclude about the performance of the algorithm and the impact of the stiffness variation on perception tasks.During the past two decades, we have witnessed an increasing trend to use Minimally Invasive Surgery (MIS) procedures over open surgeries. Even if we can find some exceptions such as robotic probes to measure the blood flow , most ofThe majority of robotic palpation probes aims to detect hard inclusions in soft tissues. In particular, these probes are mainly designed to detect tumors or anomalies which are generally stiffer than the surrounding healthy tissue. The main types of sensors used to do so are the kinesthetic sensors and tactile sensors. In this paper, we refer to kinesthetic sensors, the sensors that aim to give a signal related to the force or the torque applied at a probe joint level. On the other hand, the tactile sensing is referring to fingertip contact sensing using taxel images. Tactile sensing is usually representing the behavior of the mechanoreceptor at the skin level. Finally, It should be noticed that in this section we omit work on medical imagery such as x-ray, CT scans, or ultrasound which are also solutions to detect hard inclusions but not based on haptic palpation.et al. Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: YesReviewer #3: Partly**********2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: N/AReviewer #2: YesReviewer #3: Yes**********3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: Line 5: Authors reported "This trend is opening up new opportunities for robotic applications in the healthcare field." So, it is implied that the healthcare field with robotics is all about tactile feedback, or all the applications include tactile feedback, which is not true at all. It is true that with the tactile feedback, the robotic implications in healthcare field can be improved significantly - but authors should change their original sentence.Line 37: what do the authors mean by " force and tactile" modalities? Kinesthetic and haptic? Please elaborate or clear these modalities.Line 147: The previous sentence cites 4 different studies as the previous studies. Then, the authors start talking about presumably one of them saying "In the previous study ……" without specifying which study they are talking about. It should be clarified.The VLM probe explains the design of the probe, which can be supported also visually. The directions and the definitions should be depicted clearly for the reader.The pdf version I received had the actual Figure and the figure captions separated. I am not sure if this was a draft problem, or the final manuscript will be like this. If it's the later, numbering the sections make no sense, because the reader cannot follow. The authors should find a way to label the system parts on the images directly. Also, using the arrows with color code based on the motion direction might be impossible for the reader to capture, if they are reading from a black/white copy. Such an identification should be handled differently.Why exactly Figure 1 (a) and (b) have different coordinate systems? I understand in both conditions, the sweeping action takes place in the y direction but what does that mean? What is the advantage of such rotation for the designer?The motivation of having two conditions in Figure 1(a) and (b) are not clear. So, the direction of sweeping are different, but they are still tangential to the surface. What is the hypothesis or the expected outcome here? To have different "depth estimation", changing the direction of tangential sweep might be not enough. Also, given Figures have different orientations of component (6), resulting different contact areas with the surface. Is it intentional? If so, how is it related to the sweep direction? If not, why is it different?Figure 2 is impossible to be understood - possibly because the coordinate system for both conditions are different. Still, this Figure must me improved!The probe position seems to be changing between trials in the lateral sweep, but not in the longitudinal sweep. Why?15 different stiffness values have been chosen for the experiment and these values seem random. It seems like these values are changing incrementally, but not linearly  but it is curious how they are chosen! Is there a reason why all the values between 0.65 and 0.71 was tried, but 0.72 is ignored? Why is the differences between the last4 values are much bigger than the first 4?FE model is only used for the longitudinal sweep but not for the lateral. Why?Line 588 : Authors say "This study highlights the role of compliance of a soft robot not only as a design parameter for safety, but also as a control parameter for improved haptic perception " but in the paper, what we see is the comparison between different sweep directions. If these two things are connected, it means authors didn't do a very good job explaining how the sweep direction is related to the probe compliance. It would be also nice to mention this relationship in the discussion and/or conclusion section.Citation numbers cannot be used as a subject of a sentence ([35] proposed ……)Reviewer #2: This paper presents a control algorithm for variable lever mechanism probe to detect and localize embedded nodules in soft tissues. Using this algorithm, the 3D position of the nodule can be estimated. In general, this paper is well-written. There are some questions and possible improves below.1. What is the material used to make the simulated nodules? What types of soft tissues and nodules do you simulate?2. How do you detect when the contact between the probe and the phantom starts? How does the accuracy of detection of the moments of the contact between the probe and the phantom affect the stiffness estimation?Reviewer #3: This paper addresses the problem of detecting hard nodules in soft tissue via robotic palpation, as well as assessing their depth. The central ideas are one, that the stiffness of the probe should matter; and two, that the proper stiffness can be found via a Bayesian search technique. The paper is clearly written and technically sound; however, I see very little evidence that supports the central ideas.First, a few more details: the variable stiffness probe is mounted on a force sensor and equipped with a tactile sensor. Although Fig 7 shows that the latter provides some useful information, as far as I can tell, it is not used to support any of the paper's main points. Therefore, I see the tactile sensor as a bit of a distraction. I would recommend removing it altogether. In any event, the force sensor appears to give a clear indication of nodule location as well as depth. There is no doubt that the robotic probe succeeds!My concern, however, relates to the importance of probe stiffness.Figures 6, 9 and 11 illustrate the dependence of the "force peak prominence" on probe stiffness under lateral and longitudinal swiping, in simulation and experiment. With the exception of Fig 11, we see very little dependence on probe stiffness. Even with Fig 11, it would appear to suffice to pick a good stiffness  and to fix it. The added value of varying the stiffness is by no means apparent.This brings us to the Bayesian search, in which stiffness was updated trial-over-trial in a Bayesian fashion using likelihood functions at different stiffness values with prominence and nodule depth as variables. Two sets of likelihood functions, one obtained experimentally and one obtained from FEM. In both cases, the Bayesian technique clearly shows the best stiffness varying trial-over-trial. That variation, however, is not good evidence that an optimal stiffness is being obtained. To the contrary, it is notable that the best stiffness versus module depth behaves completely differently in Fig 14  versus Fig 15 (FEM). The former tends toward a softer probe for deeper nodules and the latter tends toward a stiffer probe for deeper nodules. It is deeply concerning that the answers are just the opposite of one another. However, when looking at Fig 13, it appears that the likelihood functions simply don't vary much with stiffness. I suspect that the results are just noise.Minor point: could the oscillations seen in Figs 8 and 10 be, in part, due to probe dynamics? Perhaps stick-slip excites those dynamics.**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  14 May 2020Response to the Reviewer 11. Line 5: Authors reported ”This trend is opening up new opportunities for robotic applications in thehealthcare field.” So, it is implied that the healthcare field with robotics is all about tactile feedback,or all the applications include tactile feedback, which is not true at all. It is true that with the tactilefeedback, the robotic implications in healthcare field can be improved significantly - but authors shouldchange their original sentence.The authors would like to thank the reviewer for this comment. The authors did not mean that it isthe only approach that contributes to healthcare robotics. To avoid confusion, the authors rephrased thesentence as follows:In section Introduction, paragraph 1 ”This trend is one of the promising advances that can bring newopportunities for robotic applications in the healthcare field.”2. Line 37: what do the authors mean by ” force and tactile” modalities? Kinesthetic and haptic? Pleaseelaborate or clear these modalities.The authors effectively were meaning kinesthetic instead of force. This has been replaced in the highlightedsentence but also in the rest of the paper. In order to clarify this point, the authors have also addedthese definitions:In section Related work, paragraph 2 ”The main types of sensors used to do so are the kinesthetic sensorsand tactile sensors. In this paper, we refer to kinesthetic sensors, the sensors that aim to give a signalrelated to the force or the torque applied at a probe joint level. On the other hand, the tactile sensingis referring to fingertip contact sensing using taxel images. Tactile sensing is usually representing thebehavior of the mechanoreceptor at the skin level.”3. Line 147: The previous sentence cites 4 different studies as the previous studies. Then, the authors starttalking about presumably one of them saying ”In the previous study . . . . . . ” without specifying whichstudy they are talking about. It should be clarified.As suggested by the reviewer, the authors are now specifying the study that they were talking about:In section Related work, paragraph 9 ”In the previous study [47], we have shown that the stiffness of thearm and hand joints is modified during the longitudinal sweeping exploration of soft tissues by varyingthe level of co-contraction of antagonistic muscles.”4. The VLM probe explains the design of the probe, which can be supported also visually. The directionsand the definitions should be depicted clearly for the reader.If the authors understood well the comment, the reviewer is asking for a figure describing clearly thedesign of the probe and the 2 sweeping directions. The authors have modified Figures 1 and 2. Themodified Fig 1 describes the VLM probe design while the modified Fig 2 clearly depicts the 2 sweepingdirections. We also revised the definitions in the Materials and methods section to clarify the descriptionof the sweeping directions. The modifications regarding the sweeping directions are detailed in thecomment 7. The modifications regarding the design are the following:In section Variable stiffness palpation: the VLM probe, paragraph 2 ”Fig 1 shows the design of the VLMprobe. The VLM probe is based on a revolute variable stiffness joint composed of 2 rigid links (the baselink and the tip link) connected with a revolute joint in parallel with a deformable carbon rod. Thiscarbon rod acts as a variable spring that allows the stiffness of the joint to be controlled thanks to anActuonix L12-30-50-6-I linear actuator. This actuator slides the carbon rod through the base link andthe tip link changing the length of the carbon rod that can be bent (active length). As one can see, the holein the base link has been designed such as that the carbon rod can slide axially but is constrained radiallyto prevent bending of the rod in the base link. On the other hand, the hole in the tip link is large enoughto allow the carbon rod to bend in. A PTFE cylinder is used to transmit the radial forces between the tiplink to the carbon rod. This PTFE cylinder has been designed to slide easily axially when the actuatoris translating the carbon rod. Adjusting the active length of the carbon rod changes, by cantilever effect,the amount of force required to bend the rod and by consequence the angular stiffness of the probe.”In section Variable stiffness palpation: the VLM probe, paragraph 3 ”In order to describe the movementof the probe, we need to define a frame. First, we define the axis z as the direction of the normal to thephantom surface. We then define the x axis as the intersection between the tangent surface of the phantomand the mid-sagittal plane of the probe. Finally, the y is defined in order to obtain a direct orthonormalframe . In the rest of the paper, this reference frame will be used to describe the directions of forcesor displacement.”5. The pdf version I received had the actual Figure and the figure captions separated. I am not sure if thiswas a draft problem, or the final manuscript will be like this. If it’s the later, numbering the sectionsmake no sense, because the reader cannot follow. The authors should find a way to label the system partson the images directly. Also, using the arrows with color code based on the motion direction might beimpossible for the reader to capture, if they are reading from a black/white copy. Such an identificationshould be handled differently.The figures were separated from the captions as explicitly defined in the PLOS submission guideline, thefinal manuscript once edited should integrate the figures in the text. However, in order to simplify thereview process, the figures with section numbers have been edited. Also, the caption referring to colorshave been changed to help the reading from grayscale copies.6. Why exactly Figure 1 (a) and (b) have different coordinate systems? I understand in both conditions, thesweeping action takes place in the y direction but what does that mean? What is the advantage of suchrotation for the designer?The difference in the coordinate system was a mistake. Figures 1 and 2 have been modified to avoidconfusion with the reference frame. More details about the motivation of having the two sweepingdirections are given in the next answer.7. The motivation of having two conditions in Figure 1(a) and (b) are not clear. So, the direction of sweepingare different, but they are still tangential to the surface. What is the hypothesis or the expected outcomehere? To have different ”depth estimation”, changing the direction of tangential sweep might be notenough.The authors thank the reviewer for this comment. The aim of having two different sweeping strategiesis to reproduce the exploration behavior of human participants observed during the previous study [44].Indeed we observed that different strategies could be applied to localize the nodule and to estimate thedepth. In particular, this study showed that the force applied during the palpation varies according tothe aim of the exploration. Based on these observations and results we found interesting to compare thetwo type of sweeping strategies, one local with a light force applied to the phantom and one more global. The hypothesis behind the interest of the sweepingdirection is that one direction is more suitable for nodule localization in the tangential plane where theother one gives better results to estimate the nodule depth. This hypothesis has been verified through thestudy. The authors agree with the fact that changing the direction of the tangential sweep is not the onlyimpacting factor for depth estimation. The presented paper discusses the interest of stiffness variation aswell. To clarify the information regarding the two sweeping directions, the following modification hasbeen added to the paper:In section Sweeping directions, paragraph 2 ”The aim of the two sweeping directions is to reproducesome human participants’ palpation strategies that we observed during our previous study [44]. Wehave shown in this study that the palpation behavior of the participants is adapted to localize the noduleor to estimate the depth. From these observations and results, we found interesting to compare two typesof sweeping strategies, one local with a light force applied to the phantom using the tip of the probe andone more global using the whole palmar region of the probe with the tactile sensor.”8. Also, given Figures have different orientations of component (6), resulting different contact areas withthe surface. Is it intentional? If so, how is it related to the sweep direction? If not, why is it different?The authors thank the reviewer for this comment. On figure 1, the orientation of the phantom and nodule(previously labelled (6)) was, effectively, different between the subfigure (a) and (b). The proposedprobing strategy aims to detect the 3D location of the nodules independently from the orientation of thephantom. This is also the reason why the phantom was also examined in different orientations duringthe evaluation of the algorithm. In this regard, the two sweeping directions have been tested for differentorientations of the phantom. The modification of Figures 1 and 2 (presented in our answer to comment 4of the reviewer 1) should suppress the confusion. To clarify that the strategy aims to be independent ofthe initial phantom orientation, the following sentence has been added in the paper:In section Evaluation of the algorithm, paragraph 1 ”Finally, the proposed palpation strategy aims tolocalize the nodule independently from the phantom orientation, so the algorithm has been tested forseveral orientations of the phantom.”9. Figure 2 is impossible to be understood - possibly because the coordinate system for both conditions aredifferent. Still, this Figure must me improved!Fig 2 has been modified to improve clarity. The latter is presented in our answer for your comment 4.10. The probe position seems to be changing between trials in the lateral sweep, but not in the longitudinalsweep. Why?As explained in previous answers, the two sweeping directions have different objectives. The interest ofthe lateral sweep is to detect the position of the nodule in the tangential plane. To localize the nodule inthe  plane, the probe utilizes both the kinesthetic sensor and the tactile sensor. Then, once a noduleis localized, the longitudinal sweeping is used to improve the depth estimation thanks to the kinestheticfeedback. In this regard, it is interesting to change the position for the lateral sweep (nodule positiondetection) but not for the longitudinal sweep (nodule depth estimation). The following paragraph hasbeen rephrased to improve the clarity of the paper.In section Sweeping directions, paragraph 6 ”This cycle is repeated 5 times, and after the fifth time, theVLM probe is shifted by 5mm along x axis to a new initial position. As the lateral sweeps are performedto localize nodule on a wide area, the aim of this shift is to observe the behavior of the probe when thelatter is sweeping over a nodule at different distances. The next cycle is also repeated 5 times beforeapplying a new shift. In total, 4 shifts are applied, the distance between the initial and last trajectories isthen 20mm.”11. 15 different stiffness values have been chosen for the experiment and these values seem random. Itseems like these values are changing incrementally, but not linearly  butit is curious how they are chosen! Is there a reason why all the values between 0.65 and 0.71 was tried,but 0.72 is ignored? Why is the differences between the last 4 values are much bigger than the first 4?The nonlinearity in the stiffness is coming from the VLM probe behavior. Indeed in a previous study[22], the VLM probe stiffness has been modeled and characterized for several active lengths of thecarbon rod. Instead of using constant steps in stiffness, the authors have chosen linear steps of activelength of the carbon rod for three reasons: 1) we are using the same active carbon rod length as the onewe characterized in our previous study, 2) it is practically easier to control accurately the position of theactuator thanks to its sensor (closed-loop control) 3) It is simpler to implement carbon rod displacementin the FEM simulation. To clarify this information, the following paragraph has been added.In section Sweeping directions, paragraph 9 ”One can notice that the steps of the stiffness tested in thispaper is not linear. This comes from the fact that for simplicity, we have chosen linear steps of 2mm inthe active length of the carbon rod. This choice allows us to take advantage of the probe characterizationperformed in our previous study [22] and makes the stiffness control easier by relying on the closed-loopposition control of the linear actuator. It also simplifies the implementation of carbon rod displacementin the FE simulation. However, since the relation between the stiffness and the active length of the carbonrod is nonlinear, it results in nonlinear steps of stiffness.”12. FE model is only used for the longitudinal sweep but not for the lateral. Why?The reasons why the FE model for the lateral sweeps is not proposed in the paper are multiple. First,the aim of our FE model is to provide a further study on the impact of the joint stiffness variation duringpalpation exploration. However, the experimental results show that the stiffness variation for the lateralsweeps is less significant than for the longitudinal sweeps. As a consequence, there was less interestto further carry the FE simulation for the lateral sweep. Second, to model the lateral sweeps, the FEsimulation needs to be modified from a 2D model to a 3D model. This implies an exponential increasein computation cost . Also, to followthe experimental protocol, the simulation should be performed for the five different shifts, which alsoincrease the computational cost of the study. Finally, in the proposed algorithm, the lateral sweep isgenerally used only once. According to the author, the complexity is not worth the information that thelateral sweep FEM simulation would bring to this paper. To clarify, the following modifications havebeen added to the paper:In section Finite Element Simulation, paragraph 1 ”The aim of our Finite Element (FE) model is toprovide a further study on the impact of the joint stiffness variation during palpation exploration. Theexperimental results show that the variation of stiffness is more significant for the longitudinal sweepsthan for the lateral sweep. As a consequence, we focused our FE simulation on longitudinal sweeps.”In section Discussion, paragraph 2 ”Also, simulating the lateral sweeps would require developing a 3DFE model and repeating the simulation for several shifts . These modifications wouldincrease the computational cost of the simulation significantly.”13. Line 588 : Authors say ”This study highlights the role of compliance of a soft robot not only as a designparameter for safety, but also as a control parameter for improved haptic perception ” but in the paper,what we see is the comparison between different sweep directions. If these two things are connected,it means authors didn’t do a very good job explaining how the sweep direction is related to the probecompliance. It would be also nice to mention this relationship in the discussion and/or conclusion section.The paper presents the analysis of the impact of the probe stiffness (or compliance) variation on the haptic(kinesthetic and tactile) detection of nodules in soft tissues for two sweeping directions. The authorswould like to apologize if the confusion comes from the use of the word compliance. Indeed, complianceis defined as the inverse of the stiffness. The authors then used from time to time compliance instead ofstiffness to avoid repetition. To avoid confusion, the authors have added the following modification inthe paper:In section Introduction, paragraph 3 ”Since the compliance is defined as the inverse of the stiffness, wemean by compliant system a physical system with low stiffness. By opposition, a stiff system is a systemwith low compliance. We will deliberately use the two words compliance and stiffness inconsistently inthis paper since some ideas are more intuitive when expressed using the stiffness, while some others aremore intuitive with the compliance.”14. Citation numbers cannot be used as a subject of a sentence ([35] proposed . . . . . . )As suggested, this has been corrected in the revised manuscript.In section Related work, paragraph 7 ”Using point by point strategy, Hoshi et al. [36] proposed analgorithm to optimize the stiffness estimation of the palpated tissues by coupling the force measurementwith a predictive model based on the Finite Element Method”Response to the Reviewer 2This paper presents a control algorithm for a variable lever mechanism probe to detect and localize embeddednodules in soft tissues. Using this algorithm, the 3D position of the nodule can be estimated. In general, thispaper is well-written. There are some questions and possible improves below.1. What is the material used to make the simulated nodules? What types of soft tissues and nodules do yousimulate?The components used to simulate the nodule are acrylic spheres of 16mm diameter. The size of thenodule represents the size of a tumor type T1 (< 2cm) for breast or liver cancer. This is, according tothe TNM classification, the earliest stage where the nodules can be detected by palpation [49]. With theplatinum-catalyzed silicone (Ecoflex 00-10), the authors aim to simulate general human soft tissues, forinstance, abdominal organs such as liver or human breast. Indeed, this type of silicone is widely used tomimic the mechanical properties of human tissues during palpation [22] or needle insertion [48]. Thisinformation has been added in the paperIn section Soft tissue phantom with nodules, paragraph 2 ”These materials have been widely used to simulatehuman soft tissues mechanical properties. In particular, Ecoflex 0010 has been used in biomedicalsimulators to practice abdominal palpation [11] or needle insertion [48]. The size of the nodule representsthe size of a tumor of type T1 (<2cm) for the breast or liver cancers. This is, according to the TNMclassification, the earliest stage where the nodules can be detected by palpation [49].”2. How do you detect when the contact between the probe and the phantom starts? How does the accuracyof detection of the moments of the contact between the probe and the phantom affect the stiffnessestimation?The authors thank the reviewer for this question. The contact between the probe and the phantom isdetected every time the probe changes the palpation area thanks to its kinesthetic sensor. As described inthe paper, the method is based on an indentation (without sweeping) and the detection of force variation.As shown in Fig 4, from the force sensor readings, it is simple to detect when the probe touches thephantom. Since each actuator has its own position sensors, the position of the probe during the contactcan be found. The accuracy of the contact point detection is important; related studies have shown that avariation of indentation can impact the stiffness estimation . The described detection routine andthe use of the force peak prominence (which takes into account the force measured around the peak) aimsto improve the robustness against an indentation error. More discussion on this point has been added inthe paper.In section Variable stiffness palpation: the VLM probe, paragraph 6 ”To autonomously detect the 0mmindentation position, the method is based on an indentation (without sweeping) and the detection ofvariation in the kinesthetic sensor measurement. This detection strategy aims to improve the robustnessof the nodule detection by improving the accuracy of the indentation measurement. This is particularlyimportant since related studies have shown that a variation of indentation can impact the nodule depthestimation.”Response to the Reviewer 3This paper addresses the problem of detecting hard nodules in soft tissue via robotic palpation, as well asassessing their depth. The central ideas are one, that the stiffness of the probe should matter; and two, thatthe proper stiffness can be found via a Bayesian search technique. The paper is clearly written and technicallysound; however, I see very little evidence that supports the central ideas.1. First, a few more details: the variable stiffness probe is mounted on a force sensor and equipped with atactile sensor. Although Fig 7 shows that the latter provides some useful information, as far as I can tell,it is not used to support any of the paper’s main points. Therefore, I see the tactile sensor as a bit of adistraction. I would recommend removing it altogether. In any event, the force sensor appears to give aclear indication of nodule location as well as depth. There is no doubt that the robotic probe succeeds!The tactile sensor plays an important role in the nodule localization in the  plane. Indeed as explainedin the algorithm, the tactile sensor is used to locate the xn position of the nodule. The detection of xn aftera lateral sweep is not possible from the force sensor only. Without the x position computed after thelateral sweep, the longitudinal sweeping distance would have to be increased by two times the length ofthe tip of the probe. Increasing this distance would degrade the performances of the proposed method,in terms of time . In thisregard, the authors decided to keep the tactile sensor in the paper but added more discussion about it.In section Discussion, paragraph 5 ”In the proposed algorithm, the tactile sensor is currently used tohelp to find the location of the nodule. Removing the sensor would be possible, but it would require toincrease the longitudinal sweeping distance by two times the length of the probe’s tip link. This wouldthen increase the exploration time and also the tissue region area that is probed. These two factors arenot really suitable in the case of patient palpation.”2. My concern, however, relates to the importance of probe stiffness. Figures 6, 9 and 11 illustrate thedependence of the ”force peak prominence” on probe stiffness under lateral and longitudinal swiping,in simulation and experiment. With the exception of Fig 11, we see very little dependence on probestiffness. Even with Fig 11, it would appear to suffice to pick a good stiffness  and to fix it. The added value of varying the stiffness is by no means apparent.The authors thank the reviewer for this comment. To provide a generic method that a user could reproducefor any controllable stiffness probe, we present a detailed statistical analysis of the significance ofjoint stiffness variation on the force peak prominence distribution. This statistical analysis supports theauthors’ claim that the stiffness plays a significant role in the force peak prominence distribution duringlongitudinal sweeps and by consequence on the nodule depth estimation. Also, the case where a lowfix stiffness (Kq = 0:68Nm/rad) is maintained across trials have been tested and added to the Fig 15 tohighlight the limitation of such a strategy in term of estimation confidence.The presented statistical analysis tests the null hypothesis that the data from 2 different stiffnesses arecoming from the same distribution. Since the distribution for each stiffness is not normally distributed,we use the Kruskal-Wallis test, which is particularly suitable for non-parametric distributions. The resultsare summarized in the supplemental Appendix S1. These results of cross Kruskal-Wallis testsshow that, for the longitudinal sweeps with nodules, the force peak prominence is statistically different. In addition, the more different the two stiffnesses are, the higher the significance ofthe difference between their force peak prominence distribution is. Furthermore, the results from theKruskal-Wallis tests for data from the lateral sweeps show that the difference between the force peakprominence’s distributions is not statistically significant. These results support our claim that the stiffnessvariation has a lower significance for the lateral sweeps. Finally, the results of the Kruskal-Wallistests for the longitudinal sweeps data when no nodule is embedded exhibits a lower number of statisticallydifferent distributions than the ones from the data with a nodule. This can be interpreted as the factthat the interaction between the nodule and stiffness impacts the force peak prominence significantly. Inorder to make clearer that the stiffness variation is more significant for the longitudinal sweeps than forthe lateral sweeps, the authors have added the following paragraphs:In section Conclusion, paragraph 1 ”For the lateral sweep, the impact of the joint’s stiffness variation onthe force peak prominence distribution is not as significant as for the longitudinal sweeps. This results inthe fact that the haptic information gain is not sufficient to distinguish the depth of a nodule. However, thestiffness can be chosen to facilitate the detection of a nodule. In contrast, for the longitudinal sweeps, thehaptic information gain from one depth to another is significant and helps to determine which stiffness issuitable for the depth estimation.”In section Lateral sweep, paragraph 10 ”To further support the interpretation of Fig 6, we detail, in thesupplemental Appendix S1, a comparison of the distributions obtained for each stiffness using statisticalanalysis.”In section Experimental results, paragraph 2 ”Similarly to the lateral sweeps, the significance of theprobe’s stiffness variation on the force peak prominence distribution is further studied, using statisticalanalysis, in the supplemental Appendix S1.”To highlight the interest of the proposed algorithm compared to a palpation strategy with constant stiffness.Two examples of Bayesian nodule depth estimation with a constant stiffness (chosen low as recommendedby the reviewer) have been added to the figure 15. These 2 examples clearly show that theinformation gain (KL divergence) drops quickly, and the final confidence level of the depth estimationstays low but with good accuracy. The discussion added to compare the scenario with a constant stiffnesswith the proposed algorithm follows:In section Evaluation of the algorithm, paragraph 8 ”In addition, to complement the investigation on theeffect of the probe’s stiffness variation in the Bayesian nodule depth estimation, 2 trials have been runwithout the stiffness modulation strategy. During these trials performed for 4 and 6mm nodule depths,the stiffness is therefore maintained constant at the stiffness Kq = 0:68Nm/rad . The results for these trials are shown in Fig 15B. One can see that the accuracystays similar to the case where the stiffness is updated from previous knowledge but the confidence levelis significantly lower. It can also be observed in Fig 15C that the KL divergence quickly converges to 0,which means that the repetition of the sweeps with the same fixed stiffness did not bring much informationon the nodule depth. These results confirm that the proposed strategy using stiffness variation helps inconditioning the force peak prominence likelihood and improves the nodule depth estimation.”3. This brings us to the Bayesian search, in which stiffness was updated trial-over-trial in a Bayesian fashionusing likelihood functions at different stiffness values with prominence and nodule depth as variables.Two sets of likelihood functions, one obtained experimentally and one obtained from FEM. In both cases,the Bayesian technique clearly shows the best stiffness varying trial-over-trial. That variation, however,is not good evidence that an optimal stiffness is being obtained. To the contrary, it is notable that the beststiffness versus module depth behaves completely differently in Fig 14  versusFig 15 (FEM). The former tends toward a softer probe for deeper nodules and the latter tends toward astiffer probe for deeper nodules. It is deeply concerning that the answers are just the opposite of oneanother. However, when looking at Fig 13, it appears that the likelihood functions simply don’t varymuch with stiffness. I suspect that the results are just noise.The authors thank the reviewer for this comment. This paper shows how a set of favorable likelihoodfunctions can be used for fast convergence of the posterior to a higher information gain. The paper showsthat this likelihood function conditioning can be done just by changing the stiffness.The authors did not claim that a global optimal stiffness exists. Indeed, the claim of the author is eventhe opposite saying that the stiffness needs to be adapted according to the current knowledge during thepalpation exploration. The proposed method then presents a strategy that tunes the stiffness in orderto increase the probability of getting new information based on prior knowledge (likelihood functions).Comparing the gradient of the selected stiffness between 2 different trials does not really make sensesince it is dependent on the past measurement of a random variable (the force peak prominence). Dueto the stochastic behavior of this variable, even for the same stiffness and same nodule, the informationobtained is different (which is the purpose of the paper). By consequence, it is not surprising that thestiffness gradient followed during the trials with the likelihood functions obtained from the FEM and the likelihood functions obtained from experimental data  are different. This comes from thefact that the prior knowledge is different and so is the information remained to be obtained. This can alsobe supported by another study [14] where the variation of the human’s joints stiffness during palpationtasks has been studied and clearly showed that this joint stiffness follows a random walk. This confirmsthat during palpation exploration tasks even humans do not follow a particular gradient of joint stiffnessvariation.Even if in Fig 13, the variation of the likelihood function for different stiffness is not visually obvious, theadded statistical analysis clearly shows that the variation of the force peak prominence distribution dueto a stiffness variation is statistically significant for the longitudinal sweeps. The discussions obtainedby addressing the reviewer’s comments have been used to strengthen the discussions in the paper. Themodifications done are the following:In section Discussion, paragraph 6 ”Finally, one may notice that the stiffness variations (for the samenodule depth) during the trials with likelihoods functions computed from experimental do not necessaryfollow the same gradient as the variations during the trials with likelihoods function computed fromthe FE simulations. More generally, even across trials repeated for the same scenario, we observeddifferent stiffness variations. This comes from the fact that the stiffness is adapted according to the currentknowledge during the palpation exploration. The proposed method then presents a strategy that tunesthe stiffness in order to increase the probability of getting new information based on prior knowledge(likelihood functions). Due to the stochastic behavior of the force peak prominence, even for the samestiffness and same nodule, the information obtained during a sweep is different from one sweep to another.As a consequence, for two trials on the same nodule, if the information collected so far is different, thestiffness selected to maximize the information gain of the next sweep will be different. Finally, thiscan also be supported by another study [14] where the variation of the human’s joints stiffness duringpalpation tasks has been studied and clearly showed that this joint stiffness follows a random walk. Inother words, during palpation exploration tasks, even humans do not follow a predictable gradient ofjoint’s stiffness variation.”In section Experimental results, paragraph 5 ”In particular, the bests of the tested stiffnesses to detectthe presence of a nodule in the stiffness range of the VLM probe are respectively Kq = 0:68Nm/rad andKq = 0:76Nm/rad for the lateral sweep and for the longitudinal sweep.”to avoid the use of ”optimal”.4. Minor point: could the oscillations seen in Figs 8 and 10 be, in part, due to probe dynamics? Perhapsstick-slip excites those dynamics.These oscillations come from both the dynamics of the probe and the dynamics of the phantom (bothconnected in series). Indeed, if they were coming exclusively from the probe dynamics, the oscillationswould vary with the stiffness variation but not with the nodule depth. Also, one can see that for the samestiffness, the amplitude of the oscillations is varying with the nodule depth ; so, both dynamics are important. The authors strongly agree on the fact that the stick-slip ofthe probe excites the probe and phantom dynamics. For improving clarity, more discussion about theseoscillations has been added in the paper.In section Simulation results, paragraph 3 ”Furthermore, one can notice that the amplitude of theseoscillations varies with the nodule depth, which means that these oscillations are not only dependent onthe probe’s internal dynamics but also on the ones from the phantom.”AttachmentResponse to Reviewers.pdfSubmitted filename: Click here for additional data file. 8 Jun 2020PONE-D-20-03370R1Conditioned haptic perception for 3D localization of nodules in soft tissue palpation with a variable stiffness probe.PLOS ONEDear Dr. Herzig,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.The authors should still address the comments from the reviewer in particular on: (1) how the experimental results can be generalized to non-homogeneous curved objects, (2) the validation of the accuracy of the proposed methodology, and  (3) the modeling approach.plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.Please submit your revised manuscript by Jul 23 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at Please include the following items when submitting your revised manuscript:A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). 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For instructions see: We look forward to receiving your revised manuscript.Kind regards,Tommaso Ranzani, PhDAcademic EditorPLOS ONE[Note: HTML markup is below. Please do not edit.]Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #3: All comments have been addressedReviewer #4: (No Response)**********2. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #3: YesReviewer #4: Partly**********3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #3: YesReviewer #4: Yes**********4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #3: YesReviewer #4: Yes**********5. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #3: YesReviewer #4: Yes**********6. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #3: Thank you for the thorough response to my critique and for adding the constant stiffness case as a comparison. I also stand corrected on the behavior of the stiffness during Bayesian search. I now find the paper quite convincing.Reviewer #4: The authors present a new method for 3D localization of nodules in sot tissues based on a variable stiffness probe equipped with F/T sensors for kinesthetic perception and a tactile array for tactile perception. The authors proposed an exploration strategy based on a Bayesian approach to the detection and localization of the nodule that allows the authors to set the stiffness of the probe and the direction of the sweep to detect and localize the nodule.The paper is well written and clear. However, I have some doubts and concerns that I would like the authors to clarify.Major concerns1) The proposed study is based on the experimental results over a simplified setup in which the soft tissue is isotropic and homogenous, and its surface is flat. Since the method relies on fine-tuning of a few thresholds, how does it generalize to the real case, where the conditions on the soft tissue are not so clean, and the presence of other organs and tissues (even as stiff as bones) affects the sensed force?2) I don't see a great added value in the FEM simulations that the authors propose. First, I would like to have more details about how contacts were modeled , and about the size of the soft tissue and its constraints to a fixed frame Second, if it can have a role in setting the initial value of the stiffness for a real case experiment, the soft tissue should be modeled more accurately.3) My third concern is about parameters. In particular the soft tissue thickness, the nodule Young modulus, and its depth. Since nodule diameter is 16mm, I would expect to have at least 32mm of soft tissue between the nodule and the supporting rigid plane. Even if the applied forces are small, it is a bit surprising that the nodule, especially at 2mm depth, does not influence the stress tensor of the surrounding soft tissue. For what regarding the depth, why the maximum selected depth is 8mm?4) The proposed algorithm seems quite sensitive to the thresholds. In all cases one lateral sweep allows the system to make the right decision whether the nodule is present or not. Did the authors try starting from a position far from the nodule? Is it so unlikely to have P(N)<0.2 after the first sweep if it takes place far from the nodule?5) The authors claim submillimeter accuracy, but this is not supported by the results. Please note that it is even difficult to place the nodule in the soft body with such accuracy. Moreover, I can't see in the results where such accuracy has been achieved.Minor concerns6) Algorithm1: I suggest the inclusion of an escape from the do-while (e.g. a timeout). Line 15: shouldn't dir be "lat" instead of "long"? Line 18: shouldn't dir be "long" instead of "lat"?7) line 221: what does it mean "implemented in real-time"?8) Typos: line 334: remove "performed", line 462: "sweeps", line 488: "cases", line 512: remove "distance"**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  29 Jun 2020Response to the Reviewer 3Thank you for the thorough response to my critique and for adding the constant stiffness case as a comparison.I also stand corrected on the behavior of the stiffness during Bayesian search. I now find the paper quiteconvincing.The authors would like to thank again the reviewer for the valuable comments and feedback that helped us toimprove the clarity of the paper. The authors are happy to read that the previous answers reached the expectationof the reviewer.Response to the Reviewer 4The authors present a new method for 3D localization of nodules in sot tissues based on a variable stiffnessprobe equipped with F/T sensors for kinesthetic perception and a tactile array for tactile perception. The authorsproposed an exploration strategy based on a Bayesian approach to the detection and localization of the nodulethat allows the authors to set the stiffness of the probe and the direction of the sweep to detect and localize thenodule. The paper is well written and clear. However, I have some doubts and concerns that I would like theauthors to clarify.1. The proposed study is based on the experimental results over a simplified setup in which the soft tissueis isotropic and homogenous, and its surface is flat. Since the method relies on fine-tuning of a fewthresholds, how does it generalize to the real case, where the conditions on the soft tissue are not soclean, and the presence of other organs and tissues (even as stiff as bones) affects the sensed force?The aim of this paper is to quantify the role of compliance in the probe to accurately estimate the depthof a stiff formation. Therefore, we idealized the scenario as much as possible to remove the effect ofany other artefacts introduced by the tissue. We even use a spherical hard nodule to remove the effectof uneven geometry of the nodule. We do not claim that there is a specific probe stiffness that gives thebest result irrespective of the probe and the tissue condition. Therefore, what can be generalized is thatprobe stiffness matters in conditioning the shape of the likelihood function (sensor model) in a Bayesianframework to estimate a given feature in the tissue . Therefore, when the tissue is inhomogeneous, multiple force prominencevalues will be present in the force profile. Then a shape filter such as a convolution of a target shape overthe force profile should be developed to extract the target feature. This is beyond the scope of this paper.We added the following text in the discussion to address this concern:In section Discussion, paragraph 5 ”More generally, this paper concludes that the probe stiffness mattersin conditioning the shape of the likelihood function (sensor model) in a Bayesian framework to estimate agiven feature in the tissue . However, when the tissue is inhomogeneous, multiple force prominence values will be present inthe force profile. Then a suitable technique should be adopted to filter a target force prominence shape.One realtime solution is to convolve a target force shape on the measured force data. A data-drivenapproach can be used to build the target shape from a variety of tissue samples with a given feature inthem.”2. I don’t see a great added value in the FEM simulations that the authors propose. First, I would like tohave more details about how contacts were modeled , and about the sizeof the soft tissue and its constraints to a fixed frame Second, if it can have a role in setting the initial valueof the stiffness for a real case experiment, the soft tissue should be modeled more accurately.The FEM simulations were done to understand how the probe stiffness variation leads to changes intissue stress dynamics that cannot be measured otherwise. Such insights are useful to understand whyprobe stiffness variation and resulting differences in the shape of likelihood functions are underpinnedby the coupled dynamics between the probe and the tissue. Also, we have shown that the FE Analysiscan be used to generate the likelihood function. Using this likelihood functions, generated from simulations,comes at a cost on the confidence level of the prediction, but can be useful in the case whereno experimental palpation data is available. Regarding the contact models; unfortunately, COMSOLdocumentation does not specify if bearings or bushes models are used. However, the model is definedwith 2 contact pairs: the fingertip and the phantom. Then the pressure contact calculation between the2 contact pairs is based on an Augmented Lagrangian Method, and the friction between the 2 pairs ismodeled as Coulomb friction. Finally, no rolling resistance is modeled for the contact between the probeand the phantom, which is equivalent to assuming pure sliding. The authors agree that there is still roomfor improvement in the soft tissue model. Yet, for the proposed application, the FE model is accurateenough to perform the 3D localization of the nodules based on the likelihood functions obtained from thesimulation results. To improve the clarity of the model approach and support the interest of the proposedFE simulation, the following modifications have been added to the paper:In section Finite Element Simulation, paragraph 5 ”The contact between the probe and the phantom ismodeled with two surface contact pairs covering the palmar region of the probe and the upper layer of thephantom, respectively. The pressure contact calculation is based on an Augmented Lagrangian Method,and the friction between the 2 contacts is modeled as Coulomb friction (m in Table 1). Finally, no rollingresistance is modeled for the contact between the probe and the phantom assuming pure sliding at theelements level.”In section Discussion, paragraph 2 ”Also, increasing the accuracy of the tissue model or simulatingthe lateral sweeps would require developing a 3D FE model and repeating the simulation for severalshifts . These modifications would increase the computational cost of the simulationsignificantly.”3. My third concern is about parameters. In particular the soft tissue thickness, the nodule Young modulus,and its depth. Since nodule diameter is 16mm, I would expect to have at least 32mm of soft tissue betweenthe nodule and the supporting rigid plane. Even if the applied forces are small, it is a bit surprising thatthe nodule, especially at 2mm depth, does not influence the stress tensor of the surrounding soft tissue.For what regarding the depth, why the maximum selected depth is 8mm?The phantom has been designed with a similar ratio tissue thickness to nodule diameter than the onesused in published related works such as . Also, it can be noticed that in the case of T1 tumorsin the kidney or in the left lobe of the liver, for instance, the ratio between the organ thickness and tumorthickness can be inferior to 2. As the reviewer noticed, the FE simulation shows that with the smallforces applied during the longitudinal sweeps, the stress tensor under the nodule is not influenced evenfor the 2mm deep nodule. This phenomenon comes from the fact that during the palpation sweeps, thedisplacement of the nodule is negligible compared to the displacement of tissue above the nodule. Inother words, the amount of tissue compressed between the probe and the nodule (referred in this articleas the nodule depth) is more significant than the amount of tissue under the nodule. Finally, we decidedto limit the nodule depth to 8mm to reduce the average palpation force level to minimise damage to theprobe. Indeed, as shown in related works, detecting deeper nodules requires deeper indentation and byconsequence, higher forces. Higher forces also lead to faster degradation of the tissue in repeated trials,making it difficult to compare results. Moreover, the lateral sweeps used an array of capacitive tactilesensors, that saturate if an excessive force is applied during lateral sweeps to locate the nodule. Sincethe development of a tactile sensor array for deep tissue exploration is not the focus of this paper, weused a nodule depth that meets all hardware requirements to demonstrate the key scientific phenomenonmentioned above. The discussion generated by the reviewer’s comment have been added in the paper asfollows:In section Soft tissue phantom with nodules, paragraph 1 ”The ratio between the tissue thickness andthe nodule diameter has been chosen accordingly to the one used in related studies in the literature”In section Soft tissue phantom with nodules, paragraph 2 ”In the presented study, we limited the noduledepth to 8mm to reduce the average palpation force level and minimize damage to the probe. Indeed,as shown in related works, detecting deeper nodules requires deeper indentation and by consequence,higher forces. Higher forces also lead to faster degradation of the tissue in repeated trials, making itdifficult to compare results. Moreover, the lateral sweeps used an array of capacitive tactile sensors, thatsaturates if an excessive force is applied to locate the nodule. To avoid saturating the tactile sensor, weused a nodule depth that meets all hardware requirements to demonstrate the role of stiffness variationin conditioning the haptic perception during 3D localization of nodules in soft tissues. ”In section Simulation results, paragraph 2 ”Moreover, with the small forces applied during the longitudinalsweeps, the stress in the material under the nodule is not impacted as much as the stress in thematerial above the nodule. This phenomenon comes from the fact that during the palpation sweeps, thedisplacement of the nodule is small compared to the displacement of tissue above the nodule. This showsthat the probe is more significantly affected by the amount of material above the nodule (the noduledepth) than the amount of material under the nodule.”4. The proposed algorithm seems quite sensitive to the thresholds. In all cases one lateral sweep allows thesystem to make the right decision whether the nodule is present or not. Did the authors try starting froma position far from the nodule? Is it so unlikely to have P(N) < 0:2 after the first sweep if it takes placefar from the nodule?As any control strategy, the proposed algorithm relies on the tuning of some parameters (the thresholdhere). In the sake of clarity, the authors described and discuss the role of each chosen threshold. One ofthe advantages of the proposed threshold is that it is simple for the user to tune them according to theirdesired level of confidence. The authors proposed this threshold because it is the one that gave the bestdetection rate during the validation of the algorithm. The authors tested the algorithm at different startingdistance from the nodule, and the detection was successful independently from the starting point. Thelimitation of this threshold comes more from the risk of false-positive than from missing a nodule due tothe initial position of the probe. Indeed, the algorithm continues to investigate even if the probability ofhaving a nodule is higher or equal 20%, which may result in some case in additional lateral explorationwhen it was not required. The discussion from this question has been added to the paper:In section Evaluation of the algorithm, paragraph 4 ”With the proposed threshold values, the algorithmwas 100% accurate on the estimation of the presence of a nodule with a single lateral sweep. Whena nodule was present, P(N) was over 0.98 after the first sweep, independently from the initial distancebetween the probe and the nodule. When there was no nodule, P(N) was in a range between 0 and 0.18after the first lateral sweep. A trade-off needs to be found while tuning PthN in order to maximize the detection rate but not increasing the number of false-positive detection, which would lead to unnecessary additional lateral explorations.”5. The authors claim submillimeter accuracy, but this is not supported by the results. Please note that it iseven difficult to place the nodule in the soft body with such accuracy. Moreover, I can’t see in the resultswhere such accuracy has been achieved.The authors disagree on this point with the reviewer. Indeed, the Root Mean Square Error (RMSE) forthe eight nodule detections using the presented algorithm  is 0:27mm. The highest absolute error is 0:53mm for the6mm deep nodule with the likelihood function obtained from the FE simulation. Both the RMSE and themaximum absolute error are under 1mm, which support the authors claim on submillimeter accuracy. Theaccuracy of the nodule detection is computed from the estimated depth computed from the probabilitydistribution obtained after the last sweep  as follow:dest = sum(P(d)d)Of course, the computed errors relies on the fact that the position of the nodule tested to generate thelikelihood functions are the ground truth for 2, 4, 6 and 8 mm deep. To better support the author claim,the following modifications have been added to the paper:In section Evaluation of the algorithm, paragraph 7 ”The final depth estimate dest can be computed asfollows:dest = dest = sum(P(d)d)The Root Mean Square Error (RMSE) between the estimated depths and the actual nodule depths for allthe detections presented in Fig 14 and Fig 15A is 0.27mm. The highest absolute error is 0.53mm for the6mm deep nodule with the likelihood function obtained from the FE simulation.”6. Algorithm1: I suggest the inclusion of an escape from the do-while (e.g. a timeout). Line 15: shouldn’tdir be ”lat” instead of ”long”? Line 18: shouldn’t dir be ”long” instead of ”lat”?The authors would like to thanks the authors for his suggestion. Adding a timeout to the algorithm wouldprobably increase the robustness of the algorithm for real-world scenarios. However, for the purpose ofthis paper, the author does not feel the need to add one since the threshold on the information gain alreadyact like a timeout. Indeed when the information gain during a new sweep is too low, the algorithm stopsthe sweeps and returns the estimated position and depth probability distribution. Thank you very muchfor pointing out the typos for line 15 and 18, the directions have corrected.7. line 221: what does it mean ”implemented in real-time”?The authors were using inappropriately ”real-time”, thank you for pointing it out. The sentence has nowbeen rephrased as follows:In section Variable stiffness palpation: the VLM probe, paragraph 4 ”The programs to run the experimentand the algorithm have been implemented using C++.”8. Typos: line 334: remove ”performed”, line 462: ”sweeps”, line 488: ”cases”, line 512: remove ”distance”The authors would like to thank the reviewer once again for pointing these typos out. They have beencorrected.AttachmentResponse to reviewers.pdfSubmitted filename: Click here for additional data file. 27 Jul 2020Conditioned haptic perception for 3D localization of nodules in soft tissue palpation with a variable stiffness probe.PONE-D-20-03370R2Dear Dr. Herzig,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. 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European Journal of Endocrinology (EJE) are publishing an Expression of Concern regarding a recently published article in the journal. The Expression of Concern is to alert readers that an active investigation is underway into an allegation made regarding this article and the data reported within it:The Editor-in-Chief and Editorial Board of the European Journal of Endocrinology 2021 184277–287. (https://doi.org/10.1530/EJE-20-0857)Ye X, Zhao H, Liu J, Lu B, Shao J & Wang J. Efficacy and safety of tripterygium glycosides for active moderate to severe Graves’ ophthalmopathy: a randomised, observer-masked, single-centre trial. The paper will not be published in print until the investigation has been completed.An update to this notice will be published online when the investigation is concluded.