Pub Date : 2018-10-09DOI: 10.1109/BIOROB.2018.8487635
P. Arena, L. Patané, Dario Sanalitro, A. Vitanza
In this paper an insect-inspired body size learning algorithm is adopted in a humanoid robot and a control system, mainly developed with spiking neurons, is proposed. It implements an evaluation of distances by using the typical parallax method performed by different insect species, such as Drosophila melanogaster. A Darwin-OP robot was used as testbed to demonstrate the potential application of the learning method on a humanoid structure. The robot, equipped with a hand extension, was free to move in an environment to discover objects. As consequence, it was able to learn, using an operant conditioning, which objects can be reached, via the estimation of their distance on varying the length of the equipped tool. The learning scheme was tested both in a dynamical simulation environment and with the Darwin-OP robot.
{"title":"Insect-Inspired Body Size Learning Model on a Humanoid Robot","authors":"P. Arena, L. Patané, Dario Sanalitro, A. Vitanza","doi":"10.1109/BIOROB.2018.8487635","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487635","url":null,"abstract":"In this paper an insect-inspired body size learning algorithm is adopted in a humanoid robot and a control system, mainly developed with spiking neurons, is proposed. It implements an evaluation of distances by using the typical parallax method performed by different insect species, such as Drosophila melanogaster. A Darwin-OP robot was used as testbed to demonstrate the potential application of the learning method on a humanoid structure. The robot, equipped with a hand extension, was free to move in an environment to discover objects. As consequence, it was able to learn, using an operant conditioning, which objects can be reached, via the estimation of their distance on varying the length of the equipped tool. The learning scheme was tested both in a dynamical simulation environment and with the Darwin-OP robot.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128672907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/BIOROB.2018.8487213
M. Eslamy, A. Schilling
In this paper, the goal is to develop a high level controller for active prosthetic feet that can continuously estimate the ankle motion based on the shank motion. The proposed controller does not require speed determination, gait percent identification, input data manipulation, look-up tables or switching rules. To do this, the Gaussian process (GP) regression is used. The performance of the controller has been tested for walking speed of 0.6, 0.9, 1.2, 1.4 and 1.6 m/s. The results showed that the controller had lower estimation quality when input was only shank angular velocity or shank angle. However, the aggregated angular velocity and angle input resulted in high output estimation quality. Furthermore, for each speed, the estimation quality was more acceptable when the controller was trained for it. Accordingly, when the high level controller was tested without previous training, the estimation quality was less acceptable.
{"title":"A Conceptual High Level Controller to Walk with Active Foot Prostheses/Orthoses","authors":"M. Eslamy, A. Schilling","doi":"10.1109/BIOROB.2018.8487213","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487213","url":null,"abstract":"In this paper, the goal is to develop a high level controller for active prosthetic feet that can continuously estimate the ankle motion based on the shank motion. The proposed controller does not require speed determination, gait percent identification, input data manipulation, look-up tables or switching rules. To do this, the Gaussian process (GP) regression is used. The performance of the controller has been tested for walking speed of 0.6, 0.9, 1.2, 1.4 and 1.6 m/s. The results showed that the controller had lower estimation quality when input was only shank angular velocity or shank angle. However, the aggregated angular velocity and angle input resulted in high output estimation quality. Furthermore, for each speed, the estimation quality was more acceptable when the controller was trained for it. Accordingly, when the high level controller was tested without previous training, the estimation quality was less acceptable.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127550244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/BIOROB.2018.8487185
C. Pierella, A. Sciacchitano, Ali Farshchiansadegh, M. Casadio, F. Mussa-Ivaldi
The human machine interface (HMI) refers to a paradigm in which the users interact with external devices through an interface that mediates the information exchanges between them and the device. In this work we focused on a HMI that exploits signals derived from the body to control the machine: the body machine interface (BMI). It is reasonable to assume that signals derived from body movements, electromyography activity, as well as brain activity, have a non-linear nature. This implies that linear algorithms cannot exploit all the information contained in these signals. In this work we proposed a new BMI that maps electromyographic signals into the control of a computer cursor by using a new non-linear dimensionality reduction algorithm based on autoassociative neural network. We tested the system on a group of ten healthy subjects that, controlling this cursor, performed a reaching task. We compared the result with the performance of an age and gender matched group of healthy subjects that solved the same task using a BMI based on a linear mapping. The analysis of the performance indices showed a substantial difference between the two groups. In particular, the performance of the people using the non-linear mapping were better in terms of time, accuracy and smoothness of the cursor's movement. This study opened the way to the exploitation of non-linear dimensionality reduction algorithms to pursue a new and effective clinical approach for body-machine interfaces.
{"title":"Linear vs Non-Linear Mapping in a Body Machine Interface Based on Electromyographic Signals","authors":"C. Pierella, A. Sciacchitano, Ali Farshchiansadegh, M. Casadio, F. Mussa-Ivaldi","doi":"10.1109/BIOROB.2018.8487185","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487185","url":null,"abstract":"The human machine interface (HMI) refers to a paradigm in which the users interact with external devices through an interface that mediates the information exchanges between them and the device. In this work we focused on a HMI that exploits signals derived from the body to control the machine: the body machine interface (BMI). It is reasonable to assume that signals derived from body movements, electromyography activity, as well as brain activity, have a non-linear nature. This implies that linear algorithms cannot exploit all the information contained in these signals. In this work we proposed a new BMI that maps electromyographic signals into the control of a computer cursor by using a new non-linear dimensionality reduction algorithm based on autoassociative neural network. We tested the system on a group of ten healthy subjects that, controlling this cursor, performed a reaching task. We compared the result with the performance of an age and gender matched group of healthy subjects that solved the same task using a BMI based on a linear mapping. The analysis of the performance indices showed a substantial difference between the two groups. In particular, the performance of the people using the non-linear mapping were better in terms of time, accuracy and smoothness of the cursor's movement. This study opened the way to the exploitation of non-linear dimensionality reduction algorithms to pursue a new and effective clinical approach for body-machine interfaces.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125058559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/BIOROB.2018.8488065
S. Dalley, C. Hartigan, C. Kandilakis, R. Farris
A new exoskeleton control method has been developed to enable continuous joint motion and thereby increase walking speed and speed control in exoskeleton enabled gait. To characterize walking speed and speed control using this controller, a new assessment tool has also been proposed, the 40 Meter Walk Test (40MWT). This paper presents the controller, describes its implementation in a commercially-available exoskeleton, and provides clinical results obtained using the 40MWT with five individuals having spinal cord injury. Results include maximum walking speeds, which varied by subject from 0.48m/s to 0.78 m/s, and speed ranges (max speed - min speed), which varied from 0.33 m/s to 0.55 m/s. As these Ranges were associated with an average Speed Control Factor (a new outcome measure associated with the 40MWT) of 0.43, the results demonstrate that subjects were able to access speeds which spanned several functional categories and were able to control speed in a highly linear fashion while doing so.
{"title":"Increased Walking Speed and Speed Control in Exoskeleton Enabled Gait","authors":"S. Dalley, C. Hartigan, C. Kandilakis, R. Farris","doi":"10.1109/BIOROB.2018.8488065","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8488065","url":null,"abstract":"A new exoskeleton control method has been developed to enable continuous joint motion and thereby increase walking speed and speed control in exoskeleton enabled gait. To characterize walking speed and speed control using this controller, a new assessment tool has also been proposed, the 40 Meter Walk Test (40MWT). This paper presents the controller, describes its implementation in a commercially-available exoskeleton, and provides clinical results obtained using the 40MWT with five individuals having spinal cord injury. Results include maximum walking speeds, which varied by subject from 0.48m/s to 0.78 m/s, and speed ranges (max speed - min speed), which varied from 0.33 m/s to 0.55 m/s. As these Ranges were associated with an average Speed Control Factor (a new outcome measure associated with the 40MWT) of 0.43, the results demonstrate that subjects were able to access speeds which spanned several functional categories and were able to control speed in a highly linear fashion while doing so.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126026192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/BIOROB.2018.8487665
E. Noce, A. Ciancio, L. Zollo
Ahstract- The Spike Sorting is an algorithm that allows extracting peculiar features from the neural signals and uniquely identifying the neurons that contributed to the generation of the recording. The literature shows that researches on this topic do not pay the due attention to the optimization process of the algorithm parameters. Here, an optimization process based on the multimodality approach is presented. It was aimed to select the best set of features to increase the accuracy of classification of neural signals. Simulated recordings were used to validate the approach. We demonstrated that triplets of optimized features were able to discriminate among 10 classes with an accuracy of ~95%; on the other hand, a fixed triplet reached an accuracy of ~90%. Moreover, accuracy decay with respect to the classes was slower and surprisingly more predictable.
{"title":"Accuracy Optimization of the Spike Sorting Algorithm for Classification of Neural Signals","authors":"E. Noce, A. Ciancio, L. Zollo","doi":"10.1109/BIOROB.2018.8487665","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487665","url":null,"abstract":"Ahstract- The Spike Sorting is an algorithm that allows extracting peculiar features from the neural signals and uniquely identifying the neurons that contributed to the generation of the recording. The literature shows that researches on this topic do not pay the due attention to the optimization process of the algorithm parameters. Here, an optimization process based on the multimodality approach is presented. It was aimed to select the best set of features to increase the accuracy of classification of neural signals. Simulated recordings were used to validate the approach. We demonstrated that triplets of optimized features were able to discriminate among 10 classes with an accuracy of ~95%; on the other hand, a fixed triplet reached an accuracy of ~90%. Moreover, accuracy decay with respect to the classes was slower and surprisingly more predictable.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"64 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114423481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/BIOROB.2018.8487884
Z. Rahmati, S. Behzadipour, A. Schouten, G. Taghizadeh
Studies have shown that balance and mobility in people with Parkinson's disease (PD) can improve through rehabilitation interventions. However, until now no quantitative method investigated how these patients improve their balance control. In this study, a single inverted pendulum model with PID controller was used to describe the improvement of forty PD patients after a 12-session therapy program, and to compare their balance with twenty healthy subjects. The Center of Pressure (COP) data were recorded in seven sensory conditions - on rigid and foam surface, each with eyes open and closed, and with visual disturbance; and stance on rigid surface with attached vibrator to the Achilles tendons. From COP data four Stabilogram Diffusion Function (SDF) measures were extracted. In order to find the appropriate model parameters (three control parameters and a noise gain) from the SDF measures, first model simulations were performed to tune an artificial neural network (ANN) which relates the SDF measures to the PID parameters, and second the trained ANN was used to find the suitable PID model parameters from the experimentally recorded SDF measures. Statistical analysis revealed that patients had lower control parameters and noise gain than healthy subjects; confirming reduced control ability and sensory information in PDs. Balance rehabilitation improved the patients' clinical scores, which is reflected in the increased control parameters (particularly in foam tasks), and noise gain (in tasks on rigid surface). The presented method provides a good and sensitive measure to describe functional balance and mobility in PD.
{"title":"A Postural Control Model to Assess the Improvement of Balance Rehabilitation in Parkinson's Disease","authors":"Z. Rahmati, S. Behzadipour, A. Schouten, G. Taghizadeh","doi":"10.1109/BIOROB.2018.8487884","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487884","url":null,"abstract":"Studies have shown that balance and mobility in people with Parkinson's disease (PD) can improve through rehabilitation interventions. However, until now no quantitative method investigated how these patients improve their balance control. In this study, a single inverted pendulum model with PID controller was used to describe the improvement of forty PD patients after a 12-session therapy program, and to compare their balance with twenty healthy subjects. The Center of Pressure (COP) data were recorded in seven sensory conditions - on rigid and foam surface, each with eyes open and closed, and with visual disturbance; and stance on rigid surface with attached vibrator to the Achilles tendons. From COP data four Stabilogram Diffusion Function (SDF) measures were extracted. In order to find the appropriate model parameters (three control parameters and a noise gain) from the SDF measures, first model simulations were performed to tune an artificial neural network (ANN) which relates the SDF measures to the PID parameters, and second the trained ANN was used to find the suitable PID model parameters from the experimentally recorded SDF measures. Statistical analysis revealed that patients had lower control parameters and noise gain than healthy subjects; confirming reduced control ability and sensory information in PDs. Balance rehabilitation improved the patients' clinical scores, which is reflected in the increased control parameters (particularly in foam tasks), and noise gain (in tasks on rigid surface). The presented method provides a good and sensitive measure to describe functional balance and mobility in PD.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122206272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/BIOROB.2018.8488130
T. G. Thuruthel, M. Manti, E. Falotico, M. Cianchetti, C. Laschi
Soft robotic systems are primarily characterized by their low stiffness properties. However, for these high dimension nonlinear systems, it becomes increasingly difficult to define and estimate stiffness properties. This paper presents a methodology to estimate the dominant compliance of a soft robotic manipulator using only motion information. We show how this information can be used for input shaping to suppress unwanted vibrations during point to point motion. Furthermore the methodology can be used to assess manipulator design and stiffening mechanisms.
{"title":"Induced Vibrations of Soft Robotic Manipulators for Controller Design and Stiffness Estimation","authors":"T. G. Thuruthel, M. Manti, E. Falotico, M. Cianchetti, C. Laschi","doi":"10.1109/BIOROB.2018.8488130","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8488130","url":null,"abstract":"Soft robotic systems are primarily characterized by their low stiffness properties. However, for these high dimension nonlinear systems, it becomes increasingly difficult to define and estimate stiffness properties. This paper presents a methodology to estimate the dominant compliance of a soft robotic manipulator using only motion information. We show how this information can be used for input shaping to suppress unwanted vibrations during point to point motion. Furthermore the methodology can be used to assess manipulator design and stiffening mechanisms.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117263742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/BIOROB.2018.8487932
Dylan J. A. Brenneis, M. R. Dawson, Glyn Murgatroyd, J. Carey, P. Pilarski
Lack of adequate wrist control in prostheses forces people with upper limb amputations to use compensatory movements that eventually result in overuse injuries. This is partly because conventional control of myoelectric wrists involves switching between directly controlling the wrist and fixing the wrist relative to the forearm. We propose that by implementing a wrist that is able to maintain the hand's orientation relative to the ground reference frame, here termed a self-adjusting wrist, users may see benefits in terms of both compensatory movements and ease of control. In this design study, we describe a simple initial implementation of a self-adjusting wrist. We then introduce and compare five control methods for the system. These methods were tested with six able-bodied participants who used a desk-mounted robotic arm to perform an object transfer and manipulation task. Quantitative and qualitative analyses coupled with user feedback suggest that a self-adjusting wrist may reduce task completion time and number of control interactions, and increase user satisfaction compared to conventional switching-based control. Our results indicate that use of a momentary switch to toggle a robotic hand's orientation between being fixed to the ground reference frame and being either fixed to the forearm reference frame or employing direct wrist control may be the best choice for a self-adjusting wrist. More broadly, by considering a wrist that automatically and continually orients itself to the user and their environment, this work contributes insight about how prostheses and other assistive robotic technology may intelligently adapt in real time to support the daily-life tasks faced by their users.
{"title":"Initial Investigation of a Self-Adjusting Wrist Control System to Maintain Prosthesis Terminal Device Orientation Relative to the Ground Reference Frame","authors":"Dylan J. A. Brenneis, M. R. Dawson, Glyn Murgatroyd, J. Carey, P. Pilarski","doi":"10.1109/BIOROB.2018.8487932","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487932","url":null,"abstract":"Lack of adequate wrist control in prostheses forces people with upper limb amputations to use compensatory movements that eventually result in overuse injuries. This is partly because conventional control of myoelectric wrists involves switching between directly controlling the wrist and fixing the wrist relative to the forearm. We propose that by implementing a wrist that is able to maintain the hand's orientation relative to the ground reference frame, here termed a self-adjusting wrist, users may see benefits in terms of both compensatory movements and ease of control. In this design study, we describe a simple initial implementation of a self-adjusting wrist. We then introduce and compare five control methods for the system. These methods were tested with six able-bodied participants who used a desk-mounted robotic arm to perform an object transfer and manipulation task. Quantitative and qualitative analyses coupled with user feedback suggest that a self-adjusting wrist may reduce task completion time and number of control interactions, and increase user satisfaction compared to conventional switching-based control. Our results indicate that use of a momentary switch to toggle a robotic hand's orientation between being fixed to the ground reference frame and being either fixed to the forearm reference frame or employing direct wrist control may be the best choice for a self-adjusting wrist. More broadly, by considering a wrist that automatically and continually orients itself to the user and their environment, this work contributes insight about how prostheses and other assistive robotic technology may intelligently adapt in real time to support the daily-life tasks faced by their users.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129021435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/BIOROB.2018.8488125
F. Bailly, Justin Carpentier, B. Pinet, P. Souéres, B. Watier
This work aims at experimentally identifying a new mechanical descriptor of human locomotion and demonstrating that it can be exploited for the generation of multi-contact motions for humanoids. For this purpose, an experimental setup was built on which five different experiments were carried out by 15 human volunteers. Experimental results show that the distance between the center of mass and the so-called central axis of the external contact wrench significantly varies as a function of locomotion phases and environmental constraints. This finding is combined with a theoretical reasoning in mechanics in order to exhibit how this distance is linked to the whole body's angular acceleration and thus constitutes an interesting parameter to control. Finally, we illustrate the relevance of this result for humanoid robot motion generation by embedding the minimization of the distance between the center of mass and the central axis of the external contact wrench in an optimal control formulation in order to generate multi-contact locomotion in simulation.
{"title":"A Mechanical Descriptor of Human Locomotion and its Application to Multi-Contact Walking in Humanoids","authors":"F. Bailly, Justin Carpentier, B. Pinet, P. Souéres, B. Watier","doi":"10.1109/BIOROB.2018.8488125","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8488125","url":null,"abstract":"This work aims at experimentally identifying a new mechanical descriptor of human locomotion and demonstrating that it can be exploited for the generation of multi-contact motions for humanoids. For this purpose, an experimental setup was built on which five different experiments were carried out by 15 human volunteers. Experimental results show that the distance between the center of mass and the so-called central axis of the external contact wrench significantly varies as a function of locomotion phases and environmental constraints. This finding is combined with a theoretical reasoning in mechanics in order to exhibit how this distance is linked to the whole body's angular acceleration and thus constitutes an interesting parameter to control. Finally, we illustrate the relevance of this result for humanoid robot motion generation by embedding the minimization of the distance between the center of mass and the central axis of the external contact wrench in an optimal control formulation in order to generate multi-contact locomotion in simulation.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129248604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/BIOROB.2018.8488075
Max K. Shepherd, Alejandro F. Azocar, M. Major, Elliott J. Rouse
Most prosthetic feet behave like springs, and their stiffness affects many important facets of amputee gait. Despite the importance of prosthesis stiffness, the ability of amputees to sense stiffness changes-that is, distinguish between more or less stiff feet-is unknown. This perceptual resolution has implications for the methodology and overall significance of selecting the optimal foot stiffness during prescription. In this experiment, we used a custom, variable-stiffness ankle prosthesis to make small adjustments to stiffness in between steps, and below-knee amputees were asked to identify whether the ankle became more or less stiff. We determined that the average difference threshold of stiffness was 8%, meaning that subjects could correctly identify an 8% change in stiffness 75% of the time. This high sensitivity underscores the importance of optimizing prosthesis stiffness on an individual basis, and suggests a shift is needed in the characterization of commercial feet and the use of stiffness variation during the prescription process.
{"title":"The Difference Threshold of Ankle-Foot Prosthesis Stiffness for Persons with Transtibial Amputation","authors":"Max K. Shepherd, Alejandro F. Azocar, M. Major, Elliott J. Rouse","doi":"10.1109/BIOROB.2018.8488075","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8488075","url":null,"abstract":"Most prosthetic feet behave like springs, and their stiffness affects many important facets of amputee gait. Despite the importance of prosthesis stiffness, the ability of amputees to sense stiffness changes-that is, distinguish between more or less stiff feet-is unknown. This perceptual resolution has implications for the methodology and overall significance of selecting the optimal foot stiffness during prescription. In this experiment, we used a custom, variable-stiffness ankle prosthesis to make small adjustments to stiffness in between steps, and below-knee amputees were asked to identify whether the ankle became more or less stiff. We determined that the average difference threshold of stiffness was 8%, meaning that subjects could correctly identify an 8% change in stiffness 75% of the time. This high sensitivity underscores the importance of optimizing prosthesis stiffness on an individual basis, and suggests a shift is needed in the characterization of commercial feet and the use of stiffness variation during the prescription process.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130567018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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