Pub Date : 2019-06-24DOI: 10.1109/ICORR.2019.8779368
Vinh-Quan Nguyen, B. Umberger, F. Sup
The human ankle provides significant positive power during the stance phase of walking, which has resulted in studies focusing on methods to reduce the energetic walking cost by augmenting the ankle with exoskeletons. Recently, a few devices have successfully reduced the metabolic cost of walking by replacing part of the biological ankle plantar flexor torque. Despite these achievements, development of assistive ankle devices remains challenging, partly because the current practice of design and control of powered exoskeletons is highly time and effort consuming, which prevents quickly exploring different design and control parameters. Predictive simulations using musculoskeletal models coupled with robotic devices may facilitate the process of design and control of assistive devices. In this study, we simulate human walking augmented by a powered ankle exoskeleton. The walking problem was formulated as a predictive dynamic optimization in which both the optimal assistive device torque and the gait were solved simultaneously. Cases with exoskeletons assisting one ankle and both ankles were considered. The results showed that the energetic cost of walking could be reduced by 45% with one ankle augmented, and by 52% with both ankles augmented. This study contributes towards the goal of providing optimal assistive torque through external devices and theoretical peak reductions that could be expected from such devices.
{"title":"Predictive Simulation of Human Walking Augmented by a Powered Ankle Exoskeleton","authors":"Vinh-Quan Nguyen, B. Umberger, F. Sup","doi":"10.1109/ICORR.2019.8779368","DOIUrl":"https://doi.org/10.1109/ICORR.2019.8779368","url":null,"abstract":"The human ankle provides significant positive power during the stance phase of walking, which has resulted in studies focusing on methods to reduce the energetic walking cost by augmenting the ankle with exoskeletons. Recently, a few devices have successfully reduced the metabolic cost of walking by replacing part of the biological ankle plantar flexor torque. Despite these achievements, development of assistive ankle devices remains challenging, partly because the current practice of design and control of powered exoskeletons is highly time and effort consuming, which prevents quickly exploring different design and control parameters. Predictive simulations using musculoskeletal models coupled with robotic devices may facilitate the process of design and control of assistive devices. In this study, we simulate human walking augmented by a powered ankle exoskeleton. The walking problem was formulated as a predictive dynamic optimization in which both the optimal assistive device torque and the gait were solved simultaneously. Cases with exoskeletons assisting one ankle and both ankles were considered. The results showed that the energetic cost of walking could be reduced by 45% with one ankle augmented, and by 52% with both ankles augmented. This study contributes towards the goal of providing optimal assistive torque through external devices and theoretical peak reductions that could be expected from such devices.","PeriodicalId":130415,"journal":{"name":"2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132600310","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 : 2019-06-01DOI: 10.1109/ICORR.2019.8779376
R. L. Kæseler, Kasper Leerskov, L. Struijk, K. Dremstrup, M. Jochumsen
An assistive robotic manipulator (ARM) can provide independence and improve the quality of life for patients suffering from tetraplegia. However, to properly control such device to a satisfactory level without any motor functions requires a very high performing brain-computer interface (BCI). Steady-state visual evoked potentials (SSVEP) based BCI are among the best performing. Thus, this study investigates the design of a system for a full workspace control of a 7 degrees of freedom ARM. A SSVEP signal is elicited by observing a visual stimulus flickering at a specific frequency and phase. This study investigates the best combination of unique frequencies and phases to provide a 16-target BCI by testing three different systems off line. Furthermore, a fourth system is developed to investigate the impact of the stimulating monitor refresh rate. Experiments conducted on two subjects suggest that a 16-target BCI created by four unique frequencies and 16-unique phases provide the best performance. Subject 1 reaches a maximum estimated ITR of 235 bits/min while subject 2 reaches 140 bits/min. The findings suggest that the optimal SSVEP stimuli to generate 16 targets are a low number of frequencies and a high number of unique phases. Moreover, the findings do not suggest any need for considering the monitor refresh rate if stimuli are modulated using a sinusoidal signal sampled at the refresh rate.
{"title":"Designing a brain computer interface for control of an assistive robotic manipulator using steady state visually evoked potentials","authors":"R. L. Kæseler, Kasper Leerskov, L. Struijk, K. Dremstrup, M. Jochumsen","doi":"10.1109/ICORR.2019.8779376","DOIUrl":"https://doi.org/10.1109/ICORR.2019.8779376","url":null,"abstract":"An assistive robotic manipulator (ARM) can provide independence and improve the quality of life for patients suffering from tetraplegia. However, to properly control such device to a satisfactory level without any motor functions requires a very high performing brain-computer interface (BCI). Steady-state visual evoked potentials (SSVEP) based BCI are among the best performing. Thus, this study investigates the design of a system for a full workspace control of a 7 degrees of freedom ARM. A SSVEP signal is elicited by observing a visual stimulus flickering at a specific frequency and phase. This study investigates the best combination of unique frequencies and phases to provide a 16-target BCI by testing three different systems off line. Furthermore, a fourth system is developed to investigate the impact of the stimulating monitor refresh rate. Experiments conducted on two subjects suggest that a 16-target BCI created by four unique frequencies and 16-unique phases provide the best performance. Subject 1 reaches a maximum estimated ITR of 235 bits/min while subject 2 reaches 140 bits/min. The findings suggest that the optimal SSVEP stimuli to generate 16 targets are a low number of frequencies and a high number of unique phases. Moreover, the findings do not suggest any need for considering the monitor refresh rate if stimuli are modulated using a sinusoidal signal sampled at the refresh rate.","PeriodicalId":130415,"journal":{"name":"2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115413870","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 : 2019-06-01DOI: 10.1109/ICORR.2019.8779420
F. Bernardoni, Özhan Özen, Karin A. Buetler, L. Marchal-Crespo
Motivation plays a crucial role in motor learning and neurorehabilitation. Participants’ motivation could decline to a point where they may stop training when facing a very difficult task. Conversely, participants may perform well and consider the training boring if the task is too easy. In this paper, we present a combination of a virtual reality environment with different robotic training strategies that modify task functional difficulty to enhance participants’ motivation. We employed a pneumatically driven robotic stepper as a haptic interface. We first evaluated the use of disturbance observers as acceleration controllers to provide high robustness to varying system parameters, unmodeled dynamics and unknown disturbances associated with pneumatic control. The locomotor task to be learned in the virtual reality environment consisted of steering a recumbent bike to follow a desired path by changing the movement frequency of the dominant leg. The motor task was specially designed to engage implicit learning -i.e., learning without conscious recognition of what is learned. A haptic assistance strategy was developed in order to reduce the task functional difficulty during practice. In a feasibility study with eight healthy participants, we found that the haptic assistance provided by the robotic device successfully contributed to improve task performance during training, especially for less skilled participants. Furthermore, we found a negative correlation between participants’ motivation and performance error when training with haptic assistance, suggesting that haptic assistance has a great potential to enhance motivation during motor training.
{"title":"Virtual Reality Environments and Haptic Strategies to Enhance Implicit Learning and Motivation in Robot-Assisted Training","authors":"F. Bernardoni, Özhan Özen, Karin A. Buetler, L. Marchal-Crespo","doi":"10.1109/ICORR.2019.8779420","DOIUrl":"https://doi.org/10.1109/ICORR.2019.8779420","url":null,"abstract":"Motivation plays a crucial role in motor learning and neurorehabilitation. Participants’ motivation could decline to a point where they may stop training when facing a very difficult task. Conversely, participants may perform well and consider the training boring if the task is too easy. In this paper, we present a combination of a virtual reality environment with different robotic training strategies that modify task functional difficulty to enhance participants’ motivation. We employed a pneumatically driven robotic stepper as a haptic interface. We first evaluated the use of disturbance observers as acceleration controllers to provide high robustness to varying system parameters, unmodeled dynamics and unknown disturbances associated with pneumatic control. The locomotor task to be learned in the virtual reality environment consisted of steering a recumbent bike to follow a desired path by changing the movement frequency of the dominant leg. The motor task was specially designed to engage implicit learning -i.e., learning without conscious recognition of what is learned. A haptic assistance strategy was developed in order to reduce the task functional difficulty during practice. In a feasibility study with eight healthy participants, we found that the haptic assistance provided by the robotic device successfully contributed to improve task performance during training, especially for less skilled participants. Furthermore, we found a negative correlation between participants’ motivation and performance error when training with haptic assistance, suggesting that haptic assistance has a great potential to enhance motivation during motor training.","PeriodicalId":130415,"journal":{"name":"2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116777900","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 : 2019-06-01DOI: 10.1109/ICORR.2019.8779428
Ton T. H. Duong, Huanghe Zhang, T. Lynch, D. Zanotto
The trend toward soft wearable robotic systems creates a compelling need for new and reliable sensor systems that do not require a rigid mounting frame. Despite the growing use of inertial measurement units (IMUs) in motion tracking applications, sensor drift and IMU-to-segment misalignment still represent major problems in applications requiring high accuracy. This paper proposes a novel 2-step calibration method which takes advantage of the periodic nature of human locomotion to improve the accuracy of wearable inertial sensors in measuring lower-limb joint angles. Specifically, the method was applied to the determination of the hip joint angles during walking tasks. The accuracy and precision of the calibration method were accessed in a group of N =8 subjects who walked with a custom-designed inertial motion capture system at 85% and 115% of their comfortable pace, using an optical motion capture system as reference. In light of its low computational complexity and good accuracy, the proposed approach shows promise for embedded applications, including closed-loop control of soft wearable robotic systems.
{"title":"Improving the Accuracy of Wearable Sensors for Human Locomotion Tracking Using Phase-Locked Regression Models","authors":"Ton T. H. Duong, Huanghe Zhang, T. Lynch, D. Zanotto","doi":"10.1109/ICORR.2019.8779428","DOIUrl":"https://doi.org/10.1109/ICORR.2019.8779428","url":null,"abstract":"The trend toward soft wearable robotic systems creates a compelling need for new and reliable sensor systems that do not require a rigid mounting frame. Despite the growing use of inertial measurement units (IMUs) in motion tracking applications, sensor drift and IMU-to-segment misalignment still represent major problems in applications requiring high accuracy. This paper proposes a novel 2-step calibration method which takes advantage of the periodic nature of human locomotion to improve the accuracy of wearable inertial sensors in measuring lower-limb joint angles. Specifically, the method was applied to the determination of the hip joint angles during walking tasks. The accuracy and precision of the calibration method were accessed in a group of N =8 subjects who walked with a custom-designed inertial motion capture system at 85% and 115% of their comfortable pace, using an optical motion capture system as reference. In light of its low computational complexity and good accuracy, the proposed approach shows promise for embedded applications, including closed-loop control of soft wearable robotic systems.","PeriodicalId":130415,"journal":{"name":"2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116957004","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 : 2019-06-01DOI: 10.1109/ICORR.2019.8779399
J. Wee, Tracy M. Shank, M. N. Castro, L. Ryan, Joanna Costa, T. Rahman
Introduction: People with arthrogryposis multiplex congenita (AMC) often have muscle weakness in the biceps that makes elbow flexion difficult. An elbow-flexion assist orthosis was designed using the force of springs, combined with a sliding joint, to apply appropriate elbow torque to aid a user in lifting her hand to her mouth. The sliding joint allows an increasing elbow torque despite a decreasing spring force.Methods: The device was prototyped for a user with AMC. An occupational therapist measured the user’s flexion with and without the device. Benchtop torque measurements were also determined and compared with user trials.Results: The assist orthosis applied an increasing torque as the elbow flexed, thereby allowing the subject to reach her mouth for feeding and then extend her elbow to a position of no applied torque. Without the device, the subject had active elbow flexion of 87 degrees. With the device, this flexion increased to 120 degrees.Conclusion: The novel prototype is a lightweight, spring-powered flexion orthosis which can be made relatively easily and is potentially concealed under clothing. It provides the appropriate torque to move the hand against gravity and increases elbow-flexion of the user.
{"title":"Elbow Flexion Assist Orthosis for Arthrogryposis","authors":"J. Wee, Tracy M. Shank, M. N. Castro, L. Ryan, Joanna Costa, T. Rahman","doi":"10.1109/ICORR.2019.8779399","DOIUrl":"https://doi.org/10.1109/ICORR.2019.8779399","url":null,"abstract":"Introduction: People with arthrogryposis multiplex congenita (AMC) often have muscle weakness in the biceps that makes elbow flexion difficult. An elbow-flexion assist orthosis was designed using the force of springs, combined with a sliding joint, to apply appropriate elbow torque to aid a user in lifting her hand to her mouth. The sliding joint allows an increasing elbow torque despite a decreasing spring force.Methods: The device was prototyped for a user with AMC. An occupational therapist measured the user’s flexion with and without the device. Benchtop torque measurements were also determined and compared with user trials.Results: The assist orthosis applied an increasing torque as the elbow flexed, thereby allowing the subject to reach her mouth for feeding and then extend her elbow to a position of no applied torque. Without the device, the subject had active elbow flexion of 87 degrees. With the device, this flexion increased to 120 degrees.Conclusion: The novel prototype is a lightweight, spring-powered flexion orthosis which can be made relatively easily and is potentially concealed under clothing. It provides the appropriate torque to move the hand against gravity and increases elbow-flexion of the user.","PeriodicalId":130415,"journal":{"name":"2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126854192","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 : 2019-06-01DOI: 10.1109/ICORR.2019.8779495
Sunny Amatya, Amir Salimi Lafmejani, Souvik Poddar, Saivimal Sridar, T. Sugar, Panagiotis Polygerinos
This paper investigates the design of a robotic fabric-based, soft ankle module capable of generating 50% of the human ankle stiffness, in plantarflexion and dorsiflexion for walking. Kinematics, dynamics, and anatomy of the human ankle joint are studied to set the functional requirements of the module. The design of the compliant and lightweight soft ankle module uses fabric-based inflatable actuator arrays for actuation. Models for the human ankle stiffness, as well as a data-driven model of soft ankle module is presented. A high-level stiffness controller utilizing the human ankle and soft ankle model with a low-level pressure controller is implemented. We demonstrate the ability to closely follow the ankle stiffness trajectory using soft ankle module.
{"title":"Design, Development, and Control of a Fabric-Based Soft Ankle Module to Mimic Human Ankle Stiffness","authors":"Sunny Amatya, Amir Salimi Lafmejani, Souvik Poddar, Saivimal Sridar, T. Sugar, Panagiotis Polygerinos","doi":"10.1109/ICORR.2019.8779495","DOIUrl":"https://doi.org/10.1109/ICORR.2019.8779495","url":null,"abstract":"This paper investigates the design of a robotic fabric-based, soft ankle module capable of generating 50% of the human ankle stiffness, in plantarflexion and dorsiflexion for walking. Kinematics, dynamics, and anatomy of the human ankle joint are studied to set the functional requirements of the module. The design of the compliant and lightweight soft ankle module uses fabric-based inflatable actuator arrays for actuation. Models for the human ankle stiffness, as well as a data-driven model of soft ankle module is presented. A high-level stiffness controller utilizing the human ankle and soft ankle model with a low-level pressure controller is implemented. We demonstrate the ability to closely follow the ankle stiffness trajectory using soft ankle module.","PeriodicalId":130415,"journal":{"name":"2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115257383","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 : 2019-06-01DOI: 10.1109/ICORR.2019.8779406
Daniel Chizhik, B. Hejrati
This paper provides a proof of concept for an actuating system comprised of a linear actuator and a spring steel strip that enables bidirectional articulation of a finger by transmitting the force directly to the finger tip. This proposed design can be distinguished from other orthosis designs, which use rigid linkages or cables with DC motors or fluidic systems for force generation and transmission. We designed an experimental setup with a 3D-printed model finger to mimic a passive human finger on which the actuation system was mounted and tested. The finger was positioned such that it would curl upward to lift various masses when articulated by the actuating system to demonstrate the system’s force generation capability. We tested two linear actuators and two steel strips, using a wide range of masses to determine which would be the most suitable components for our design. We analyzed motion profiles, joint angles, force generation, and actuator stroke velocities during various experimental trials. Our results demonstrate that our actuating system is capable of generating sufficient forces and motions with an adequate response time to be used in the design of a hand orthosis for grasping/releasing assistance. From our tests, a prototype was designed with three linear actuators positioned on the dorsal side of the hand and actuated the thumb, index, and middle fingers. Future work will include sensor integration and performance evaluation of the orthosis.
{"title":"A Lightweight Linear Actuating System for Finger Articulation: A Proof-of-Concept Study","authors":"Daniel Chizhik, B. Hejrati","doi":"10.1109/ICORR.2019.8779406","DOIUrl":"https://doi.org/10.1109/ICORR.2019.8779406","url":null,"abstract":"This paper provides a proof of concept for an actuating system comprised of a linear actuator and a spring steel strip that enables bidirectional articulation of a finger by transmitting the force directly to the finger tip. This proposed design can be distinguished from other orthosis designs, which use rigid linkages or cables with DC motors or fluidic systems for force generation and transmission. We designed an experimental setup with a 3D-printed model finger to mimic a passive human finger on which the actuation system was mounted and tested. The finger was positioned such that it would curl upward to lift various masses when articulated by the actuating system to demonstrate the system’s force generation capability. We tested two linear actuators and two steel strips, using a wide range of masses to determine which would be the most suitable components for our design. We analyzed motion profiles, joint angles, force generation, and actuator stroke velocities during various experimental trials. Our results demonstrate that our actuating system is capable of generating sufficient forces and motions with an adequate response time to be used in the design of a hand orthosis for grasping/releasing assistance. From our tests, a prototype was designed with three linear actuators positioned on the dorsal side of the hand and actuated the thumb, index, and middle fingers. Future work will include sensor integration and performance evaluation of the orthosis.","PeriodicalId":130415,"journal":{"name":"2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114605277","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 : 2019-06-01DOI: 10.1109/ICORR.2019.8779478
K. Heiwolt, Claudio Zito, Markus Nowak, Claudio Castellini, R. Stolkin
Myoelectric control systems for assistive devices are still unreliable. The user’s input signals can become unstable over time due to e.g. fatigue, electrode displacement, or sweat. Hence, such controllers need to be constantly updated and heavily rely on user feedback. In this paper, we present an automatic failure detection method which learns when plausible predictions become unreliable and model updates are necessary. Our key insight is to enhance the control system with a set of generative models that learn sensible behaviour for a desired task from human demonstration. We illustrate our approach on a grasping scenario in Virtual Reality, in which the user is asked to grasp a bottle on a table. From demonstration our model learns the reach-to-grasp motion from a resting position to two grasps (power grasp and tridigital grasp) and how to predict the most adequate grasp from local context, e.g. tridigital grasp on the bottle cap or around the bottleneck. By measuring the error between new grasp attempts and the model prediction, the system can effectively detect which input commands do not reflect the user’s intention. We evaluated our model in two cases: i) with both position and rotation information of the wrist pose, and ii) with only rotational information. Our results show that our approach detects statistically highly significant differences in error distributions with p<0.001 between successful and failed grasp attempts in both cases.
{"title":"Automatic Detection of Myocontrol Failures Based upon Situational Context Information","authors":"K. Heiwolt, Claudio Zito, Markus Nowak, Claudio Castellini, R. Stolkin","doi":"10.1109/ICORR.2019.8779478","DOIUrl":"https://doi.org/10.1109/ICORR.2019.8779478","url":null,"abstract":"Myoelectric control systems for assistive devices are still unreliable. The user’s input signals can become unstable over time due to e.g. fatigue, electrode displacement, or sweat. Hence, such controllers need to be constantly updated and heavily rely on user feedback. In this paper, we present an automatic failure detection method which learns when plausible predictions become unreliable and model updates are necessary. Our key insight is to enhance the control system with a set of generative models that learn sensible behaviour for a desired task from human demonstration. We illustrate our approach on a grasping scenario in Virtual Reality, in which the user is asked to grasp a bottle on a table. From demonstration our model learns the reach-to-grasp motion from a resting position to two grasps (power grasp and tridigital grasp) and how to predict the most adequate grasp from local context, e.g. tridigital grasp on the bottle cap or around the bottleneck. By measuring the error between new grasp attempts and the model prediction, the system can effectively detect which input commands do not reflect the user’s intention. We evaluated our model in two cases: i) with both position and rotation information of the wrist pose, and ii) with only rotational information. Our results show that our approach detects statistically highly significant differences in error distributions with p<0.001 between successful and failed grasp attempts in both cases.","PeriodicalId":130415,"journal":{"name":"2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116833107","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 : 2019-06-01DOI: 10.1109/ICORR.2019.8779515
M. Khalili, Tianxin Tao, Ruolan Ye, Shuyong Xie, Huancheng Yang, H. V. D. Loos, J. Borisoff
There has been a growth in the design and use of power assist devices for manual wheelchairs (MWCs) to alleviate the physical load of MWC use. A pushrim-activated power-assisted wheel (PAPAW) is an example of a power assist device that replaces the conventional wheel of a MWC. Although the use of PAPAWs provides some benefits to MWC users, it can also cause difficulties in maneuvering the wheelchair. In this research, we examined the characteristics of wheelchair propulsion when using manual and powered wheels. We used the left and right wheels’ angular velocity to calculate the linear and angular velocity of the wheelchair. Results of this analysis revealed that the powered wheel’s controller is not optimally designed to reflect the intentions of a wheelchair user. To address some of the challenges with coordinating the pushes on PAPAWs, we proposed the design of a user-intention detection framework. We used the kinematic data of MWC experiments and tested six supervised learning algorithms to classify one of four movements: “not moving”, “moving straight forward”, “turning left”, and “turning right”. We found that all the classification algorithms determined the type of movement with high accuracy and low computation time. The proposed intention detection framework can be used in the design of learning-based controllers for PAPAWs that take into account the individualized characteristics of wheelchair users. Such a system may improve the experience of PAPAW users.
{"title":"Towards the Development of a Learning-Based Intention Classification Framework for Pushrim-Activated Power-Assisted Wheelchairs","authors":"M. Khalili, Tianxin Tao, Ruolan Ye, Shuyong Xie, Huancheng Yang, H. V. D. Loos, J. Borisoff","doi":"10.1109/ICORR.2019.8779515","DOIUrl":"https://doi.org/10.1109/ICORR.2019.8779515","url":null,"abstract":"There has been a growth in the design and use of power assist devices for manual wheelchairs (MWCs) to alleviate the physical load of MWC use. A pushrim-activated power-assisted wheel (PAPAW) is an example of a power assist device that replaces the conventional wheel of a MWC. Although the use of PAPAWs provides some benefits to MWC users, it can also cause difficulties in maneuvering the wheelchair. In this research, we examined the characteristics of wheelchair propulsion when using manual and powered wheels. We used the left and right wheels’ angular velocity to calculate the linear and angular velocity of the wheelchair. Results of this analysis revealed that the powered wheel’s controller is not optimally designed to reflect the intentions of a wheelchair user. To address some of the challenges with coordinating the pushes on PAPAWs, we proposed the design of a user-intention detection framework. We used the kinematic data of MWC experiments and tested six supervised learning algorithms to classify one of four movements: “not moving”, “moving straight forward”, “turning left”, and “turning right”. We found that all the classification algorithms determined the type of movement with high accuracy and low computation time. The proposed intention detection framework can be used in the design of learning-based controllers for PAPAWs that take into account the individualized characteristics of wheelchair users. Such a system may improve the experience of PAPAW users.","PeriodicalId":130415,"journal":{"name":"2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR)","volume":"420 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126709040","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 : 2019-06-01DOI: 10.1109/ICORR.2019.8779555
Wen Wang, Rochelle J. Mendonca, Konrad Paul Kording, Mikael Avery, M. Johnson
Task-oriented therapy consists of three stages: demonstration, observation and assistance. While demonstration using robots has been extensively studied, the other two stages rarely involve robots. This paper focuses on the transition between observation and assistance. More specifically, we tackle the robot’s decision making problem of whether to assist a patient or not based on the observation. The proposed method is to train a discrete tunnel shape 3-D decision boundary through correct demonstration to classify motions. Additional conditions such as slow progress, self correction and overshot motions are taken into account of the decision making. Preliminary experiments have been performed on BAXTER robot for a cup reaching task. The BAXTER robot is programmed to react according to the decision boundary. It assists the patient when the patient’s hand position is determined by the proposed algorithm to be unacceptable. Multiple cases including correct motion, continuous assistance, overshot, misaim and slow progress are tested. Results have confirmed the feasibility of the proposed method, which can reduce the current shortage of physical rehabilitation therapists.
{"title":"Towards Data-Driven Autonomous Robot-Assisted Physical Rehabilitation Therapy","authors":"Wen Wang, Rochelle J. Mendonca, Konrad Paul Kording, Mikael Avery, M. Johnson","doi":"10.1109/ICORR.2019.8779555","DOIUrl":"https://doi.org/10.1109/ICORR.2019.8779555","url":null,"abstract":"Task-oriented therapy consists of three stages: demonstration, observation and assistance. While demonstration using robots has been extensively studied, the other two stages rarely involve robots. This paper focuses on the transition between observation and assistance. More specifically, we tackle the robot’s decision making problem of whether to assist a patient or not based on the observation. The proposed method is to train a discrete tunnel shape 3-D decision boundary through correct demonstration to classify motions. Additional conditions such as slow progress, self correction and overshot motions are taken into account of the decision making. Preliminary experiments have been performed on BAXTER robot for a cup reaching task. The BAXTER robot is programmed to react according to the decision boundary. It assists the patient when the patient’s hand position is determined by the proposed algorithm to be unacceptable. Multiple cases including correct motion, continuous assistance, overshot, misaim and slow progress are tested. Results have confirmed the feasibility of the proposed method, which can reduce the current shortage of physical rehabilitation therapists.","PeriodicalId":130415,"journal":{"name":"2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129125741","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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