Pub Date : 2018-08-01DOI: 10.1109/BIOROB.2018.8487228
Kaustab Pal, Sakyajit Bhattacharya, S. Dey, A. Mukherjee
Various machine learning models have so far been used for training robots to perform different tasks in the context of Industry 4.0. However, following the advances in neuroscience, new models are being pursued which are biologically inspired. One such model is the Hierarchical Temporal Memory (HTM) which models a neural network by drawing inspirations from human neocortex. This model is however a theoretical one, though its performance in multiple scenarios is worth taking note of. In this paper, the authors model the deviation in learning for HTM when applied to a robotic path learning scenario and investigated different parameters which influence the learning.
{"title":"Modelling HTM Learning and Prediction for Robotic Path-Learning","authors":"Kaustab Pal, Sakyajit Bhattacharya, S. Dey, A. Mukherjee","doi":"10.1109/BIOROB.2018.8487228","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487228","url":null,"abstract":"Various machine learning models have so far been used for training robots to perform different tasks in the context of Industry 4.0. However, following the advances in neuroscience, new models are being pursued which are biologically inspired. One such model is the Hierarchical Temporal Memory (HTM) which models a neural network by drawing inspirations from human neocortex. This model is however a theoretical one, though its performance in multiple scenarios is worth taking note of. In this paper, the authors model the deviation in learning for HTM when applied to a robotic path learning scenario and investigated different parameters which influence the learning.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"1 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":"122195583","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.2018.8487984
{"title":"Biorob2018","authors":"","doi":"10.1109/biorob.2018.8487984","DOIUrl":"https://doi.org/10.1109/biorob.2018.8487984","url":null,"abstract":"","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"9 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":"125860732","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.2018.8487892
M. Farooq, S. Ko
Surgical robotics have helped surgeons for more than two decades using sophisticated and operation-based devices. Different kinds of surgical robots have been developed for specific purposes. In recent times, stiffness changing robots are in the spotlight due to their necessity. The interaction force on neighboring tissues during navigation to surgical target can be reduced owing to the low stiffness and the stiffness can be increased to provide high payloads as it reaches the surgical site. In this work, a 2-DOF soft robot with stiffness changing capability is presented for tumor removal in neurosurgery under MRI-guidance. A floating fixed-point approach is used that changes the physical length of the manipulator to decrease deflection and increase stiffness. Experimental results confirmed that the stiffness could be varied more than three and a half times than the initial value. The robot can bend 37.46° in right and left and 38.56° in up and down direction. The current version of the robot is joystick-operated and can be controlled manually. Finally, the manipulator is composed of MR-compatible materials allowing it to be used in MR-guided interventions.
{"title":"A Stiffness-Changing Continuum Robotic Manipulator for Possible Use in MRI-Guided Neurosurgical Interventions","authors":"M. Farooq, S. Ko","doi":"10.1109/BIOROB.2018.8487892","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487892","url":null,"abstract":"Surgical robotics have helped surgeons for more than two decades using sophisticated and operation-based devices. Different kinds of surgical robots have been developed for specific purposes. In recent times, stiffness changing robots are in the spotlight due to their necessity. The interaction force on neighboring tissues during navigation to surgical target can be reduced owing to the low stiffness and the stiffness can be increased to provide high payloads as it reaches the surgical site. In this work, a 2-DOF soft robot with stiffness changing capability is presented for tumor removal in neurosurgery under MRI-guidance. A floating fixed-point approach is used that changes the physical length of the manipulator to decrease deflection and increase stiffness. Experimental results confirmed that the stiffness could be varied more than three and a half times than the initial value. The robot can bend 37.46° in right and left and 38.56° in up and down direction. The current version of the robot is joystick-operated and can be controlled manually. Finally, the manipulator is composed of MR-compatible materials allowing it to be used in MR-guided interventions.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"42 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":"123608220","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.2018.8487737
Keya Ghonasgi, Jiyeon Kang, S. Agrawal
In a previous study, a Tethered Pelvic Assist Device (TPAD) was used to successfully retrain crouch gait of children with Cerebral Palsy by applying a downward force on the pelvis during walking on a treadmill. While the results of this study were promising, an important issue was translating these results to special needs children with crouch gait using simpler alternative procedures. This motivates the present study to compare the biomechanical differences in walking under two conditions: (i) the TPAD applies a pure downward force on the pelvis using tethers, and (ii) a weighted pelvic belt is used to apply the same downward force on the pelvis. In the second case the weight belt also increases the mass at the pelvis. Ten healthy subjects performed two separate experiments while walking on an instrumented treadmill. The whole-body kinematics was recorded using a motion capture system and the ground reaction forces were measured by force plates embedded in the treadmill. We found no significant difference in the actual gait parameters of healthy subjects when the downwards force, equivalent to 15% body weight, applied by the TPAD was replaced by a weighted pelvic belt of 15% body weight. However, the estimated maximum ankle torque, predicted by an inverted pendulum mathematical model, during the single support phase showed a higher increase during walking with the weight belt when compared to a pure downward force. This suggests that the weight belt, due to its simplicity, may be a better medium to translate the results of TPAD in children with cerebral palsy who have a crouch gait.
{"title":"Walking with a Weighted Pelvic Belt or with an Equivalent Pure Downward Force on the Pelvis: Are These Different?","authors":"Keya Ghonasgi, Jiyeon Kang, S. Agrawal","doi":"10.1109/BIOROB.2018.8487737","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487737","url":null,"abstract":"In a previous study, a Tethered Pelvic Assist Device (TPAD) was used to successfully retrain crouch gait of children with Cerebral Palsy by applying a downward force on the pelvis during walking on a treadmill. While the results of this study were promising, an important issue was translating these results to special needs children with crouch gait using simpler alternative procedures. This motivates the present study to compare the biomechanical differences in walking under two conditions: (i) the TPAD applies a pure downward force on the pelvis using tethers, and (ii) a weighted pelvic belt is used to apply the same downward force on the pelvis. In the second case the weight belt also increases the mass at the pelvis. Ten healthy subjects performed two separate experiments while walking on an instrumented treadmill. The whole-body kinematics was recorded using a motion capture system and the ground reaction forces were measured by force plates embedded in the treadmill. We found no significant difference in the actual gait parameters of healthy subjects when the downwards force, equivalent to 15% body weight, applied by the TPAD was replaced by a weighted pelvic belt of 15% body weight. However, the estimated maximum ankle torque, predicted by an inverted pendulum mathematical model, during the single support phase showed a higher increase during walking with the weight belt when compared to a pure downward force. This suggests that the weight belt, due to its simplicity, may be a better medium to translate the results of TPAD in children with cerebral palsy who have a crouch gait.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"493 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":"117023188","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.2018.8487894
Itzel Jared Rodríguez Martínez, F. Clemente, Gunter Kanitz, A. Mannini, A. Sabatini, C. Cipriani
Ahstract- The force applied with a prosthetic device is fundamental for the correct handling of objects in daily tasks. However, it is also a factor that normally gets relegated to a secondary plane, as researchers mainly focus on decoding the users intent in terms of movements to be performed. Continuous estimates of the grasp force from the electromyographic (EMG) signals were proposed in the past. As motor actions are preplanned in humans, we hypothesized that it would be possible to decode the intended grasp force from the transient state of the EMG signal. We tested this hypothesis by using features extracted from surface HD-EMG recordings from forearm muscles, classified using artificial neural networks. Data from 6 able-bodied subjects were collected. They were trained and tested at segments of 120 ms with 20 ms overlap, starting 1 s before and ending 0.5 s after the detection of the onset with different subsets of channels. The results obtained showed that the transient phase contains information about the target grasp force, achieving predictions of 2.62 % MVC average absolute errors within 430 ms from the onset of the EMG.
{"title":"Grasp Force Estimation from HD-EMG Recordings with Channel Selection Using Elastic Nets: Preliminary Study","authors":"Itzel Jared Rodríguez Martínez, F. Clemente, Gunter Kanitz, A. Mannini, A. Sabatini, C. Cipriani","doi":"10.1109/BIOROB.2018.8487894","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487894","url":null,"abstract":"Ahstract- The force applied with a prosthetic device is fundamental for the correct handling of objects in daily tasks. However, it is also a factor that normally gets relegated to a secondary plane, as researchers mainly focus on decoding the users intent in terms of movements to be performed. Continuous estimates of the grasp force from the electromyographic (EMG) signals were proposed in the past. As motor actions are preplanned in humans, we hypothesized that it would be possible to decode the intended grasp force from the transient state of the EMG signal. We tested this hypothesis by using features extracted from surface HD-EMG recordings from forearm muscles, classified using artificial neural networks. Data from 6 able-bodied subjects were collected. They were trained and tested at segments of 120 ms with 20 ms overlap, starting 1 s before and ending 0.5 s after the detection of the onset with different subsets of channels. The results obtained showed that the transient phase contains information about the target grasp force, achieving predictions of 2.62 % MVC average absolute errors within 430 ms from the onset of the EMG.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"24 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":"121135972","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.2018.8487677
Yi-Tsen Pan, Zachary Lamb, Jennifer Macievich, Katherine A. Strausser
Robotic exoskeletons have been used in physical therapy clinics for several years to help individuals with neurological impairments stand and walk. Exoskeletons, including EksoGT™, are used as rehabilitation tools to assist in gait re-training for those with the potential to restore some walking function. For patients with impaired proprioceptive systems, the exoskeleton can compensate for impaired sensory signals, thereby assisting in balance and gait training; however, not much information is provided to the patients in real-time about their balance. In this paper, we present a haptic device that can provide real-time balance feedback during standing in an EksoGT™. Sensory information is conveyed via a vibrotactile belt worn around the chest. Three subjects with spinal cord injuries (SCI) and eight able-bodied subjects were recruited to test the prototype and evaluate the efficacy of the additional biofeedback in balance training. Results show reduced postural sway in quiet standing tasks among both groups when vibrotactile feedback was enabled. Additional vibrotactile cues also assisted in guiding the subjects towards the target positions and kept the subjects within a safe region of standing balance. All subjects found the additional sensory feedback intuitive and they could control their postures actively. This preliminary study has demonstrated the potential therapeutic/in-home application of the additional haptic feedback in improving balance control for SCI patients.
{"title":"A Vibrotactile Feedback Device for Balance Rehabilitation in the EksoGT™ Robotic Exoskeleton","authors":"Yi-Tsen Pan, Zachary Lamb, Jennifer Macievich, Katherine A. Strausser","doi":"10.1109/BIOROB.2018.8487677","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487677","url":null,"abstract":"Robotic exoskeletons have been used in physical therapy clinics for several years to help individuals with neurological impairments stand and walk. Exoskeletons, including EksoGT™, are used as rehabilitation tools to assist in gait re-training for those with the potential to restore some walking function. For patients with impaired proprioceptive systems, the exoskeleton can compensate for impaired sensory signals, thereby assisting in balance and gait training; however, not much information is provided to the patients in real-time about their balance. In this paper, we present a haptic device that can provide real-time balance feedback during standing in an EksoGT™. Sensory information is conveyed via a vibrotactile belt worn around the chest. Three subjects with spinal cord injuries (SCI) and eight able-bodied subjects were recruited to test the prototype and evaluate the efficacy of the additional biofeedback in balance training. Results show reduced postural sway in quiet standing tasks among both groups when vibrotactile feedback was enabled. Additional vibrotactile cues also assisted in guiding the subjects towards the target positions and kept the subjects within a safe region of standing balance. All subjects found the additional sensory feedback intuitive and they could control their postures actively. This preliminary study has demonstrated the potential therapeutic/in-home application of the additional haptic feedback in improving balance control for SCI patients.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"52 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":"121544042","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.2018.8488060
Trivoramai Jiralerspong, Kelvin H. L. Heung, R. Tong, Zheng Li
For assistive and rehabilitation purposes, this paper presents a novel soft robotic glove that supports the thumb in performing the abduction, adduction, flexion, and extension movements. In addition, using the combination of the abduction and flexion movements, the glove is able to assist the user in performing the thumb opposition motion. The feature of the proposed design is to combine two types of fiber-reinforced actuators, i.e. the rotary and the bending actuators. The rotary actuator facilitates the thumb abduction and adduction, and the bending actuator controls the finger flexion and extension. To quantify the actuators, the angle and the force output from both actuators are measured. Experimental results show that an angle of 90° and a force of 0.8 N could be obtained by the bending actuator at 150 kPa. On the other hand, an angle of 43° and a force of 0.8 N could be achieved by the rotary actuator at 50 kPa. Furthermore, these actuators were implemented onto a polyester glove and tested on a healthy subject. The results demonstrated that the soft robotic glove could produce the abduction and adduction movements of the thumb, as well as the flexion and extension movements of the fingers. This shows that the proposed soft robotic glove could provide a full range of motion to the fingers.
{"title":"A Novel Soft Robotic Glove for Daily Life Assistance","authors":"Trivoramai Jiralerspong, Kelvin H. L. Heung, R. Tong, Zheng Li","doi":"10.1109/BIOROB.2018.8488060","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8488060","url":null,"abstract":"For assistive and rehabilitation purposes, this paper presents a novel soft robotic glove that supports the thumb in performing the abduction, adduction, flexion, and extension movements. In addition, using the combination of the abduction and flexion movements, the glove is able to assist the user in performing the thumb opposition motion. The feature of the proposed design is to combine two types of fiber-reinforced actuators, i.e. the rotary and the bending actuators. The rotary actuator facilitates the thumb abduction and adduction, and the bending actuator controls the finger flexion and extension. To quantify the actuators, the angle and the force output from both actuators are measured. Experimental results show that an angle of 90° and a force of 0.8 N could be obtained by the bending actuator at 150 kPa. On the other hand, an angle of 43° and a force of 0.8 N could be achieved by the rotary actuator at 50 kPa. Furthermore, these actuators were implemented onto a polyester glove and tested on a healthy subject. The results demonstrated that the soft robotic glove could produce the abduction and adduction movements of the thumb, as well as the flexion and extension movements of the fingers. This shows that the proposed soft robotic glove could provide a full range of motion to the fingers.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"136 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":"122758753","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.2018.8487215
A. Ejupi, A. Ferrone, C. Menon
Goal: Textile-based stretch sensors are a novel and innovative alternative to traditional wearable sensors with applications in many different fields including robotics, virtual reality and healthcare. However, due to their non-linear properties it can be challenging to obtain accurate information. The goal of this study was to investigate if machine learning can be applied to obtain more accurate measurements. Methods: In a tensile test using a linear stage setup, data were collected from two commercial available stretch sensors (Adafruit and Image SI) and one self-fabricated sensor (Menrva research group at Simon Fraser University, Canada). For each sensor, one hour of consecutive stretches in both a trapezoidal and sinusoidal input pattern were collected. We identified a set of features, trained three commonly used machine learning algorithms, and compared their performance in estimating the amount of stretch. To demonstrate the feasibility of our approach in real life, we tested our setup in two human applications. First, we attached a stretch sensor to the human chest to estimate the expansion of the rib cage during breathing. Second, we evaluated the performance in estimating the ankle position with a sensor attached to the foot. Results: In the tensile test, Support Vector Regression performed best with an average accuracy $(mathbf{R}^{2})$ of 0.98 (0.01) and mean absolute error of 0.18 (0.06) mm across all input patterns and sensors. The accuracy was significantly $(mathbf{p} < pmb{0.01})$. higher than the performance of a traditional linear model. An accuracy $(mathbf{R}^{2})$ of 0.91 (0.04) with a mean absolute error of 3.08 (0.38) mm has been achieved in estimating the expansion of the chest. Similarly, an accuracy (R2) of 0.90 (0.04) with a mean absolute error of 2.90 (0.61) degree has been achieved in estimating the ankle position. Conclusion: We demonstrate that machine learning can be used to obtain accurate stretch information from textile-based stretch sensors.
{"title":"Quantification of Textile-Based Stretch Sensors Using Machine Learning: An Exploratory Study","authors":"A. Ejupi, A. Ferrone, C. Menon","doi":"10.1109/BIOROB.2018.8487215","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487215","url":null,"abstract":"Goal: Textile-based stretch sensors are a novel and innovative alternative to traditional wearable sensors with applications in many different fields including robotics, virtual reality and healthcare. However, due to their non-linear properties it can be challenging to obtain accurate information. The goal of this study was to investigate if machine learning can be applied to obtain more accurate measurements. Methods: In a tensile test using a linear stage setup, data were collected from two commercial available stretch sensors (Adafruit and Image SI) and one self-fabricated sensor (Menrva research group at Simon Fraser University, Canada). For each sensor, one hour of consecutive stretches in both a trapezoidal and sinusoidal input pattern were collected. We identified a set of features, trained three commonly used machine learning algorithms, and compared their performance in estimating the amount of stretch. To demonstrate the feasibility of our approach in real life, we tested our setup in two human applications. First, we attached a stretch sensor to the human chest to estimate the expansion of the rib cage during breathing. Second, we evaluated the performance in estimating the ankle position with a sensor attached to the foot. Results: In the tensile test, Support Vector Regression performed best with an average accuracy $(mathbf{R}^{2})$ of 0.98 (0.01) and mean absolute error of 0.18 (0.06) mm across all input patterns and sensors. The accuracy was significantly $(mathbf{p} < pmb{0.01})$. higher than the performance of a traditional linear model. An accuracy $(mathbf{R}^{2})$ of 0.91 (0.04) with a mean absolute error of 3.08 (0.38) mm has been achieved in estimating the expansion of the chest. Similarly, an accuracy (R2) of 0.90 (0.04) with a mean absolute error of 2.90 (0.61) degree has been achieved in estimating the ankle position. Conclusion: We demonstrate that machine learning can be used to obtain accurate stretch information from textile-based stretch sensors.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"112 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":"123306741","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.2018.8487888
Xiaojun Sun, Fumihito Sugai, K. Okada, M. Inaba
In this paper, design and control of a novel robotic prosthetic knee and ankle system is presented. Robotic prosthetic knee and ankle system consists of a robotic knee prosthesis and a robotic ankle prosthesis, connected by a prosthetic pylon, adjusting shank length and alignment between knee and ankle. We present a novel mechanism incorporating a series elastic actuator and crank mechanism, which is applied to transform linear motion of series elastic actuator to rotary motion of knee joint and ankle. The crank mechanism contributes a variable transmission ratio of each joint. This feature could uniquely give the knee both: the torque necessary to assist with standing up from a chair and the speed necessary to swing the leg forward during walking. Because of variable transmission ratio, ankle joint torque is increasing while ankle angle is flexed from plantar flexion to dorsiflexion, whose feature has a similar increase trend with human's ankle joint torque-angle relationship. Robotic knee prostheses and robotic ankle prostheses are mechanically separable integrated system, including actuation, electronics and control respectively and they could be used independently. In order to coordinate movement of knee and ankle as one system in this paper, The knee is controlled as a master and ankle is a slave and they are connected by electrical cable to send control signal from master to slave. Prototype has been built and a preliminary experiment has been implemented with a transfemoral amputee.
{"title":"Design and Control of a Novel Robotic Knee-Ankle Prosthesis System","authors":"Xiaojun Sun, Fumihito Sugai, K. Okada, M. Inaba","doi":"10.1109/BIOROB.2018.8487888","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487888","url":null,"abstract":"In this paper, design and control of a novel robotic prosthetic knee and ankle system is presented. Robotic prosthetic knee and ankle system consists of a robotic knee prosthesis and a robotic ankle prosthesis, connected by a prosthetic pylon, adjusting shank length and alignment between knee and ankle. We present a novel mechanism incorporating a series elastic actuator and crank mechanism, which is applied to transform linear motion of series elastic actuator to rotary motion of knee joint and ankle. The crank mechanism contributes a variable transmission ratio of each joint. This feature could uniquely give the knee both: the torque necessary to assist with standing up from a chair and the speed necessary to swing the leg forward during walking. Because of variable transmission ratio, ankle joint torque is increasing while ankle angle is flexed from plantar flexion to dorsiflexion, whose feature has a similar increase trend with human's ankle joint torque-angle relationship. Robotic knee prostheses and robotic ankle prostheses are mechanically separable integrated system, including actuation, electronics and control respectively and they could be used independently. In order to coordinate movement of knee and ankle as one system in this paper, The knee is controlled as a master and ankle is a slave and they are connected by electrical cable to send control signal from master to slave. Prototype has been built and a preliminary experiment has been implemented with a transfemoral amputee.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"1 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":"130680386","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.2018.8487193
Kyle J. Kaveny, A. M. Simon, T. Lenzi, Suzanne B. Finucane, Emily A. Seyforth, Graci Finco, Kasen Culler, L. Hargrove
Powered knee and ankle prostheses can potentially improve the mobility and function of their users, but determining the best way to control the prosthesis is difficult. Controllers that vary knee swing speed have been shown to restore gait symmetry with a powered knee and ankle prosthesis. This study's goal was to combine an existing variable speed knee swing controller with an existing impedance stance controller to determine if comfortable walking with variable cadence can be achieved and if the control method transitions would be noticeable to the user. The knee swing trajectory and duration was varied based on user walking speed as a function of the previous stance phase duration. Four individuals with unilateral transfemoral amputations were fit with a powered knee and ankle prosthesis. After 30–45 minutes of practice walking with the variable knee swing controller, subjects performed a variable speed walk test, a steady state walk test, and a 10-meter walk test. A GAITRite mat was used to collect spatial and temporal walking parameters during the 10-meter walk test. Results showed that subjects could control prosthetic knee swing duration and kinematics by modifying their walking speed. Subjects were able to comfortably transition between speeds and achieve mean (SD) comfortable and fast speeds of 1.10 (0.05) and 1.51 (0.05) m/s, respectively for a 10-meter walk test. This study's contribution is to show that a variable speed knee controller can be combined with an impedance-based controller while maintaining the functionality of both controllers and to provide gait mechanics for amputee powered gait that can be used towards future studies of controller development and prosthesis design.
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