Pub Date : 2007-06-13DOI: 10.1109/ICORR.2007.4428528
A. Khanicheh, D. Mintzopoulos, B. Weinberg, A. Tzika, C. Mavroidis
This paper presents the design, fabrication and testing of a novel, one degree of freedom (DOF) magnetic resonance compatible smart hand interfaced rehabilitation device (MR_CHIROD v.2), which may be used in brain magnetic resonance (MR) imaging during handgrip rehabilitation. The device consists of three major subsystems: a) an ERF based resistive element; b) handles and c) two sensors, one optical encoder and one force sensor, to measure the patient induced motion and force. MR_CHIROD v.2 is designed to resist up to 50% of the maximum level of gripping force of a human hand and be controlled in real time. Our results demonstrate that the MR environment does not interfere with the performance of the MR_CHIROD v.2, and, reciprocally, its use does not cause fMR image artifacts. The results are encouraging in jointly using MR_CHIROD v.2 and brain MR imaging to study motor performance and assess rehabilitation after neurological injuries such as stroke.
{"title":"MR_CHIROD v.2: A fMRI Compatible Mechatronic Hand Rehabilitation Device","authors":"A. Khanicheh, D. Mintzopoulos, B. Weinberg, A. Tzika, C. Mavroidis","doi":"10.1109/ICORR.2007.4428528","DOIUrl":"https://doi.org/10.1109/ICORR.2007.4428528","url":null,"abstract":"This paper presents the design, fabrication and testing of a novel, one degree of freedom (DOF) magnetic resonance compatible smart hand interfaced rehabilitation device (MR_CHIROD v.2), which may be used in brain magnetic resonance (MR) imaging during handgrip rehabilitation. The device consists of three major subsystems: a) an ERF based resistive element; b) handles and c) two sensors, one optical encoder and one force sensor, to measure the patient induced motion and force. MR_CHIROD v.2 is designed to resist up to 50% of the maximum level of gripping force of a human hand and be controlled in real time. Our results demonstrate that the MR environment does not interfere with the performance of the MR_CHIROD v.2, and, reciprocally, its use does not cause fMR image artifacts. The results are encouraging in jointly using MR_CHIROD v.2 and brain MR imaging to study motor performance and assess rehabilitation after neurological injuries such as stroke.","PeriodicalId":197465,"journal":{"name":"2007 IEEE 10th International Conference on Rehabilitation Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132526818","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 : 2007-06-13DOI: 10.1109/ICORR.2007.4428442
J. Furusho, T. Kikuchi, K. Oda, Y. Ohyama, T. Morita, N. Shichi, Ying Jin, A. Inoue
Rehabilitation for upper limbs is important for aged people, stroked patients and so on. In recent years, the needs for rehabilitation support systems are increasing, which use robot technology and virtual reality technology. Applying these technologies make efficient rehabilitation possible. But there is no rehabilitation support system that has 6-DOF for upper limbs including wrists besides application software of physical therapy. We developed a 6-DOF-rehabilitation support system for upper limbs including wrists, named "Robotherapist". Furthermore we develop new application software for clinical training and evaluation on the basis of physical therapy. Therefore Robotherapist make more effective rehabilitation possible. This paper presents the mechanism of Robotherapist and its software on physical therapy.
{"title":"A 6-DOF Rehabilitation Support System for Upper Limbs including Wrists \"Robotherapist\" with Physical Therapy","authors":"J. Furusho, T. Kikuchi, K. Oda, Y. Ohyama, T. Morita, N. Shichi, Ying Jin, A. Inoue","doi":"10.1109/ICORR.2007.4428442","DOIUrl":"https://doi.org/10.1109/ICORR.2007.4428442","url":null,"abstract":"Rehabilitation for upper limbs is important for aged people, stroked patients and so on. In recent years, the needs for rehabilitation support systems are increasing, which use robot technology and virtual reality technology. Applying these technologies make efficient rehabilitation possible. But there is no rehabilitation support system that has 6-DOF for upper limbs including wrists besides application software of physical therapy. We developed a 6-DOF-rehabilitation support system for upper limbs including wrists, named \"Robotherapist\". Furthermore we develop new application software for clinical training and evaluation on the basis of physical therapy. Therefore Robotherapist make more effective rehabilitation possible. This paper presents the mechanism of Robotherapist and its software on physical therapy.","PeriodicalId":197465,"journal":{"name":"2007 IEEE 10th International Conference on Rehabilitation Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131117815","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 : 2007-06-13DOI: 10.1109/ICORR.2007.4428415
H. Zabaleta, M. Bureau, G. Eizmendi, E. Olaiz, J. Medina, M. Perez
The prevalence of neurological disorders such as stroke, spinal cord injury and traumatic brain injury is increasing quickly in the industrialised societies. Although the benefit of the use of technology in rehabilitation and neurorehabilitation programs is proved, the presence of mechatronic systems is still very low. This paper proposes a new lower limb exoskeleton for functional rehabilitation in persons with neurological pathologies. Since potential users have very reduced mobility even to start common daily movements, the control of the exoskeleton has to be intention based The estimation of the intention of the user is based on hip and knee angle, and the EMG signal is monitored for intention detection, control and neurofeedback aims. A novel approach of a whole mechatronic system has been done in order to approach functional rehabilitation in patients with neurological disorders and stroke. The EMG to force conversion in paraplegic patients is also described.
{"title":"Exoskeleton design for functional rehabilitation in patients with neurological disorders and stroke","authors":"H. Zabaleta, M. Bureau, G. Eizmendi, E. Olaiz, J. Medina, M. Perez","doi":"10.1109/ICORR.2007.4428415","DOIUrl":"https://doi.org/10.1109/ICORR.2007.4428415","url":null,"abstract":"The prevalence of neurological disorders such as stroke, spinal cord injury and traumatic brain injury is increasing quickly in the industrialised societies. Although the benefit of the use of technology in rehabilitation and neurorehabilitation programs is proved, the presence of mechatronic systems is still very low. This paper proposes a new lower limb exoskeleton for functional rehabilitation in persons with neurological pathologies. Since potential users have very reduced mobility even to start common daily movements, the control of the exoskeleton has to be intention based The estimation of the intention of the user is based on hip and knee angle, and the EMG signal is monitored for intention detection, control and neurofeedback aims. A novel approach of a whole mechatronic system has been done in order to approach functional rehabilitation in patients with neurological disorders and stroke. The EMG to force conversion in paraplegic patients is also described.","PeriodicalId":197465,"journal":{"name":"2007 IEEE 10th International Conference on Rehabilitation Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114703860","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 : 2007-06-13DOI: 10.1109/ICORR.2007.4428498
O. Lambercy, L. Dovat, V. Johnson, B. Salman, S. Wong, R. Gassert, T. Milner, T. C. Leong, E. Burdet
This paper presents the evaluation of a new two degree-of-freedom robotic interface, and the development of exercises to train movements and force control of wrist and hand. The Haptic Knob has two actuated parallelogram structures with a knob at the output, to interact with the fingers in a way to simulate grasping/releasing, in combination with pronation/supination movements of the forearm. Motivating game-like exercises have been designed according to a functional approach, where fundamental hand function required in activities of daily living (ADL) can be trained, while the device provides assistive or resistive forces. Preliminary testing has been performed with healthy subjects and three chronic stroke patients. Subjects found the exercises to be comfortable, and the robotic interface offers adequate range of motion and forces. A study with a group of chronic stroke patients will be conducted during the next months to determine the potential benefit of a therapy using our robotic equipment.
{"title":"Development of a Robot-Assisted Rehabilitation Therapy to train Hand Function for Activities of Daily Living","authors":"O. Lambercy, L. Dovat, V. Johnson, B. Salman, S. Wong, R. Gassert, T. Milner, T. C. Leong, E. Burdet","doi":"10.1109/ICORR.2007.4428498","DOIUrl":"https://doi.org/10.1109/ICORR.2007.4428498","url":null,"abstract":"This paper presents the evaluation of a new two degree-of-freedom robotic interface, and the development of exercises to train movements and force control of wrist and hand. The Haptic Knob has two actuated parallelogram structures with a knob at the output, to interact with the fingers in a way to simulate grasping/releasing, in combination with pronation/supination movements of the forearm. Motivating game-like exercises have been designed according to a functional approach, where fundamental hand function required in activities of daily living (ADL) can be trained, while the device provides assistive or resistive forces. Preliminary testing has been performed with healthy subjects and three chronic stroke patients. Subjects found the exercises to be comfortable, and the robotic interface offers adequate range of motion and forces. A study with a group of chronic stroke patients will be conducted during the next months to determine the potential benefit of a therapy using our robotic equipment.","PeriodicalId":197465,"journal":{"name":"2007 IEEE 10th International Conference on Rehabilitation Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123903228","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 : 2007-06-13DOI: 10.1109/ICORR.2007.4428529
M. D. Ellis, T. Sukal, T. Demott, J. Dewald
Abnormal upper extremity coordination can be expressed in the form of atypical muscle synergies that result in limited and stereotypic movement patterns when an individual with hemiparetic stroke attempts to support the arm against gravity. These movement constraints are functionally disabling. We have developed and are employing the Arm Coordination Training 3D Device (ACT3D). This report documents evidence supporting the efficacy of an impairment-specific dynamic reaching protocol for a group of individuals with chronic stroke and was taken as part of a larger randomized controlled trial (RCT). Six individuals with stroke were trained to actively support their arm while reaching to various outward targets over a period of eight weeks. The intervention was progressed by increasing the level of required active limb support or gravitational loading experienced by the participant during reaching repetitions as performance improved. Reaching work area was evaluated pre-and post-intervention for ten different support levels along with a battery of clinical assessments performed by a blinded physical therapist. There was a significant effect of session (pre vs. post) with an increase in reaching work area and a concurrent significant improvement on some of the clinical impairment assessments. This data suggests that specifically targeting the abnormal joint torque coupling impairment is an effective strategy for improving reaching work area following hemiparetic stroke. Following the completion of this study physical therapists will have new evidence supporting the application of an intervention employing rehabilitation robotics for individuals with chronic and severe hemiparetic stroke.
{"title":"ACT3D exercise targets gravity-induced discoordination and improves reaching work area in individuals with stroke","authors":"M. D. Ellis, T. Sukal, T. Demott, J. Dewald","doi":"10.1109/ICORR.2007.4428529","DOIUrl":"https://doi.org/10.1109/ICORR.2007.4428529","url":null,"abstract":"Abnormal upper extremity coordination can be expressed in the form of atypical muscle synergies that result in limited and stereotypic movement patterns when an individual with hemiparetic stroke attempts to support the arm against gravity. These movement constraints are functionally disabling. We have developed and are employing the Arm Coordination Training 3D Device (ACT3D). This report documents evidence supporting the efficacy of an impairment-specific dynamic reaching protocol for a group of individuals with chronic stroke and was taken as part of a larger randomized controlled trial (RCT). Six individuals with stroke were trained to actively support their arm while reaching to various outward targets over a period of eight weeks. The intervention was progressed by increasing the level of required active limb support or gravitational loading experienced by the participant during reaching repetitions as performance improved. Reaching work area was evaluated pre-and post-intervention for ten different support levels along with a battery of clinical assessments performed by a blinded physical therapist. There was a significant effect of session (pre vs. post) with an increase in reaching work area and a concurrent significant improvement on some of the clinical impairment assessments. This data suggests that specifically targeting the abnormal joint torque coupling impairment is an effective strategy for improving reaching work area following hemiparetic stroke. Following the completion of this study physical therapists will have new evidence supporting the application of an intervention employing rehabilitation robotics for individuals with chronic and severe hemiparetic stroke.","PeriodicalId":197465,"journal":{"name":"2007 IEEE 10th International Conference on Rehabilitation Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114960629","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 : 2007-06-13DOI: 10.1109/ICORR.2007.4428480
J. Ward, S. Balasubramanian, T. Sugar, Jiping He
With over 600,000 people each year surviving a stroke, it has become the leading cause of serious long-term disability in the United States [1, 2, 3]. Studies have proven that through repetitive task training, neural circuits can be re-mapped thus increasing the mobility of the patient [4, 5, 6, 7, 8]. This fuels the emerging field of rehabilitation robotics. As technology advances new therapy robots are developed that are increasingly compliant and captivating to use. This paper examines the robotic gait trainer (RGT) developed in the human machine integration laboratory at Arizona State University. The RGT is a tripod mechanism, where the patient's leg is the fixed link, controlled on a Mat-lab and Simulink platform. An eight week case study was conducted with a 22 year old female stroke survivor. Subjective feedback, robot performance and the patient's key performance indicators examined throughout the study are analyzed.
{"title":"Robotic Gait Trainer Reliability and Stroke Patient Case Study","authors":"J. Ward, S. Balasubramanian, T. Sugar, Jiping He","doi":"10.1109/ICORR.2007.4428480","DOIUrl":"https://doi.org/10.1109/ICORR.2007.4428480","url":null,"abstract":"With over 600,000 people each year surviving a stroke, it has become the leading cause of serious long-term disability in the United States [1, 2, 3]. Studies have proven that through repetitive task training, neural circuits can be re-mapped thus increasing the mobility of the patient [4, 5, 6, 7, 8]. This fuels the emerging field of rehabilitation robotics. As technology advances new therapy robots are developed that are increasingly compliant and captivating to use. This paper examines the robotic gait trainer (RGT) developed in the human machine integration laboratory at Arizona State University. The RGT is a tripod mechanism, where the patient's leg is the fixed link, controlled on a Mat-lab and Simulink platform. An eight week case study was conducted with a 22 year old female stroke survivor. Subjective feedback, robot performance and the patient's key performance indicators examined throughout the study are analyzed.","PeriodicalId":197465,"journal":{"name":"2007 IEEE 10th International Conference on Rehabilitation Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123031113","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 : 2007-06-13DOI: 10.1109/ICORR.2007.4428505
T. Luth, D. Ojdanic, O. Friman, O. Prenzel, A. Graser
In this work, a connection between a semi-autonomous rehabilitation robotic system and Brain-Computer Interfaces (BCI) is described This paper focuses on a system for user intervention in low-level movement control of an assistive robotic arm. The rehabilitation robotic system allows tetra-plegics to control the system with high-level commands (e.g., "grab the bottle"), and then to intervene in the execution of the task, if they see that something is going wrong. In such a case, the user gets the opportunity to continue the task with a low-level control of the robot arm. A system for such a control on a low abstraction level by a Brain-Computer Interface based on P300 and steady-state visual evoked potentials (SSVEP) will be described in this work.
{"title":"Low level control in a semi-autonomous rehabilitation robotic system via a Brain-Computer Interface","authors":"T. Luth, D. Ojdanic, O. Friman, O. Prenzel, A. Graser","doi":"10.1109/ICORR.2007.4428505","DOIUrl":"https://doi.org/10.1109/ICORR.2007.4428505","url":null,"abstract":"In this work, a connection between a semi-autonomous rehabilitation robotic system and Brain-Computer Interfaces (BCI) is described This paper focuses on a system for user intervention in low-level movement control of an assistive robotic arm. The rehabilitation robotic system allows tetra-plegics to control the system with high-level commands (e.g., \"grab the bottle\"), and then to intervene in the execution of the task, if they see that something is going wrong. In such a case, the user gets the opportunity to continue the task with a low-level control of the robot arm. A system for such a control on a low abstraction level by a Brain-Computer Interface based on P300 and steady-state visual evoked potentials (SSVEP) will be described in this work.","PeriodicalId":197465,"journal":{"name":"2007 IEEE 10th International Conference on Rehabilitation Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115334476","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 : 2007-06-13DOI: 10.1109/ICORR.2007.4428561
O. Ma, Xiumin Diao, L. Martinez, T. Sarkodie-Gyan
This paper describes a control strategy for an active body suspension system for treadmill based neural rehabilitation or training devices. Using an acceleration feedback, the system behaves like dynamically removing part or all of the body mass of the trainee so that he/she will truly feel like having a reduced mass while being trained for walking, jogging, or other leg activities on a treadmill. It will be shown that the proposed controller can compensate any amount of inertia force which would not be present as if the trainee had a real reduced mass. As a result, the dynamic load on the trainee's body as well as the supporting legs during an exercise will also be reduced correspondingly. Simulation results are presented to demonstrate the benefits of the actively controlled body suspension system.
{"title":"Dynamically Removing Partial Body Mass Using Acceleration Feedback for Neural Training","authors":"O. Ma, Xiumin Diao, L. Martinez, T. Sarkodie-Gyan","doi":"10.1109/ICORR.2007.4428561","DOIUrl":"https://doi.org/10.1109/ICORR.2007.4428561","url":null,"abstract":"This paper describes a control strategy for an active body suspension system for treadmill based neural rehabilitation or training devices. Using an acceleration feedback, the system behaves like dynamically removing part or all of the body mass of the trainee so that he/she will truly feel like having a reduced mass while being trained for walking, jogging, or other leg activities on a treadmill. It will be shown that the proposed controller can compensate any amount of inertia force which would not be present as if the trainee had a real reduced mass. As a result, the dynamic load on the trainee's body as well as the supporting legs during an exercise will also be reduced correspondingly. Simulation results are presented to demonstrate the benefits of the actively controlled body suspension system.","PeriodicalId":197465,"journal":{"name":"2007 IEEE 10th International Conference on Rehabilitation Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125595689","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 : 2007-06-13DOI: 10.1109/ICORR.2007.4428557
H. Schmidt, F. Piorko, J. Krüger, S. Hussein, M. Volkmar, C. Werner, I. Helmich, S. Hesse, Ralf Tita, R. Riener, Martin Buss, Tim C Lüth
A major criterion for the application of rehabilitation robots in gait therapy is the question to what extent the machine is able to facilitate physiologically correct muscle activation patters in the patients leg muscles in order to achieve an optimal gait training effect. The EMG data presented in this paper is based on intermediate results of a study with 8 healthy subjects (5 male, 3 female) to evaluate the end-effector based gait rehabilitation robot HapticWalker in position controlled mode. The study investigated two different walking trajectories (floor, upstairs) at three different cadences (45, 60, 90 steps/min) in three different modes (free walking, HapticWalker with vertical CoM motion, HapticWalker without vertical CoM motion). Results show that muscle EMGs measured from all relevant leg muscles have the same phasic and rhythmic muscle activation patterns on the HapticWalker as with free walking. Even though there are differences in patterns of dedicated muscles, we observed reduced amplitudes and slightly delayed activation on the HapticWalker compared to free walking. No differences in EMGs were observed between the two different HapticWalker modes (with vertical CoM motion, cancelled CoM motion), which might eliminate the need for an active trunk suspension system in the latter case. A passive patient lifter would significantly reduce the complexity of the machine construction, all advanced training modes (e.g. dynamic body weight reduction) could then be accomplished via compliant behavior of the freely programmable footplates. Numerous EMG measurements with healthy subjects and non-ambulatory stroke patients were performed on the predecessing electromechanical Gait Trainer GT I and showed that physiologically relevant findings from healthy subjects (e.g. correct phasic muscle activation) can be transferred to a certain extent to stroke patients, but nevertheless studies with stroke patients on the robotic gait trainer HapticWalker are needed to confirm the results presented in this paper.
{"title":"Muscle activation patterns of healthy subjects during floor walking and stair climbing on an end-effector-based gait rehabilitation robot","authors":"H. Schmidt, F. Piorko, J. Krüger, S. Hussein, M. Volkmar, C. Werner, I. Helmich, S. Hesse, Ralf Tita, R. Riener, Martin Buss, Tim C Lüth","doi":"10.1109/ICORR.2007.4428557","DOIUrl":"https://doi.org/10.1109/ICORR.2007.4428557","url":null,"abstract":"A major criterion for the application of rehabilitation robots in gait therapy is the question to what extent the machine is able to facilitate physiologically correct muscle activation patters in the patients leg muscles in order to achieve an optimal gait training effect. The EMG data presented in this paper is based on intermediate results of a study with 8 healthy subjects (5 male, 3 female) to evaluate the end-effector based gait rehabilitation robot HapticWalker in position controlled mode. The study investigated two different walking trajectories (floor, upstairs) at three different cadences (45, 60, 90 steps/min) in three different modes (free walking, HapticWalker with vertical CoM motion, HapticWalker without vertical CoM motion). Results show that muscle EMGs measured from all relevant leg muscles have the same phasic and rhythmic muscle activation patterns on the HapticWalker as with free walking. Even though there are differences in patterns of dedicated muscles, we observed reduced amplitudes and slightly delayed activation on the HapticWalker compared to free walking. No differences in EMGs were observed between the two different HapticWalker modes (with vertical CoM motion, cancelled CoM motion), which might eliminate the need for an active trunk suspension system in the latter case. A passive patient lifter would significantly reduce the complexity of the machine construction, all advanced training modes (e.g. dynamic body weight reduction) could then be accomplished via compliant behavior of the freely programmable footplates. Numerous EMG measurements with healthy subjects and non-ambulatory stroke patients were performed on the predecessing electromechanical Gait Trainer GT I and showed that physiologically relevant findings from healthy subjects (e.g. correct phasic muscle activation) can be transferred to a certain extent to stroke patients, but nevertheless studies with stroke patients on the robotic gait trainer HapticWalker are needed to confirm the results presented in this paper.","PeriodicalId":197465,"journal":{"name":"2007 IEEE 10th International Conference on Rehabilitation Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130038840","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 : 2007-06-13DOI: 10.1109/ICORR.2007.4428545
Dominique M. Durand, W. Tesfayesus, P. Yoo
Neural signals recorded in functional sections of the nervous system where voluntary movement has been retained can be used to control prosthetic devices to assist patients to regain lost function. The number of signals recorded to control these devices can be increased by using a single multi-contact electrode placed over a multi-fasciculated peripheral nerve. Recordings made using these electrodes can then be separated using blind signal separation (BSS) methods to recover individual fascicular neural activity. In this study, we first determine the feasibility of recording selectively using nerve cuff electrodes. A flat nerve interface electrode was applied to the hypoglossal nerve to record signals from 11 contacts. Individual fascicles were activated to determine the ability of the electrode to detect signals from the various fascicles. The results show that fascicular signals can be distinguished in the presence of physiological noise amplitudes. We then investigate the feasibility of recovering the individual fascicular signals. We implement a blind source separation (BSS) algorithm BSS using independent component analysis (ICA) and investigate the effects of the number of contacts used and electrode layout on separation. Peripheral neural signals were simulated using a finite element model of the hypoglossal nerve of adult beagle dogs with a multi-contact cuff electrode placed around it. FastICA was then used to separate simulated neural signals. The separated and processed neural signals were then compared to the original source signals in the fascicles using correlation coefficient (CC) calculations. For n = 50 trials, the CC values obtained were all higher than 0.9 indicating that BSS can be used to recover linearly mixed independent fascicular neural signals recorded using a multi-contact cuff electrode. However, the order of the signals is lost during the recovery process. In order to solve the ambiguity of the recovered signals a novel method was designed and tested. In this method, a template of the demixing matrix is built during a training period. Each new estimated signals is compared to the template and the columns rearranged to restore the correct order of the recovered signals. These results suggest that it is possible to obtain multiple control signals from fasciculated peripheral nerves.
{"title":"Peripheral Nerve Signals for Neural Control","authors":"Dominique M. Durand, W. Tesfayesus, P. Yoo","doi":"10.1109/ICORR.2007.4428545","DOIUrl":"https://doi.org/10.1109/ICORR.2007.4428545","url":null,"abstract":"Neural signals recorded in functional sections of the nervous system where voluntary movement has been retained can be used to control prosthetic devices to assist patients to regain lost function. The number of signals recorded to control these devices can be increased by using a single multi-contact electrode placed over a multi-fasciculated peripheral nerve. Recordings made using these electrodes can then be separated using blind signal separation (BSS) methods to recover individual fascicular neural activity. In this study, we first determine the feasibility of recording selectively using nerve cuff electrodes. A flat nerve interface electrode was applied to the hypoglossal nerve to record signals from 11 contacts. Individual fascicles were activated to determine the ability of the electrode to detect signals from the various fascicles. The results show that fascicular signals can be distinguished in the presence of physiological noise amplitudes. We then investigate the feasibility of recovering the individual fascicular signals. We implement a blind source separation (BSS) algorithm BSS using independent component analysis (ICA) and investigate the effects of the number of contacts used and electrode layout on separation. Peripheral neural signals were simulated using a finite element model of the hypoglossal nerve of adult beagle dogs with a multi-contact cuff electrode placed around it. FastICA was then used to separate simulated neural signals. The separated and processed neural signals were then compared to the original source signals in the fascicles using correlation coefficient (CC) calculations. For n = 50 trials, the CC values obtained were all higher than 0.9 indicating that BSS can be used to recover linearly mixed independent fascicular neural signals recorded using a multi-contact cuff electrode. However, the order of the signals is lost during the recovery process. In order to solve the ambiguity of the recovered signals a novel method was designed and tested. In this method, a template of the demixing matrix is built during a training period. Each new estimated signals is compared to the template and the columns rearranged to restore the correct order of the recovered signals. These results suggest that it is possible to obtain multiple control signals from fasciculated peripheral nerves.","PeriodicalId":197465,"journal":{"name":"2007 IEEE 10th International Conference on Rehabilitation Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120988935","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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