The Experts below are selected from a list of 378 Experts worldwide ranked by ideXlab platform

Weihai Chen - One of the best experts on this subject based on the ideXlab platform.

  • Mechanical Design and Simulation on Bionic Lower Extremity Rehabilitation Robot
    2019 14th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2019
    Co-Authors: Jianbin Zhang, Jianhua Wang, Xin Chang, Weihai Chen
    Abstract:

    Lower extremity Exoskeleton Rehabilitation robot is a research focus in the field of robotics, which is meant to assist Rehabilitation doctors in Rehabilitation training for patients. This paper mainly discusses a new type of bionic lower limb Rehabilitation robot. First, the main mechanical structure of the Rehabilitation robot is analyzed, including the leg structure, the backboard system and the auxiliary Rehabilitation platform. Secondly, the kinematics analysis of the external bones was carried out and the space of motion was calculated. Finally, the whole model of the Rehabilitation robot is imported into ADAMS, and the correctness of the analysis is verified by kinematics simulation. In addition, the force on the connecting shaft of each electric push rod is measured by ADAMS, which provides a basis for the dynamic analysis and verification of the Exoskeleton of the lower extremity. Kinematics analysis and simulation can help plan and optimize gait curves.

  • ICARCV - Research on Command Confirmation Unit Based on Motor Imagery EEG Signal Decoding Feedback in Brain-Computer Interface
    2018 15th International Conference on Control Automation Robotics and Vision (ICARCV), 2018
    Co-Authors: Yue Zhang, Weihai Chen, Fangang Meng
    Abstract:

    The brain-computer interface (BCI) technology is a new human-machine interaction technology that realizes people to control external devices directly by thinking (i.e. electroencephalogram, EEG). However, because of the weakness and randomness of EEG signal, it is very complicated and difficult to process and identify the EEG signal recorded by the non-invasive BCI, and the decoding error often occurs. In view of the brain electrical signal decoding error, an experimental paradigm for simultaneous acquisition of spontaneous EEG and evoked EEG was designed, where the subjects generated the error-related potentials (ErrP) based on the decoded feedback of motor imagery EEG. We analyzed the EEG signal two times. The motor imagery EEG, which was the component of the EEG signal, was analyzed at the first time analysis. We classified the motor imagery EEG signal of left and right hand, then analyzed the classification method quantitatively using the Receiver Operating Characteristic (ROC) curves and the area under the curve (AVC). Although the EEG signal were influenced greatly by the individual difference, the AVC values can still reach more than 0.7. Meanwhile, the frequency domain characteristics were analyzed. The activation brain regions of the left-right hand motor imagery are mainly concentrated in the area of the perceptual motor cortex where is responsible for hand motion, but they will also be influenced by the artifacts of the surrounding channels. In the second time analysis, the ErrP was extracted and discussed. Its latency, waveform and amplitude characteristics were studied in the time domain and then a suitable classifier is selected by comparing a variety of classifiers, which classification accuracy is up to 90%. Therefore, the research based on the ErrP signal played a theoretical foundation for applying to the lower limb Exoskeleton Rehabilitation robot in the future, and ensured the feasibility of applying the command confirmation unit based on ErrP signal to the Exoskeleton Rehabilitation robot.

  • Adaptive sliding mode control for a lower-limb Exoskeleton Rehabilitation robot
    2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2018
    Co-Authors: Yinping Zhang, Jianhua Wang, Weihai Chen
    Abstract:

    This paper presents an adaptive sliding mode control (ASMC) method for wearable lower extremity Exoskeleton. Since the dynamic control system of lower limb Exoskeleton robot is non-linear, it is difficult to track the desired trajectory accurately. In this paper, an adaptive single-input single-output (SISO) system, whose adaptive law is designed based on the Lyapunov method, is applied to calculate the element of the control gain vector in a sliding mode controller. A simulating model was built, different control methods, like PID control, classical sliding mode control, and adaptive sliding mode control, have been tested on the prototype. The results show that ASMC has better performance in eliminating jitter and tracking trajectories than PID and classical sliding mode control.

  • Research on Command Confirmation Unit Based on Motor Imagery EEG Signal Decoding Feedback in Brain-Computer Interface
    2018 15th International Conference on Control Automation Robotics and Vision (ICARCV), 2018
    Co-Authors: Yue Zhang, Weihai Chen, Fangang Meng
    Abstract:

    The brain-computer interface (BCI) technology is a new human-machine interaction technology that realizes people to control external devices directly by thinking (i.e. electroencephalogram, EEG). However, because of the weakness and randomness of EEG signal, it is very complicated and difficult to process and identify the EEG signal recorded by the non-invasive BCI, and the decoding error often occurs. In view of the brain electrical signal decoding error, an experimental paradigm for simultaneous acquisition of spontaneous EEG and evoked EEG was designed, where the subjects generated the error-related potentials (ErrP) based on the decoded feedback of motor imagery EEG. We analyzed the EEG signal two times. The motor imagery EEG, which was the component of the EEG signal, was analyzed at the first time analysis. We classified the motor imagery EEG signal of left and right hand, then analyzed the classification method quantitatively using the Receiver Operating Characteristic (ROC) curves and the area under the curve (AVC). Although the EEG signal were influenced greatly by the individual difference, the AVC values can still reach more than 0.7. Meanwhile, the frequency domain characteristics were analyzed. The activation brain regions of the left-right hand motor imagery are mainly concentrated in the area of the perceptual motor cortex where is responsible for hand motion, but they will also be influenced by the artifacts of the surrounding channels. In the second time analysis, the ErrP was extracted and discussed. Its latency, waveform and amplitude characteristics were studied in the time domain and then a suitable classifier is selected by comparing a variety of classifiers, which classification accuracy is up to 90%. Therefore, the research based on the ErrP signal played a theoretical foundation for applying to the lower limb Exoskeleton Rehabilitation robot in the future, and ensured the feasibility of applying the command confirmation unit based on ErrP signal to the Exoskeleton Rehabilitation robot.

  • CIS/RAM - EEG-based brain-controlled lower extremity Exoskeleton Rehabilitation robot
    2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics Automation and Mechatronics (RAM), 2017
    Co-Authors: Gaojie Yu, Jianhua Wang, Weihai Chen, Jianbin Zhang
    Abstract:

    Brain-computer interfaces (BCIs), based on electroencephalography (EEG), have been proved to play an important role in motor Rehabilitation, motor replacement, prosthesis control, and assistive technologies. BCIs can classify EEG signals and translate the brain activities into useful commands for external devices. This paper presents a brain-controlled lower extremity Exoskeleton Rehabilitation robot with a motor-imagery (MI)-based BCI to enhance active Rehabilitation participation. Four healthy individuals performed MI tasks of left and right hand movements to control the speed of gait training. The proposed paradigm could be further implemented by adding motor tasks and promoting MI classification accuracy.

Yunliang Wang - One of the best experts on this subject based on the ideXlab platform.

  • Development of an upper limb Rehabilitation robot system for bilateral training
    2014 IEEE International Conference on Mechatronics and Automation, 2014
    Co-Authors: Wu Zhang, Xin Zhao, Yunliang Wang
    Abstract:

    The paper deals with tracking control in both sides of an upper limb Rehabilitation robot system. A Rehabilitation Intelligent Training System (RITS) for the recovery of motion function of upper limbs is introduced. The system has a lot of advantages for its special applications such as small size, less weight and good human-computer interaction interface during the Rehabilitation process. Besides, this system consists of the Upper Limb Exoskeleton Rehabilitation Device (ULERD), a haptic device called PHANTOM Premium 1.5, an MTx sensor, a computer and so on. The system is a master-slave Rehabilitation system. The master side is ULERD and the slave said is the PHANTOM Premium. Tracking control in two sides means the slave side follows the motion of the master side through tracking control with force feedback. In the bilateral training process, the impaired hand of the patient wears the ULERD and the intact hand grips the stylus of the PHANTOM Premium. When the ULERD is moved by the patient, the stylus of PHANTOM Premium will track it within very short time. Experiment has been performed to prove that the bilateral training in two sides of the robot system has a good following performance. The development of this method can be a promising approach for further research in more effective Rehabilitation to the upper limb.

  • A novel VR-based upper limb Rehabilitation robot system
    2013 ICME International Conference on Complex Medical Engineering, 2013
    Co-Authors: Wu Zhang, Yunliang Wang
    Abstract:

    This paper presents a novel upper limb Rehabilitation robot system based on virtual reality as many benefits of robots involved in upper limb Rehabilitation for stroke are found out. The system has advantages of small size, less weight and interaction in Rehabilitation. This system mainly consists of a haptic device called PHANTOM Premium, the upper limb Exoskeleton Rehabilitation device (ULERD) and a virtual reality environment. The impaired hand wears the ULERD, so the therapist can control and move the injured hand by PHANTOM Premium in tele-operation. With description of the system, the realization of virtual reality environment is implemented, which can potentially motivate patients to exercise for longer periods of time. Not only virtual images but also position and force information are sent to the doctors. This system aims to develop a light and interactive upper limb Rehabilitation robot system which allows Rehabilitation stations to be placed in a patient's home. And some exercise parameters evaluate the performance of patients. Experiment has been conducted to prove that it is accurate and convenient in the Rehabilitation process. The development of this system can be a promising approach for further research in the field of tele-rehablitation science.

  • A kinematic model of an upper limb Rehabilitation robot system
    2013 IEEE International Conference on Mechatronics and Automation, 2013
    Co-Authors: Wu Zhang, Yuehui Ji, Yunliang Wang
    Abstract:

    This paper presents a kinematic model of an upper limb Rehabilitation robot system based on Denavit-Hartenberg parameters method. The system possesses advantages of less weight, compact size, and interaction in the Rehabilitation process. Furthermore it can provide a sufficient work room for the patient's upper limb. This system mainly consists of an upper limb Exoskeleton Rehabilitation device (ULERD), a haptic device called PHANTOM Premium, and an interactive virtual reality environment. The proposed Rehabilitation robot system is a master-slave system. The impaired hand is hard bolted to the ULERD, so the doctor (or the intact hand of patients) can move the stylus of PHAMTOM Premium and guide the injured hand to move along some predefined training track. This paper aims to establish a kinematic model of the Rehabilitation robot system. A kinematic model focusing on the ULERD and the PHANTOM Premium is built to ensure the consistency for both the Phantom side and ULERD side. DH-parameters-based modeling can be an effective method in kinematic modeling of a robot.

  • A novel upper limb Rehabilitation system with hand Exoskeleton mechanism
    2013 IEEE International Conference on Mechatronics and Automation, 2013
    Co-Authors: Fan Zhang, Yuehui Ji, Yunliang Wang
    Abstract:

    The Exoskeleton robot is a comprehensive technology that is combination of sensing, control and information. Based on the upper limb Exoskeleton Rehabilitation device (ULERD), this paper describes a novel hand Exoskeleton mechanism for using in Rehabilitation field and aiming at helping varieties of hemiparalysis patients recover motor function of the whole-arm. This system consists of Exoskeleton device, haptic device (PHANTOM Premium), motors, motor controllers and work station. And the hand Exoskeleton mechanism is portable, wearable and adjustable for patients doing home Rehabilitation training. Through using the finite element software (ANSYS), the main components of the hand Exoskeleton are studied by force simulation analysis. And it shows that the Exoskeleton device have the ability to resist deformation and sustain patients' fingers to implement Rehabilitation training. Except that, a finger model is established to simulate the force status in different flexion angles of the proximal interphalangeal (PIP) joint and the metacarpaophalangeal (MCP) joint. From the analysis of the finger joint, the optimal joint activity range of device is presented that the PIP joint is less than 60° and the MCP joint is less than 75°. These experiments demonstrate this Exoskeleton can provide a scientific Rehabilitation method for the hemiparalysis patients and force influence of the Exoskeleton device should be considered and reduced. In the future, with the mechanism structure improvement, this system will have a promising application prospect in the Rehabilitation field.

Peter S. Lum - One of the best experts on this subject based on the ideXlab platform.

  • Clinical effects of using HEXORR (Hand Exoskeleton Rehabilitation Robot) for movement therapy in stroke Rehabilitation
    American Journal of Physical Medicine and Rehabilitation, 2013
    Co-Authors: Sasha Blue Godfrey, Rahsaan J. Holley, Peter S. Lum
    Abstract:

    OBJECTIVE: The goals of this pilot study were to quantify the clinical benefits of using the Hand Exoskeleton Rehabilitation Robot for hand Rehabilitation after stroke and to determine the population best served by this intervention.\n\nDESIGN: Nine subjects with chronic stroke (one excluded from analysis) completed 18 sessions of training with the Hand Exoskeleton Rehabilitation Robot and a preevaluation, a postevaluation, and a 90-day clinical evaluation.\n\nRESULTS: Overall, the subjects improved in both range of motion and clinical measures. Compared with the preevaluation, the subjects showed significant improvements in range of motion, grip strength, and the hand component of the Fugl-Meyer (mean changes, 6.60 degrees, 8.84 percentage points, and 1.86 points, respectively). A subgroup of six subjects exhibited lower tone and received a higher dosage of training. These subjects had significant gains in grip strength, the hand component of the Fugl-Meyer, and the Action Research Arm Test (mean changes, 8.42 percentage points, 2.17 points, and 2.33 points, respectively).\n\nCONCLUSIONS: Future work is needed to better manage higher levels of hypertonia and provide more support to subjects with higher impairment levels; however, the current results support further study into the Hand Exoskeleton Rehabilitation Robot treatment.

  • Hand function recovery in chronic stroke with HEXORR robotic training: A case series
    2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010
    Co-Authors: Sasha Blue Godfrey, Christopher N. Schabowsky, Rahsaan J. Holley, Peter S. Lum
    Abstract:

    After a stroke, many survivors have impaired motor function. Robotic Rehabilitation techniques have emerged to provide a repetitive, activity-based therapy at potentially lower cost than conventional methods. Many patients exhibit intrinsic resistance to hand extension in the form of spasticity and/or hypertonia. We have developed a therapy program using the Hand Exoskeleton Rehabilitation Robot (HEXORR) that is capable of compensating for tone to assist patients in opening the paretic hand. The system can move the user's hand, assist movement, allow free movement, or restrict movement to allow static force production. These options combine with an interactive virtual reality game to enhance user motivation. Four chronic stroke subjects received 18 sessions of robot therapy as well as pre and post evaluation sessions. All subjects showed at least modest gains in active finger range of motion (ROM) measured in the robot, and all but one subject had gains in active thumb ROM. Most of these gains carried over to ROM gains outside of the robot. The clinical measures (Fugl-Meyer, Box-and-Blocks) showed clear improvements in two subjects and mixed results in two subjects. Overall, the robot therapy was well received by subjects and shows promising results. We conclude HEXORR therapy is best suited for patients with mild-moderate tone and at least minimal extension.

  • Development and pilot testing of HEXORR: Hand Exoskeleton Rehabilitation robot
    Journal of NeuroEngineering and Rehabilitation, 2010
    Co-Authors: Christopher N. Schabowsky, Rahsaan J. Holley, Sasha Blue Godfrey, Peter S. Lum
    Abstract:

    Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased.

Rahsaan J. Holley - One of the best experts on this subject based on the ideXlab platform.

  • Clinical effects of using HEXORR (Hand Exoskeleton Rehabilitation Robot) for movement therapy in stroke Rehabilitation
    American Journal of Physical Medicine and Rehabilitation, 2013
    Co-Authors: Sasha Blue Godfrey, Rahsaan J. Holley, Peter S. Lum
    Abstract:

    OBJECTIVE: The goals of this pilot study were to quantify the clinical benefits of using the Hand Exoskeleton Rehabilitation Robot for hand Rehabilitation after stroke and to determine the population best served by this intervention.\n\nDESIGN: Nine subjects with chronic stroke (one excluded from analysis) completed 18 sessions of training with the Hand Exoskeleton Rehabilitation Robot and a preevaluation, a postevaluation, and a 90-day clinical evaluation.\n\nRESULTS: Overall, the subjects improved in both range of motion and clinical measures. Compared with the preevaluation, the subjects showed significant improvements in range of motion, grip strength, and the hand component of the Fugl-Meyer (mean changes, 6.60 degrees, 8.84 percentage points, and 1.86 points, respectively). A subgroup of six subjects exhibited lower tone and received a higher dosage of training. These subjects had significant gains in grip strength, the hand component of the Fugl-Meyer, and the Action Research Arm Test (mean changes, 8.42 percentage points, 2.17 points, and 2.33 points, respectively).\n\nCONCLUSIONS: Future work is needed to better manage higher levels of hypertonia and provide more support to subjects with higher impairment levels; however, the current results support further study into the Hand Exoskeleton Rehabilitation Robot treatment.

  • Development and pilot testing of HEXORR: Hand Exoskeleton Rehabilitation Robot
    Journal of NeuroEngineering and Rehabilitation, 2010
    Co-Authors: Christopher N. Schabowsky, Sasha B Godfrey, Rahsaan J. Holley
    Abstract:

    Background Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased. Methods This paper introduces a newly developed Hand Exoskeleton Rehabilitation Robot (HEXORR). This device has been designed to provide full range of motion (ROM) for all of the hand's digits. The thumb actuator allows for variable thumb plane of motion to incorporate different degrees of extension/flexion and abduction/adduction. Compensation algorithms have been developed to improve the Exoskeleton's backdrivability by counteracting gravity, stiction and kinetic friction. We have also designed a force assistance mode that provides extension assistance based on each individual's needs. A pilot study was conducted on 9 unimpaired and 5 chronic stroke subjects to investigate the device's ability to allow physiologically accurate hand movements throughout the full ROM. The study also tested the efficacy of the force assistance mode with the goal of increasing stroke subjects' active ROM while still requiring active extension torque on the part of the subject. Results For 12 of the hand digits'15 joints in neurologically normal subjects, there were no significant ROM differences (P > 0.05) between active movements performed inside and outside of HEXORR. Interjoint coordination was examined in the 1^st and 3^rd digits, and no differences were found between inside and outside of the device (P > 0.05). Stroke subjects were capable of performing free hand movements inside of the Exoskeleton and the force assistance mode was successful in increasing active ROM by 43 ± 5% (P < 0.001) and 24 ± 6% (P = 0.041) for the fingers and thumb, respectively. Conclusions Our pilot study shows that this device is capable of moving the hand's digits through nearly the entire ROM with physiologically accurate trajectories. Stroke subjects received the device intervention well and device impedance was minimized so that subjects could freely extend and flex their digits inside of HEXORR. Our active force-assisted condition was successful in increasing the subjects' ROM while promoting active participation.

  • development and pilot testing of hexorr hand Exoskeleton Rehabilitation robot
    Journal of Neuroengineering and Rehabilitation, 2010
    Co-Authors: Christopher N. Schabowsky, Sasha B Godfrey, Rahsaan J. Holley
    Abstract:

    Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased. This paper introduces a newly developed Hand Exoskeleton Rehabilitation Robot (HEXORR). This device has been designed to provide full range of motion (ROM) for all of the hand's digits. The thumb actuator allows for variable thumb plane of motion to incorporate different degrees of extension/flexion and abduction/adduction. Compensation algorithms have been developed to improve the Exoskeleton's backdrivability by counteracting gravity, stiction and kinetic friction. We have also designed a force assistance mode that provides extension assistance based on each individual's needs. A pilot study was conducted on 9 unimpaired and 5 chronic stroke subjects to investigate the device's ability to allow physiologically accurate hand movements throughout the full ROM. The study also tested the efficacy of the force assistance mode with the goal of increasing stroke subjects' active ROM while still requiring active extension torque on the part of the subject. For 12 of the hand digits'15 joints in neurologically normal subjects, there were no significant ROM differences (P > 0.05) between active movements performed inside and outside of HEXORR. Interjoint coordination was examined in the 1st and 3rd digits, and no differences were found between inside and outside of the device (P > 0.05). Stroke subjects were capable of performing free hand movements inside of the Exoskeleton and the force assistance mode was successful in increasing active ROM by 43 ± 5% (P < 0.001) and 24 ± 6% (P = 0.041) for the fingers and thumb, respectively. Our pilot study shows that this device is capable of moving the hand's digits through nearly the entire ROM with physiologically accurate trajectories. Stroke subjects received the device intervention well and device impedance was minimized so that subjects could freely extend and flex their digits inside of HEXORR. Our active force-assisted condition was successful in increasing the subjects' ROM while promoting active participation.

  • Hand function recovery in chronic stroke with HEXORR robotic training: A case series
    2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010
    Co-Authors: Sasha Blue Godfrey, Christopher N. Schabowsky, Rahsaan J. Holley, Peter S. Lum
    Abstract:

    After a stroke, many survivors have impaired motor function. Robotic Rehabilitation techniques have emerged to provide a repetitive, activity-based therapy at potentially lower cost than conventional methods. Many patients exhibit intrinsic resistance to hand extension in the form of spasticity and/or hypertonia. We have developed a therapy program using the Hand Exoskeleton Rehabilitation Robot (HEXORR) that is capable of compensating for tone to assist patients in opening the paretic hand. The system can move the user's hand, assist movement, allow free movement, or restrict movement to allow static force production. These options combine with an interactive virtual reality game to enhance user motivation. Four chronic stroke subjects received 18 sessions of robot therapy as well as pre and post evaluation sessions. All subjects showed at least modest gains in active finger range of motion (ROM) measured in the robot, and all but one subject had gains in active thumb ROM. Most of these gains carried over to ROM gains outside of the robot. The clinical measures (Fugl-Meyer, Box-and-Blocks) showed clear improvements in two subjects and mixed results in two subjects. Overall, the robot therapy was well received by subjects and shows promising results. We conclude HEXORR therapy is best suited for patients with mild-moderate tone and at least minimal extension.

  • Development and pilot testing of HEXORR: Hand Exoskeleton Rehabilitation robot
    Journal of NeuroEngineering and Rehabilitation, 2010
    Co-Authors: Christopher N. Schabowsky, Rahsaan J. Holley, Sasha Blue Godfrey, Peter S. Lum
    Abstract:

    Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased.

Christopher N. Schabowsky - One of the best experts on this subject based on the ideXlab platform.

  • Development and pilot testing of HEXORR: Hand Exoskeleton Rehabilitation Robot
    Journal of NeuroEngineering and Rehabilitation, 2010
    Co-Authors: Christopher N. Schabowsky, Sasha B Godfrey, Rahsaan J. Holley
    Abstract:

    Background Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased. Methods This paper introduces a newly developed Hand Exoskeleton Rehabilitation Robot (HEXORR). This device has been designed to provide full range of motion (ROM) for all of the hand's digits. The thumb actuator allows for variable thumb plane of motion to incorporate different degrees of extension/flexion and abduction/adduction. Compensation algorithms have been developed to improve the Exoskeleton's backdrivability by counteracting gravity, stiction and kinetic friction. We have also designed a force assistance mode that provides extension assistance based on each individual's needs. A pilot study was conducted on 9 unimpaired and 5 chronic stroke subjects to investigate the device's ability to allow physiologically accurate hand movements throughout the full ROM. The study also tested the efficacy of the force assistance mode with the goal of increasing stroke subjects' active ROM while still requiring active extension torque on the part of the subject. Results For 12 of the hand digits'15 joints in neurologically normal subjects, there were no significant ROM differences (P > 0.05) between active movements performed inside and outside of HEXORR. Interjoint coordination was examined in the 1^st and 3^rd digits, and no differences were found between inside and outside of the device (P > 0.05). Stroke subjects were capable of performing free hand movements inside of the Exoskeleton and the force assistance mode was successful in increasing active ROM by 43 ± 5% (P < 0.001) and 24 ± 6% (P = 0.041) for the fingers and thumb, respectively. Conclusions Our pilot study shows that this device is capable of moving the hand's digits through nearly the entire ROM with physiologically accurate trajectories. Stroke subjects received the device intervention well and device impedance was minimized so that subjects could freely extend and flex their digits inside of HEXORR. Our active force-assisted condition was successful in increasing the subjects' ROM while promoting active participation.

  • development and pilot testing of hexorr hand Exoskeleton Rehabilitation robot
    Journal of Neuroengineering and Rehabilitation, 2010
    Co-Authors: Christopher N. Schabowsky, Sasha B Godfrey, Rahsaan J. Holley
    Abstract:

    Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased. This paper introduces a newly developed Hand Exoskeleton Rehabilitation Robot (HEXORR). This device has been designed to provide full range of motion (ROM) for all of the hand's digits. The thumb actuator allows for variable thumb plane of motion to incorporate different degrees of extension/flexion and abduction/adduction. Compensation algorithms have been developed to improve the Exoskeleton's backdrivability by counteracting gravity, stiction and kinetic friction. We have also designed a force assistance mode that provides extension assistance based on each individual's needs. A pilot study was conducted on 9 unimpaired and 5 chronic stroke subjects to investigate the device's ability to allow physiologically accurate hand movements throughout the full ROM. The study also tested the efficacy of the force assistance mode with the goal of increasing stroke subjects' active ROM while still requiring active extension torque on the part of the subject. For 12 of the hand digits'15 joints in neurologically normal subjects, there were no significant ROM differences (P > 0.05) between active movements performed inside and outside of HEXORR. Interjoint coordination was examined in the 1st and 3rd digits, and no differences were found between inside and outside of the device (P > 0.05). Stroke subjects were capable of performing free hand movements inside of the Exoskeleton and the force assistance mode was successful in increasing active ROM by 43 ± 5% (P < 0.001) and 24 ± 6% (P = 0.041) for the fingers and thumb, respectively. Our pilot study shows that this device is capable of moving the hand's digits through nearly the entire ROM with physiologically accurate trajectories. Stroke subjects received the device intervention well and device impedance was minimized so that subjects could freely extend and flex their digits inside of HEXORR. Our active force-assisted condition was successful in increasing the subjects' ROM while promoting active participation.

  • Hand function recovery in chronic stroke with HEXORR robotic training: A case series
    2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010
    Co-Authors: Sasha Blue Godfrey, Christopher N. Schabowsky, Rahsaan J. Holley, Peter S. Lum
    Abstract:

    After a stroke, many survivors have impaired motor function. Robotic Rehabilitation techniques have emerged to provide a repetitive, activity-based therapy at potentially lower cost than conventional methods. Many patients exhibit intrinsic resistance to hand extension in the form of spasticity and/or hypertonia. We have developed a therapy program using the Hand Exoskeleton Rehabilitation Robot (HEXORR) that is capable of compensating for tone to assist patients in opening the paretic hand. The system can move the user's hand, assist movement, allow free movement, or restrict movement to allow static force production. These options combine with an interactive virtual reality game to enhance user motivation. Four chronic stroke subjects received 18 sessions of robot therapy as well as pre and post evaluation sessions. All subjects showed at least modest gains in active finger range of motion (ROM) measured in the robot, and all but one subject had gains in active thumb ROM. Most of these gains carried over to ROM gains outside of the robot. The clinical measures (Fugl-Meyer, Box-and-Blocks) showed clear improvements in two subjects and mixed results in two subjects. Overall, the robot therapy was well received by subjects and shows promising results. We conclude HEXORR therapy is best suited for patients with mild-moderate tone and at least minimal extension.

  • Development and pilot testing of HEXORR: Hand Exoskeleton Rehabilitation robot
    Journal of NeuroEngineering and Rehabilitation, 2010
    Co-Authors: Christopher N. Schabowsky, Rahsaan J. Holley, Sasha Blue Godfrey, Peter S. Lum
    Abstract:

    Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased.