1
|
Veeresh Babu M, Ramya V, Senthil Murugan V. Design and development of embedded/SQL home based upper limb rehabilitation. INTERNATIONAL JOURNAL OF HEALTHCARE MANAGEMENT 2022. [DOI: 10.1080/20479700.2022.2124492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Affiliation(s)
- M. Veeresh Babu
- Research Scholar, Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University, Chidambaram, India
| | - V. Ramya
- Associate Professor, Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University, Chidambaram, India
| | - V. Senthil Murugan
- Principal, Viswam Engineering College, Madanapalle, Chittoor (Dist.), India
| |
Collapse
|
2
|
Analysis of the Leap Motion Controller's Performance in Measuring Wrist Rehabilitation Tasks Using an Industrial Robot Arm Reference. SENSORS 2022; 22:s22134880. [PMID: 35808379 PMCID: PMC9269845 DOI: 10.3390/s22134880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 05/19/2022] [Accepted: 06/25/2022] [Indexed: 11/17/2022]
Abstract
The Leap Motion Controller (LMC) is a low-cost markerless optical sensor that performs measurements of various parameters of the hands that has been investigated for a wide range of different applications. Research attention still needs to focus on the evaluation of its precision and accuracy to fully understand its limitations and widen its range of applications. This paper presents the experimental validation of the LMC device to verify the feasibility of its use in assessing and tailoring wrist rehabilitation therapy for the treatment of physical disabilities through continuous exercises and integration with serious gaming environments. An experimental set up and analysis is proposed using an industrial robot as motion reference. The high repeatability of the selected robot is used for comparisons with the measurements obtained via a leap motion controller while performing the basic movements needed for rehabilitation exercises of the human wrist. Experimental tests are analyzed and discussed to demonstrate the feasibility of using the leap motion controller for wrist rehabilitation.
Collapse
|
3
|
Therapist-Patient Interactions in Task-Oriented Stroke Therapy can Guide Robot-Patient Interactions. Int J Soc Robot 2022. [DOI: 10.1007/s12369-022-00881-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
|
4
|
A Case Study of Upper Limb Robotic-Assisted Therapy Using the Track-Hold Device. SENSORS 2022; 22:s22031009. [PMID: 35161755 PMCID: PMC8840074 DOI: 10.3390/s22031009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/19/2022] [Accepted: 01/21/2022] [Indexed: 12/07/2022]
Abstract
The Track-Hold System (THS) project, developed in a healthcare facility and therefore in a controlled and protected healthcare environment, contributes to the more general and broad context of Robotic-Assisted Therapy (RAT). RAT represents an advanced and innovative rehabilitation method, both motor and cognitive, and uses active, passive, and facilitating robotic devices. RAT devices can be equipped with sensors to detect and track voluntary and involuntary movements. They can work in synergy with multimedia protocols developed ad hoc to achieve the highest possible level of functional re-education. The THS is based on a passive robotic arm capable of recording and facilitating the movements of the upper limbs. An operational interface completes the device for its use in the clinical setting. In the form of a case study, the researchers conducted the experimentation in the former Tabarracci hospital (Viareggio, Italy). The case study develops a motor and cognitive rehabilitation protocol. The chosen subjects suffered from post-stroke outcomes affecting the right upper limb, including strength deficits, tremors, incoordination, and motor apraxia. During the first stage of the enrolment, the researchers worked with seven patients. The researchers completed the pilot with four patients because three of them got a stroke recurrence. The collaboration with four patients permitted the generation of an enlarged case report to collect preliminary data. The preliminary clinical results of the Track-Hold System Project demonstrated good compliance by patients with robotic-assisted rehabilitation; in particular, patients underwent a gradual path of functional recovery of the upper limb using the implemented interface.
Collapse
|
5
|
Wang Y, Duan F, Wang Y. Multi-point surface FES hand rehabilitation system for stroke patients based on eye movement control. Adv Robot 2021. [DOI: 10.1080/01691864.2021.1982405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Yan Wang
- The College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Feng Duan
- The College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Yongchen Wang
- The College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| |
Collapse
|
6
|
Gonçalves RS, Brito LSF, Moraes LP, Carbone G, Ceccarelli M. A fairly simple mechatronic device for training human wrist motion. INT J ADV ROBOT SYST 2020. [DOI: 10.1177/1729881420974286] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
This article proposes a novel device for wrist motion rehabilitation. The proposed mechatronic architecture is based on a simple user-friendly design, which includes a mobile platform for hand support, which is operated by a single actuator. A dedicated assist-as-needed control is designed to operate the device for the required movements. The proposed control strategy is also integrated into a gaming software for stimulating the exercising by means of various interactions with patients. Experimental tests are carried out with 14 healthy subjects at the Physiotherapy Clinical Hospital of the Federal University of Uberlandia. Also, three patients with stroke have been enrolled in a pilot clinical testing. Each of the patients has been involved in four sessions per month with 15 min of assisted treatment. Results of experimental tests are analyzed in terms of improvements and amplitude gains for the flexion and extension wrist movements. Experimental results are reported as evidence for the feasibility and soundness of the proposed device as a tool to assist professionals in procedures of wrist rehabilitation.
Collapse
|
7
|
Chou CH, Wang T, Sun X, Niu CM, Hao M, Xie Q, Lan N. Automated functional electrical stimulation training system for upper-limb function recovery in poststroke patients. Med Eng Phys 2020; 84:174-183. [PMID: 32977916 DOI: 10.1016/j.medengphy.2020.09.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 08/24/2020] [Accepted: 09/02/2020] [Indexed: 11/24/2022]
Abstract
BACKGROUND This paper describes the design and test of an automated functional electrical stimulation (FES) system for poststroke rehabilitation training. The aim of automated FES is to synchronize electrically induced movements to assist residual movements of patients. METHODS In the design of the FES system, an accelerometry module detected movement initiation and movement performed by post-stroke patients. The desired movement was displayed in visual game module. Synergy-based FES patterns were formulated using a normal pattern of muscle synergies from a healthy subject. Experiment 1 evaluated how different levels of trigger threshold or timing affected the variability of compound movements for forward reaching (FR) and lateral reaching (LR). Experiment 2 explored the effect of FES duration on compound movements. RESULTS Synchronizing FES-assisted movements with residual voluntary movements produced more consistent compound movements. Matching the duration of synergy-based FES to that of patients could assist slower movements of patients with reduced RMS errors. CONCLUSIONS Evidence indicated that synchronization and matching duration with residual voluntary movements of patients could improve the consistency of FES assisted movements. Automated FES training can reduce the burden of therapists to monitor the training process, which may encourage patients to complete the training.
Collapse
Affiliation(s)
- Chih-Hong Chou
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, China
| | - Tong Wang
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, China
| | - Xiaopei Sun
- Department of Rehabilitation Medicine, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chuanxin M Niu
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, China; Department of Rehabilitation Medicine, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Manzhao Hao
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, China
| | - Qing Xie
- Department of Rehabilitation Medicine, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
| | - Ning Lan
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, China.
| |
Collapse
|
8
|
Stewart A, Pretty C, Chen X. A portable assist-as-need upper-extremity hybrid exoskeleton for FES-induced muscle fatigue reduction in stroke rehabilitation. BMC Biomed Eng 2020; 1:30. [PMID: 32903348 PMCID: PMC7422522 DOI: 10.1186/s42490-019-0028-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 09/23/2019] [Indexed: 11/24/2022] Open
Abstract
Background Hybrid exoskeletons are a recent development which combine Functional Electrical Stimulation with actuators to improve both the mental and physical rehabilitation of stroke patients. Hybrid exoskeletons have been shown capable of reducing the weight of the actuator and improving movement precision compared to Functional Electrical Stimulation alone. However little attention has been given towards the ability of hybrid exoskeletons to reduce and manage Functional Electrical Stimulation induced fatigue or towards adapting to user ability. This work details the construction and testing of a novel assist-as-need upper-extremity hybrid exoskeleton which uses model-based Functional Electrical Stimulation control to delay Functional Electrical Stimulation induced muscle fatigue. The hybrid control is compared with Functional Electrical Stimulation only control on a healthy subject. Results The hybrid system produced 24° less average angle error and 13.2° less Root Mean Square Error, than Functional Electrical Stimulation on its own and showed a reduction in Functional Electrical Stimulation induced fatigue. Conclusion As far as the authors are aware, this is the study which provides evidence of the advantages of hybrid exoskeletons compared to use of Functional Electrical Stimulation on its own with regards to the delay of Functional Electrical Stimulation induced muscle fatigue.
Collapse
Affiliation(s)
- Ashley Stewart
- Mechanical Engineering, University of Canterbury, 20 Kirkwood Ave, Upper Riccarton, Christchurch, 8041 New Zealand
| | - Christopher Pretty
- Mechanical Engineering, University of Canterbury, 20 Kirkwood Ave, Upper Riccarton, Christchurch, 8041 New Zealand
| | - Xiaoqi Chen
- Mechanical Engineering, University of Canterbury, 20 Kirkwood Ave, Upper Riccarton, Christchurch, 8041 New Zealand
| |
Collapse
|
9
|
Milia P, Peccini M, De Salvo F, Sfaldaroli A, Grelli C, Lucchesi G, Sadauskas N, Rossi C, Caserio M, Bigazzi M. Rehabilitation with robotic glove (Gloreha) in poststroke patients. ACTA ACUST UNITED AC 2019. [DOI: 10.4103/digm.digm_3_19] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
|
10
|
Rose CG, O'Malley MK. Hybrid Rigid-Soft Hand Exoskeleton to Assist Functional Dexterity. IEEE Robot Autom Lett 2019. [DOI: 10.1109/lra.2018.2878931] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
|
11
|
Frolov AA, Kozlovskaya IB, Biryukova EV, Bobrov PD. Use of Robotic Devices in Post-Stroke Rehabilitation. ACTA ACUST UNITED AC 2018. [DOI: 10.1007/s11055-018-0668-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
|
12
|
Huang Y, Lai WP, Qian Q, Hu X, Tam EWC, Zheng Y. Translation of robot-assisted rehabilitation to clinical service: a comparison of the rehabilitation effectiveness of EMG-driven robot hand assisted upper limb training in practical clinical service and in clinical trial with laboratory configuration for chronic stroke. Biomed Eng Online 2018; 17:91. [PMID: 29941043 PMCID: PMC6019523 DOI: 10.1186/s12938-018-0516-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 06/12/2018] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Rehabilitation robots can provide intensive physical training after stroke. However, variations of the rehabilitation effects in translation from well-controlled research studies to clinical services have not been well evaluated yet. This study aims to compare the rehabilitation effects of the upper limb training by an electromyography (EMG)-driven robotic hand achieved in a well-controlled research environment and in a practical clinical service. METHODS It was a non-randomized controlled trial, and thirty-two participants with chronic stroke were recruited either in the clinical service (n = 16, clinic group), or in the research setting (n = 16, lab group). Each participant received 20-session EMG-driven robotic hand assisted upper limb training. The training frequency (4 sessions/week) and the pace in a session were fixed for the lab group, while they were flexible (1-3 sessions/week) and adaptive for the clinic group. The training effects were evaluated before and after the treatment with clinical scores of the Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT), Functional Independence Measure (FIM), and Modified Ashworth Scale (MAS). RESULTS Significant improvements in the FMA full score, shoulder/elbow and wrist/hand (P < 0.001), ARAT (P < 0.001), and MAS elbow (P < 0.05) were observed after the training for both groups. Significant improvements in the FIM (P < 0.05), MAS wrist (P < 0.001) and MAS hand (P < 0.05) were only obtained after the training in the clinic group. Compared with the lab group, higher FIM improvement in the clinic group was observed (P < 0.05). CONCLUSIONS The functional improvements after the robotic hand training in the clinical service were comparable to the effectiveness achieved in the research setting, through flexible training schedules even with a lower training frequency every week. Higher independence in the daily living and a more effective release in muscle tones were achieved in the clinic group than the lab group.
Collapse
Affiliation(s)
- Yanhuan Huang
- Department of Biomedical Engineering, Interdisciplinary Division of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Will Poyan Lai
- Jockey Club Rehabilitation Engineering Clinic, Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Qiuyang Qian
- Department of Biomedical Engineering, Interdisciplinary Division of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Xiaoling Hu
- Department of Biomedical Engineering, Interdisciplinary Division of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Eric W. C. Tam
- Department of Biomedical Engineering, Interdisciplinary Division of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Jockey Club Rehabilitation Engineering Clinic, Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Yongping Zheng
- Department of Biomedical Engineering, Interdisciplinary Division of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| |
Collapse
|
13
|
Wu W, Fong J, Crocher V, Lee PVS, Oetomo D, Tan Y, Ackland DC. Modulation of shoulder muscle and joint function using a powered upper-limb exoskeleton. J Biomech 2018; 72:7-16. [PMID: 29506759 DOI: 10.1016/j.jbiomech.2018.02.019] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Revised: 02/10/2018] [Accepted: 02/12/2018] [Indexed: 11/18/2022]
Abstract
Robotic-assistive exoskeletons can enable frequent repetitive movements without the presence of a full-time therapist; however, human-machine interaction and the capacity of powered exoskeletons to attenuate shoulder muscle and joint loading is poorly understood. This study aimed to quantify shoulder muscle and joint force during assisted activities of daily living using a powered robotic upper limb exoskeleton (ArmeoPower, Hocoma). Six healthy male subjects performed abduction, flexion, horizontal flexion, reaching and nose touching activities. These tasks were repeated under two conditions: (i) the exoskeleton compensating only for its own weight, and (ii) the exoskeleton providing full upper limb gravity compensation (i.e., weightlessness). Muscle EMG, joint kinematics and joint torques were simultaneously recorded, and shoulder muscle and joint forces calculated using personalized musculoskeletal models of each subject's upper limb. The exoskeleton reduced peak joint torques, muscle forces and joint loading by up to 74.8% (0.113 Nm/kg), 88.8% (5.8%BW) and 68.4% (75.6%BW), respectively, with the degree of load attenuation strongly task dependent. The peak compressive, anterior and superior glenohumeral joint force during assisted nose touching was 36.4% (24.6%BW), 72.4% (13.1%BW) and 85.0% (17.2%BW) lower than that during unassisted nose touching, respectively. The present study showed that upper limb weight compensation using an assistive exoskeleton may increase glenohumeral joint stability, since deltoid muscle force, which is the primary contributor to superior glenohumeral joint shear, is attenuated; however, prominent exoskeleton interaction moments are required to position and control the upper limb in space, even under full gravity compensation conditions. The modeling framework and results may be useful in planning targeted upper limb robotic rehabilitation tasks.
Collapse
Affiliation(s)
- Wen Wu
- Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Justin Fong
- Department of Mechanical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Vincent Crocher
- Department of Mechanical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Peter V S Lee
- Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Denny Oetomo
- Department of Mechanical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Ying Tan
- Department of Mechanical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
| | - David C Ackland
- Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia.
| |
Collapse
|
14
|
|
15
|
Panarese A, Pirondini E, Tropea P, Cesqui B, Posteraro F, Micera S. Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients. J Neuroeng Rehabil 2016; 13:81. [PMID: 27609062 PMCID: PMC5016877 DOI: 10.1186/s12984-016-0187-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2016] [Accepted: 08/26/2016] [Indexed: 11/22/2022] Open
Abstract
Background Common scales for clinical evaluation of post-stroke upper-limb motor recovery are often complemented with kinematic parameters extracted from movement trajectories. However, there is no a general consensus on which parameters to use. Moreover, the selected variables may be redundant and highly correlated or, conversely, may incompletely sample the kinematic information from the trajectories. Here we sought to identify a set of clinically useful variables for an exhaustive but yet economical kinematic characterization of upper limb movements performed by post-stroke hemiparetic subjects. Methods For this purpose, we pursued a top-down model-driven approach, seeking which kinematic parameters were pivotal for a computational model to generate trajectories of point-to-point planar movements similar to those made by post-stroke subjects at different levels of impairment. Results The set of kinematic variables used in the model allowed for the generation of trajectories significantly similar to those of either sub-acute or chronic post-stroke patients at different time points during the therapy. Simulated trajectories also correctly reproduced many kinematic features of real movements, as assessed by an extensive set of kinematic metrics computed on both real and simulated curves. When inspected for redundancy, we found that variations in the variables used in the model were explained by three different underlying and unobserved factors related to movement efficiency, speed, and accuracy, possibly revealing different working mechanisms of recovery. Conclusion This study identified a set of measures capable of extensively characterizing the kinematics of upper limb movements performed by post-stroke subjects and of tracking changes of different motor improvement aspects throughout the rehabilitation process. Electronic supplementary material The online version of this article (doi:10.1186/s12984-016-0187-9) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Alessandro Panarese
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Viale R. Piaggio 34, 56025, Pontedera, Pisa, Italy.
| | - Elvira Pirondini
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| | - Peppino Tropea
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Viale R. Piaggio 34, 56025, Pontedera, Pisa, Italy
| | - Benedetta Cesqui
- Centre of Space Bio-medicine, University of Rome Tor Vergata, Rome, Italy.,Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Federico Posteraro
- Rehabilitation Department Versilia Hospital, AUSL 12, Viareggio, Italy.,Bioengineering Rehabilitation Laboratory, Auxilium Vitae Rehabilitation Centre, Volterra, Italy
| | - Silvestro Micera
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Viale R. Piaggio 34, 56025, Pontedera, Pisa, Italy.,Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| |
Collapse
|
16
|
Dionisio VC, Brown DA. Collaborative robotic biomechanical interactions and gait adjustments in young, non-impaired individuals. J Neuroeng Rehabil 2016; 13:57. [PMID: 27306027 PMCID: PMC4910204 DOI: 10.1186/s12984-016-0166-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Accepted: 06/08/2016] [Indexed: 11/10/2022] Open
Abstract
Background Collaborative robots are used in rehabilitation and are designed to interact with the client so as to provide the ability to assist walking therapeutically. One such device is the KineAssist which was designed to interact, either in a self-driven mode (SDM) or in an assist mode (AM), with neurologically-impaired individuals while they are walking on a treadmill surface. To understand the level of transparency (i.e., interference with movement due to the mechanical interface) between human and robot, and to estimate and account for changes in the kinetics and kinematics of the gait pattern, we tested the KineAssist under conditions of self-drive and horizontal push assistance. The aims of this study were to compare the joint kinematics, forces and moments during walking at a fixed constant treadmill belt speed and constrained walking cadence, with and without the robotic device (OUT) and to compare the biomechanics of assistive and self-drive modes in the device. Method Twenty non-neurologically impaired adults participated in this study. We evaluated biomechanical parameters of walking at a fixed constant treadmill belt speed (1.0 m/s), with and without the robotic device in assistive mode. We also tested the self-drive condition, which enables the user to drive the speed and direction of a treadmill belt. Hip, knee and ankle angular displacements, ground reaction forces, hip, knee and ankle moments, and center of mass displacement were compared “in” vs “out” of the device. A repeated measures ANOVA test was applied with the three level factor of condition (OUT, AM, and SDM), and each participant was used as its own comparison. Results When comparing “in” and “out” of the device, we did not observe any interruptions and/or reversals of direction of the basic gait pattern trajectory, but there was increased ankle and hip angular excursions, vertical ground reaction force and hip moments and reduced center of mass displacement during the “in device” condition. Comparing assistive vs self-drive mode in device, participants had greater flexed posture and accentuated hip moments and propulsive force, but reduced braking force. Conclusions Although the magnitudes and/or range of certain gait pattern components were altered by the device, we did not observe any interruption from the mechanical interface upon the advancement of the trajectories nor reversals in direction of movement which suggests that the KineAssist permits relative transparency (i.e.. lack of interference of movement by the device mechanism) to the individual’s gait pattern. However, there are interactive forces to take into account, which appear to be overcome by kinematic and kinetic adjustments.
Collapse
Affiliation(s)
- Valdeci C Dionisio
- Physical Therapy Course, Federal University of Uberlandia, 1876 Benjamin Constant St, Uberlandia, Minas Gerais, Brazil.
| | - David A Brown
- Department of Physical Therapy, University of Alabama at Birmingham, 1720 2nd Avenue South, Birmingham, AL, 35294, USA
| |
Collapse
|
17
|
Yu N, Xu C, Li H, Wang K, Wang L, Liu J. Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation. SENSORS (BASEL, SWITZERLAND) 2016; 16:E395. [PMID: 26999149 PMCID: PMC4813970 DOI: 10.3390/s16030395] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/01/2016] [Revised: 03/10/2016] [Accepted: 03/11/2016] [Indexed: 01/29/2023]
Abstract
Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs), and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training.
Collapse
Affiliation(s)
- Ningbo Yu
- Institute of Robotics and Automatic Information Systems, Nankai University, Tianjin 300353, China.
- Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300353, China.
| | - Chang Xu
- Institute of Robotics and Automatic Information Systems, Nankai University, Tianjin 300353, China.
- Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300353, China.
| | - Huanshuai Li
- Institute of Robotics and Automatic Information Systems, Nankai University, Tianjin 300353, China.
- Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300353, China.
| | - Kui Wang
- Institute of Robotics and Automatic Information Systems, Nankai University, Tianjin 300353, China.
- Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300353, China.
| | - Liancheng Wang
- Rehabilitation Center, Tianjin Hospital, Tianjin 300211, China.
| | - Jingtai Liu
- Institute of Robotics and Automatic Information Systems, Nankai University, Tianjin 300353, China.
- Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300353, China.
| |
Collapse
|
18
|
Fisher S, Lucas L, Adam Thrasher T. Robot-Assisted Gait Training for Patients with Hemiparesis Due to Stroke. Top Stroke Rehabil 2015; 18:269-76. [DOI: 10.1310/tsr1803-269] [Citation(s) in RCA: 83] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
|
19
|
Maciejasz P, Eschweiler J, Gerlach-Hahn K, Jansen-Troy A, Leonhardt S. A survey on robotic devices for upper limb rehabilitation. J Neuroeng Rehabil 2014; 11:3. [PMID: 24401110 PMCID: PMC4029785 DOI: 10.1186/1743-0003-11-3] [Citation(s) in RCA: 385] [Impact Index Per Article: 38.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2012] [Accepted: 01/03/2014] [Indexed: 11/10/2022] Open
Abstract
The existing shortage of therapists and caregivers assisting physically disabled individuals at home is expected to increase and become serious problem in the near future. The patient population needing physical rehabilitation of the upper extremity is also constantly increasing. Robotic devices have the potential to address this problem as noted by the results of recent research studies. However, the availability of these devices in clinical settings is limited, leaving plenty of room for improvement. The purpose of this paper is to document a review of robotic devices for upper limb rehabilitation including those in developing phase in order to provide a comprehensive reference about existing solutions and facilitate the development of new and improved devices. In particular the following issues are discussed: application field, target group, type of assistance, mechanical design, control strategy and clinical evaluation. This paper also includes a comprehensive, tabulated comparison of technical solutions implemented in various systems.
Collapse
Affiliation(s)
- Paweł Maciejasz
- DEMAR - LIRMM, INRIA, University of Montpellier 2, CNRS, Montpellier, 161 rue Ada, 34095 Montpellier, France
- Institute of Metrology and Biomedical Engineering, Warsaw University of Technology, ul. Św. A. Boboli 8, 02-525 Warszawa, Poland
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstraße 20, 52074 Aachen, Germany
| | - Jörg Eschweiler
- Chair of Medical Engineering (mediTEC), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstraße 20, 52074 Aachen, Germany
| | - Kurt Gerlach-Hahn
- Philips Chair of Medical Information Technology (MedIT), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstraße 20, 52074 Aachen, Germany
| | - Arne Jansen-Troy
- Chair of Medical Engineering (mediTEC), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstraße 20, 52074 Aachen, Germany
| | - Steffen Leonhardt
- Philips Chair of Medical Information Technology (MedIT), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstraße 20, 52074 Aachen, Germany
| |
Collapse
|
20
|
Stienen AHA, Hekman EEG, Prange GB, Jannink MJA, Aalsma AMM, van der Helm FCT, van der Kooij H. Dampace: Design of an Exoskeleton for Force-Coordination Training in Upper-Extremity Rehabilitation. J Med Device 2009. [DOI: 10.1115/1.3191727] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
The Dampace exoskeleton combines functional exercises resembling activities of daily living with impairment-targeted force-coordination training. The goal of this paper is to evaluate the performance of the Dampace. In the design, the joint rotations are decoupled from the joint translations; the robot axes align themselves to the anatomical axes, overcoming some of the traditional difficulties of exoskeletons. Setup times are reduced to mere minutes and static reaction forces are kept to a minimum. The Dampace uses hydraulic disk brakes, which can resist rotations with up to 50 N m and have a torque bandwidth of 10 Hz for multisine torques of 20 N m. The brakes provide passive control over the movement; the patients’ movements can be selectively resisted, but active movement assistance is impossible and virtual environments are restricted. However, passive actuators are inherently safe and force active patient participation. In conclusion, the Dampace is well suited to offer force-coordination training with functional exercises.
Collapse
Affiliation(s)
- Arno H. A. Stienen
- Research Assistant of Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands; Research Associate of Department of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL 60611
| | - Edsko E. G. Hekman
- Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands 7500 AE
| | | | - Michiel J. A. Jannink
- Cluster Manager of Roessingh Research and Development, Enschede, The Netherlands 7522 AH; Assistant Professor of Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands 7500 AE
| | | | - Frans C. T. van der Helm
- Full Professor of Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands 7500 AE; Full Professor of Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands 2600 AA
| | - Herman van der Kooij
- Associate Professor of Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands; Associate Professor of Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands 7500 AE
| |
Collapse
|