Literature DB >> 25838528

An EMG-Controlled Robotic Hand Exoskeleton for Bilateral Rehabilitation.

Daniele Leonardis, Michele Barsotti, Claudio Loconsole, Massimiliano Solazzi, Marco Troncossi, Claudio Mazzotti, Vincenzo Parenti Castelli, Caterina Procopio, Giuseppe Lamola, Carmelo Chisari, Massimo Bergamasco, Antonio Frisoli.   

Abstract

This paper presents a novel electromyography (EMG)-driven hand exoskeleton for bilateral rehabilitation of grasping in stroke. The developed hand exoskeleton was designed with two distinctive features: (a) kinematics with intrinsic adaptability to patient's hand size, and (b) free-palm and free-fingertip design, preserving the residual sensory perceptual capability of touch during assistance in grasping of real objects. In the envisaged bilateral training strategy, the patient's non paretic hand acted as guidance for the paretic hand in grasping tasks. Grasping force exerted by the non paretic hand was estimated in real-time from EMG signals, and then replicated as robotic assistance for the paretic hand by means of the hand-exoskeleton. Estimation of the grasping force through EMG allowed to perform rehabilitation exercises with any, non sensorized, graspable objects. This paper presents the system design, development, and experimental evaluation. Experiments were performed within a group of six healthy subjects and two chronic stroke patients, executing robotic-assisted grasping tasks. Results related to performance in estimation and modulation of the robotic assistance, and to the outcomes of the pilot rehabilitation sessions with stroke patients, positively support validity of the proposed approach for application in stroke rehabilitation.

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Year:  2015        PMID: 25838528     DOI: 10.1109/TOH.2015.2417570

Source DB:  PubMed          Journal:  IEEE Trans Haptics        ISSN: 1939-1412            Impact factor:   2.487


  19 in total

1.  Proposal of a Wearable Multimodal Sensing-Based Serious Games Approach for Hand Movement Training After Stroke.

Authors:  Xinyu Song; Shirdi Shankara van de Ven; Shugeng Chen; Peiqi Kang; Qinghua Gao; Jie Jia; Peter B Shull
Journal:  Front Physiol       Date:  2022-06-03       Impact factor: 4.755

2.  Toward Hand Pattern Recognition in Assistive and Rehabilitation Robotics Using EMG and Kinematics.

Authors:  Hui Zhou; Qianqian Zhang; Mengjun Zhang; Sameer Shahnewaz; Shaocong Wei; Jingzhi Ruan; Xinyan Zhang; Lingling Zhang
Journal:  Front Neurorobot       Date:  2021-05-13       Impact factor: 2.650

Review 3.  A structured overview of trends and technologies used in dynamic hand orthoses.

Authors:  Ronald A Bos; Claudia J W Haarman; Teun Stortelder; Kostas Nizamis; Just L Herder; Arno H A Stienen; Dick H Plettenburg
Journal:  J Neuroeng Rehabil       Date:  2016-06-29       Impact factor: 4.262

4.  Synergistic Myoelectrical Activities of Forearm Muscles Improving Robust Recognition of Multi-Fingered Gestures.

Authors:  Xiuying Luo; Xiaoying Wu; Lin Chen; Yun Zhao; Li Zhang; Guanglin Li; Wensheng Hou
Journal:  Sensors (Basel)       Date:  2019-02-01       Impact factor: 3.576

5.  New Motion Intention Acquisition Method of Lower Limb Rehabilitation Robot Based on Static Torque Sensors.

Authors:  Yongfei Feng; Hongbo Wang; Luige Vladareanu; Zheming Chen; Di Jin
Journal:  Sensors (Basel)       Date:  2019-08-06       Impact factor: 3.576

Review 6.  Effectiveness of Upper Limb Wearable Technology for Improving Activity and Participation in Adult Stroke Survivors: Systematic Review.

Authors:  Jack Parker; Lauren Powell; Susan Mawson
Journal:  J Med Internet Res       Date:  2020-01-08       Impact factor: 5.428

7.  Non-Uniform Sample Assignment in Training Set Improving Recognition of Hand Gestures Dominated with Similar Muscle Activities.

Authors:  Yao Zhang; Yanjian Liao; Xiaoying Wu; Lin Chen; Qiliang Xiong; Zhixian Gao; Xiaolin Zheng; Guanglin Li; Wensheng Hou
Journal:  Front Neurorobot       Date:  2018-02-12       Impact factor: 2.650

8.  A Linear Approach to Optimize an EMG-Driven Neuromusculoskeletal Model for Movement Intention Detection in Myo-Control: A Case Study on Shoulder and Elbow Joints.

Authors:  Domenico Buongiorno; Michele Barsotti; Francesco Barone; Vitoantonio Bevilacqua; Antonio Frisoli
Journal:  Front Neurorobot       Date:  2018-11-13       Impact factor: 2.650

9.  A Finger Grip Force Sensor with an Open-Pad Structure for Glove-Type Assistive Devices.

Authors:  Junghoon Park; Pilwon Heo; Jung Kim; Youngjin Na
Journal:  Sensors (Basel)       Date:  2019-12-18       Impact factor: 3.576

10.  An sEMG-Controlled 3D Game for Rehabilitation Therapies: Real-Time Time Hand Gesture Recognition Using Deep Learning Techniques.

Authors:  Nadia Nasri; Sergio Orts-Escolano; Miguel Cazorla
Journal:  Sensors (Basel)       Date:  2020-11-12       Impact factor: 3.576

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