Literature DB >> 24187299

A rehabilitation device to improve the hand grasp function of stroke patients using a patient-driven approach.

Wanjoo Park, Wookjin Jeong, Gyu-Hyun Kwon, Yun-Hee Kim, Laehyun Kim.   

Abstract

This paper proposes a robotic hand rehabilitation device for grasp training. The device is designed for stroke patients to train and recover their hand grasp function in order to undertake activities of daily living (ADL). The device consists of a control unit, two small actuators, an infrared (IR) sensor, and pressure sensors in the grasp handle. The advantages of this device are that it is small in size, inexpensive, and available for use at home without specialist's supervision. In addition, a novel patient-driven strategy based on the patient's movement intention detected by the pressure sensors without bio-signals is introduced. Once the system detects a patient's movement intention, it triggers the robotic device to move the patient's hand to form the normal grasping behavior. This strategy may encourage stroke patients to participate in rehabilitation training to recover their hand grasp function and it may also enhance neural plasticity. A user study was conducted in order to investigate the usability, acceptability, satisfaction, and suggestions for improvement of the proposed device. The results of this survey included positive reviews from therapists and a stroke patient. In particular, therapists expected that the proposed patient-driven mode can motivate patients for their rehabilitation training and it can be effective to prevent a compensational strategy in active movements. It is expected that the proposed device will assist stroke patients in restoring their grasp function efficiently.

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Mesh:

Year:  2013        PMID: 24187299     DOI: 10.1109/ICORR.2013.6650482

Source DB:  PubMed          Journal:  IEEE Int Conf Rehabil Robot        ISSN: 1945-7898


  2 in total

1.  Hand Rehabilitation and Telemonitoring through Smart Toys.

Authors:  N Alberto Borghese; Jacopo Essenziale; Renato Mainetti; Elena Mancon; Rossella Pagliaro; Giorgio Pajardi
Journal:  Sensors (Basel)       Date:  2019-12-13       Impact factor: 3.576

Review 2.  The Three Laws of Neurorobotics: A Review on What Neurorehabilitation Robots Should Do for Patients and Clinicians.

Authors:  Marco Iosa; Giovanni Morone; Andrea Cherubini; Stefano Paolucci
Journal:  J Med Biol Eng       Date:  2016-02-09       Impact factor: 1.553

  2 in total

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