• Title/Summary/Keyword: 손목재활로봇

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Design of a Six-axis Force/moment Sensor for Wrist Twist-exercise Rehabilitation Robot (손목회전운동 재활로봇을 위한 6축 힘/모멘트센서 설계)

  • Kim, Hyeon Min;Kim, Gab Soon
    • Journal of the Korean Society for Precision Engineering
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    • v.30 no.5
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    • pp.529-536
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    • 2013
  • Most serious stroke patients have the paralysis on their wrists, and can't use their hands freely. But their wrists can be recovered by rehabilitation exercises. Recently, professional rehabilitation therapeutists help stroke patients exercise their wrists in hospital. But it is difficult for them to rehabilitate their wrists, because the therapeutists are much less than stroke patients in number. Therefore, the wrist twist-exercise rehabilitation robot that can measure the twist force of the patients' wrists is needed and developed. In this paper, the six-axis force/moment sensor was designed appropriately for the robot. As a test result, the interference error of the six-axis force/moment sensor was less than 0.85%. It is thought that the sensor can be used to measure the wrist twist force of the patient.

Development of a Data Glove for Rehabilitation Robot for Upper Extremity Paralysis (상지마비 재활훈련로봇용 데이터글로브의 개발)

  • Park, C.Y.;Moon, I.H.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.2 no.1
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    • pp.45-49
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    • 2009
  • This paper proposes a data glove for a rehabilitation robot interface for the upper extremity paralysis. The designed data glove uses seven flexible sensors so as to measure the flexion angles of fingers and wrist. We verified the performance of the data glove using a 3D graphic interface developed. The experimental results show that the proposed data glove is feasible to sense hand motions and applicable to the robot interface.

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Analysis of Upper Limb Movement Using Bio-Impedance (임피던스를 이용한 상지 운동 분석)

  • Kim, Soo-Chan;Nam, Ki-Chang;Kim, Deok-Won
    • Proceedings of the KIEE Conference
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    • 2001.11c
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    • pp.461-464
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    • 2001
  • 본 연구에서는 생체 임피던스를 이용하여 3채널 상지(upper arm) 운동 분석 시스템을 제작하였다. 각 채널은 상지의 외전(supination)과 내전(pronation), 팔꿈치(elbow)의 폄과 굽힘, 손목(wrist)의 평과 굽힘에 따른 각 관절의 임피던스 변화를 얻을 수 있도록 설계되었다. 상체 임피던스는 전극의 부착위치에 의존하므로 정밀한 감지를 위해 상지 운동에 대한 임피던스의 변화와 각도계(goniometer)의 각도 변화와의 상관관계를 통하여 상관 관계가 높고, 변화량이 가장 크고 다른 관절의 움직임에 따른 영향이 최소인 곳을 찾아 이를 최적의 전극 위치로 정하였다. 그리고, 선정된 최적의 전극 위치에서 임피던스 변화를 얻어 상지 운동을 분석해 보았다. 최적의 전극 위치에서 손목과 팔꿈치의 각도 변화와 임피던스 변화의 상관 계수는 각각 0.94, -0.97로 아주 높은 상관 관계를 보였다. 또한 이전의 다른 연구에서 임피던스 방법으로 구현해 본적이 없는 팔의 회전(rotation)도 분석이 가능하였다. 이 시스템은 피검자의 동작에 거의 제한을 주지 않고, 가벼우며, 장시간 측정이 용이할 뿐만 아니라 시스템 구성이 영상 분석기에 비해서 단순하다는 장점을 가지고 있다. 본 연구에서 제안하는 방법은 재활과 생체역학, 로봇의 원격 제어, 그리고 가상 현실에서의 동작 구현 등에 활용 할 수 있을 것으로 사료된다.

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Design of a Three-Axis Force Sensor for Wrist Bending-Exercise Rehabilitation Robot (손목굽힘운동 재활로봇을 위한 3축 힘센서 설계)

  • Kim, Gab-Soon
    • Journal of Sensor Science and Technology
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    • v.22 no.2
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    • pp.118-123
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    • 2013
  • Most serious stroke patients have the paralysis of their wrists, and can't use of their hands freely. But their wrists can be recovered by rehabilitation exercise. Recently, professional rehabilitation therapeutists exercise the wrists of stroke patients in hospital. But the wrists of stroke patients have not rehabilitated, because the therapeutists are much less than stroke patients in number. Therefore, the wrist bending-exercise rehabilitation robot that can measure the bending force of the patients' wrists is developed. In this paper, the three-axis force sensor was designed for the wrist bending-exercise rehabilitation robot. As a test results, the interference error of the three-axis force sensor was less than 0.85%. It is thought that the sensor can be used to measure the wrist bending force of the patient.

Development of a Wrist Bending Rehabilitation Robot with a Three-axis Force Sensor (3축 힘 센서가 적용된 손목 굽힘 재활로봇 개발)

  • Kim, Gab-Soon
    • Journal of Sensor Science and Technology
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    • v.25 no.1
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    • pp.27-34
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    • 2016
  • This paper describes the development of a rehabilitation robot that can provide wrist bending exercise to a severe stroke patient staying in a bed ward or at home. The developed rehabilitation robot has a three-axis force sensor which detects three directional force Fx, Fy, and Fz. The sensor measures a bending force (Fz) exerted on the wrist and the signal force (Fx and Fy) which can be used for the safety purpose. The robot was designed for severe stroke patients in bed, and the robot program was developed to perform a wrist bending rehabilitation exercise. In our tests including a nine-day experimental exercise, the developed force sensor-based robot operated effectively and safely.