• 제목/요약/키워드: muscle activation sensor

검색결과 29건 처리시간 0.033초

물리적 인간 기계 상호작용을 위한 근육의 기하학적 형상 변화를 이용한 상지부 움직임 예측 (Prediction of the Upper Limb Motion Based on a Geometrical Muscle Changes for Physical Human Machine Interaction)

  • 한효녕;김정
    • 제어로봇시스템학회논문지
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    • 제16권10호
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    • pp.927-932
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    • 2010
  • Estimation methods of motion intention from bio-signal present challenges in man machine interaction(MMI) to offer user's command to machine without control of any devices. Measurements of meaningful bio-signals that contain the motion intention and motion estimation methods from bio-signal are important issues for accurate and safe interaction. This paper proposes a novel motion estimation sensor based on a geometrical muscle changes, and a motion estimation method using the sensor. For estimation of the motion, we measure the circumference change of the muscle which is proportional to muscle activation level using a flexible piezoelectric cable (pMAS, piezo muscle activation sensor), designed in band type. The pMAS measures variations of the cable band that originate from circumference changes of muscle bundles. Moreover, we estimate the elbow motion by applying the sensor to upper limb with least square method. The proposed sensor and prediction method are simple to use so that they can be used to motion prediction device and methods in rehabilitation and sports fields.

웨어러블 컴퓨팅을 위한 근전도 센서 시스템의 설계 및 구현 (Design and Implementation of Electromyographic Sensor System for Wearable Computing)

  • 이영석
    • 한국정보전자통신기술학회논문지
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    • 제11권1호
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    • pp.114-120
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    • 2018
  • 본 논문에서는 근전도 신호 획득 및 분석을 위한 웨어러블 디바이스용 센서 시스템을 구현하였다. 구현된 시스템의 성능은 임상용 근전도 시스템에서 획득된 근전도 신호와 근피로도 및 근활성도의 상관성 분석에 의해 평가되었으며 실측된 소비 전력이 상용 근전도 시스템들과 비교되었다. 5명의 피실험자들의 이두박근 및 삼두박근에서 수집된 근전도 신호를 통한 실험에서, 구현된 시스템이 임상용 근전도 센서 시스템과 근피로도는 1.1~1.4의 상관성을, 근활성도는 약 1.0의 강한 양의 상관 경향성을 보여주었다. 또한 소비전력의 비교에서 구현된 시스템의 소비전력이 상용 근전도 시스템보다 25%~50%의 감소하였다.

근 부피 센서를 이용한 인체 팔꿈치 관절의 동작 토크 추정 (Torque Estimation of the Human Elbow Joint using the MVS (Muscle Volume Sensor))

  • 이희돈;임동환;김완수;한정수;한창수;안재용
    • 한국정밀공학회지
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    • 제30권6호
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    • pp.650-657
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    • 2013
  • This study uses a muscle activation sensor and elbow joint model to develop an estimation algorithm for human elbow joint torque for use in a human-robot interface. A modular-type MVS (Muscle Volume Sensor) and calibration algorithm are developed to measure the muscle activation signal, which is represented through the normalization of the calibrated signal of the MVS. A Hill-type model is applied to the muscle activation signal and the kinematic model of the muscle can be used to estimate the joint torques. Experiments were performed to evaluate the performance of the proposed algorithm by isotonic contraction motion using the KIN-COM$^{(R)}$ equipment at 5, 10, and 15Nm. The algorithm and its feasibility for use as a human-robot interface are verified by comparing the joint load condition and the torque estimated by the algorithm.

Active training machine with muscle activity sensor for elderly people

  • Matsuda, Goichi;Tanaka, Motohiro;Yoon, Sung-Jae;Ishimatsu, Takakazu;Kim, Seok-Hwan;Moromugi, Shunji
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1169-1172
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    • 2005
  • For elderly people, an advanced training machine that uses actuator and can adjust load according to muscle activity is proposed. The proposed machine allows users to have a safe and effective training through exercise close to ordinal motion appears in daily life such as stretching or stooping motion. A muscle activity sensor real-timely monitors the activation level of user's muscle during the exercise and the training load is adjusted based on the measured data. The training load is exerted and continuously controlled by electric/pneumatic actuator.

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Effects of the Additional Scapular Posterior Tilt Movement on Selective Muscle Activation of the Lower Trapezius during Prone Shoulder Extension

  • Kim, Sooyong;Kang, Minhyeok
    • 국제물리치료학회지
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    • 제12권2호
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    • pp.2308-2313
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    • 2021
  • Background: Although the scapular posterior tilt movement could facilitate the lower trapezius (LT) muscle activity, no study identified the effects of the scapular posterior tilt movement on the selective activation of the LT muscle during prone shoulder extension. Objectives: To examine the influences of additional scapular posterior tilt on electromyography (EMG) of the upper trapezius (UT) and the LT muscles during prone shoulder extension. Design: Cross-sectional study. Methods: There were 15 asymptomatic male participants in this study who performed prone shoulder extension with and without scapular posterior tilt movements. For the scapular posterior tilt movements, participants performed visual biofeedback training for scapular movement using motion sensor. During the exercises, the EMG activity of the UT and LT was recorded using surface EMG system. Results: The EMG activity of the LT significantly increased during prone shoulder extension with scapular posterior tilt compared to that of general prone shoulder extension, whereas that of the UT was not significantly different between the two exercises. Moreover, scapular posterior tilt application significantly decreased UT/LT muscle activity ratio. Conclusion: Scapular posterior tilt movement may be emphasized during exercise when facilitating LT muscle activation.

인간-기계 인터페이스를 위한 근 부피 센서 개발 (Development of the MVS (Muscle Volume Sensor) for Human-Machine Interface)

  • 임동환;이희돈;김완수;한정수;한창수;안재용
    • 한국정밀공학회지
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    • 제30권8호
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    • pp.870-877
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    • 2013
  • There has been much recent research interest in developing numerous kinds of human-machine interface. This field currently requires more accurate and reliable sensing systems to detect the intended human motion. Most conventional human-machine interface use electromyography (EMG) sensors to detect the intended motion. However, EMG sensors have a number of disadvantages and, as a consequence, the human-machine interface is difficult to use. This study describes a muscle volume sensor (MVS) that has been developed to measure variation in the outline of a muscle, for use as a human-machine interface. We developed an algorithm to calibrate the system, and the feasibility of using MVS for detecting muscular activity was demonstrated experimentally. We evaluated the performance of the MVS via isotonic contraction using the KIN-COM$^{(R)}$ equipment at torques of 5, 10, and 15 Nm.