• Title/Summary/Keyword: Electromyogram (EMG)

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Ergonomic Factors Assessment on Hand Tool Handle (수공구 손잡이의 인간공학적 요소 평가)

  • Yang Sung-Hwan;Cho Mun-Son;Kang Young-Sig
    • Journal of the Korea Safety Management & Science
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    • v.8 no.1
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    • pp.43-52
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    • 2006
  • The goal of this study is to investigate the ergonomic factors in designing or selecting the hand tool handle. Electromyogram (EMG) were measured for various wrist postures and handle sizes under two loading conditions. Anthropometric data were measured and the correlation with EMG measurement data were analyzed. Investigations of this study show that wrist posture should be neutral for minimum muscle tension and optimum handle size can be found by measuring the EMG measurement data. It show that hand width and EMG measurement data is greatly correlated also. This study can be a guide of designing or selecting a hand tool, but further study with large sample sizes and various groups is needed for making general conclusion.

Detection of Hand Motions using Cross-correlation of Surface EMG (표면 EMG신호의 상관함수를 이용한 손의 움직임 검출)

  • Lee, Yong-H.;Choi, Chun-H.;Kim, Soon-S.;Kim, Dong-H.
    • Journal of Biomedical Engineering Research
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    • v.29 no.3
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    • pp.205-211
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    • 2008
  • A method of detecting the specific patterns related to hand motions using the surface EMG(electromyogram) on an arm is proposed and tested. To do this, we obtain separately modeling parameters based on the LP, Prony estimator, and calculate the latency shift value between channels by cross-correlation function. Then, the coefficients and latency shift value are applied to the detection method to classify the EMG signals related to hand motions. Compared with the conventional methods, the present method are more useful to detect the motion intention of the user as an input device in the mobile and wearable computing environments. And, We expect that the results of this study are helpful in the development of rehabilitation devices for the handicapped.

A Study on Muscle Fatigue Changes using AR Model-based Median Frequency in EMG (AR모델을 이용한 중앙주파수의 근피로 변화에 관한 연구)

  • Cho, EunSeuk;Cha, Sam;Lee, Sangsik;Lee, Kiyoung
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.2 no.1
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    • pp.17-22
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    • 2009
  • In this paper, we extract well-known parameters such as zero crossing rate(ZCR), low band energy(Band) and median frequency(MDF) from surface electromyogram (EMG), and compare to evaluate themselves as measures for fatigue. In experiments, 3 males and 3 females volunteered to participate in surface EMG recordings placed on the biceps brachii and each recording experiment continued until exhaustion.

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A Study on Order Decision of AR Model for Median Frequency in Fatiguing EMG (근피로 중앙주파수를 위한 AR모델의 차수결정에 관한 연구)

  • Cho, Eun Seuk;Cha, Sam;Lee, Ki Young
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.3 no.1
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    • pp.8-12
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    • 2010
  • In this paper, we studied on AR model order decision for extraction of EMG median frequency by t-test and ANOVA and comparison of median frequency. And we extracted well-known parameters such as zero crossing rate(ZCR), low band energy(Band) and median frequency(MDF) from surface electromyogram (EMG). And we compared to evaluate themselves as measures for fatigue.

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A Study on EMG Signals Recognition using Time Delayed Counterpropagation Neural Network (시간 지연을 갖는 쌍전파 신경회로망을 이용한 근전도 신호인식에 관한 연구)

  • Kwon, Jangwoo;Jung, Inkil;Hong, Seunghong
    • Journal of Biomedical Engineering Research
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    • v.17 no.3
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    • pp.395-401
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    • 1996
  • In this paper a new neural network model, time delayed counterpropagation neural networks (TDCPN) which have high recognition rate and short total learning time, is proposed for electromyogram(EMG) recognition. Signals the proposed model increases the recognition rates after learned the regional temporal correlation of patterns using time delay properties in input layer, and decreases the learning time by using winner-takes-all learning rule. The ouotar learning rule is put at the output layer so that the input pattern is able to map a desired output. We test the performance of this model with EMG signals collected from a normal subject. Experimental results show that the recognition rates of the suggested model is better and the learning time is shorter than those of TDNN and CPN.

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Virtual reality-based rehabilitation training program using bio-signals and gyro sensors (생체 신호와 자이로 센서를 이용한 가상현실 기반의 재활 훈련 프로그램)

  • Lee, Jaejun;Kim, Ung Gyu;Nasir, Atiqah Binti Muhammad;Lee, Young Jin
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.11a
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    • pp.1031-1033
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    • 2017
  • 본 논문에서는 EMG(Electromyogram) 신호 기반의 재활 치료용 VR(Virtual Reality) 플랫폼을 제안한다. EMG 신호는 근육의 움직임을 확인할 수 있는 생체 신호로, EMG 신호를 활용하면 근육에 직접적인 움직임이 없어도 환자의 행동 의도를 확인할 수 있다. 본 논문에서는 EMG 신호를 이용하여 환자의 근육 움직임을 확인하며, 해당 움직임을 나타내는 VR 콘텐츠에 대한 제안과 실제 제작 콘텐츠를 소개한다. 실험 결과는 실제 근육 움직임에 대한 인식률을 확인하였다.

A Design and Implementation of Detection Module for Repetitive and Successive Muscular Contraction and Relaxation Switch Time in Curl-Dumbbell Exercise through EMG Signal Analysis (EMG 신호 분석을 통한 컬-덤벨 운동의 연속/반복적인 근 수축 및 이완 동작 전환 시점 검출 모듈의 설계 및 구현)

  • Kim, Yi-Seul;Lee, Sun-Yeong;Cho, Jin-Soo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.11a
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    • pp.493-494
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    • 2013
  • 본 논문에서는 컬-덤벨 운동의 연속, 반복적인 근 수축/이완 동작에 대한 전환 시점을 검출하기 위한 EMG(Electromyogram) 신호 분석 모듈을 설계하였으며 이에 대한 안드로이드 플랫폼 기반의 테스트 프로그램을 구현하였다. 제안하는 모듈로는 무산소 운동 분석에의 활용도가 높은 EMG 신호를 기반으로 근 수축/이완의 전환 시점을 95% 검출하며, 이를 개선 및 확장함으로써 현재 상용화 및 보급화된 운동 가이드 시스템에서 제공할 수 없었던 무산소 운동의 체계적 가이드를 제공할 수 있을 것으로 기대된다.

Bayesian Onset Measure of sEMG for Fall Prediction (베이지안 기반의 근전도 발화 측정을 이용한 낙상의 예측)

  • Seongsik Park;Keehoon Kim
    • The Journal of Korea Robotics Society
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    • v.19 no.2
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    • pp.213-220
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    • 2024
  • Fall detection and prevention technologies play a pivotal role in ensuring the well-being of individuals, particularly those living independently, where falls can result in severe consequences. This paper addresses the challenge of accurate and quick fall detection by proposing a Bayesian probability-based measure applied to surface electromyography (sEMG) signals. The proposed algorithm based on a Bayesian filter that divides the sEMG signal into transient and steady states. The ratio of posterior probabilities, considering the inclusion or exclusion of the transient state, serves as a scale to gauge the dominance of the transient state in the current signal. Experimental results demonstrate that this approach enhances the accuracy and expedites the detection time compared to existing methods. The study suggests broader applications beyond fall detection, anticipating future research in diverse human-robot interface benefiting from the proposed methodology.

Effect of Acupuncture (Hapkok, LI-4) Based on Retaining Time on Pain in Rats (침법(鍼法)에 따른 합곡혈(合谷穴) 자극(刺戟)이 동통억제(疼痛抑制)에 미치는 영향(影響))

  • Yun Y.C.;Choi K.J.;Chae W.S.;Na C.S.;Song H.K.
    • Journal of Acupuncture Research
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    • v.15 no.2
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    • pp.319-329
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    • 1998
  • The purpose of this study was finding the pain inhibitory effect of acupuncture based on rataining time at LI -4. The pain at dentes incisor was evoked by noxious electric stimulation and digastric electromyogram(dEMG) changes based on time interval were measured. To do this, the opioid antagonist was administered intraperitoneally and four groups were made for convenience. Without naloxone, dEMG was changed by either retaining the needle for 40 minutes (Group I) or by lifting and thrusting the needle (Group II). With naloxone administration, dEMG was changed by either retaining the needle for 40 minutes (Group III) or by lifting and thrusting the needle (Group IV). The results are as following 1. The pain inhibitory effect of acupuncture at LI -4 was expressed best in Group I. 2. The pain inhibitory effect was somewhat expressed in Group II but the effect was smaller than Group I. 3 .In Groups III and IV, the pain inhibitory effect was not expressed. The overall result should be the foundation for the further studies to figure out the underlying mechanism of acupuncture. In addition, it is assumed that the results will be useful for optimal retaining time of acupucture for its maximal effect.

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Changes in Electromyogram Signals from the Tibialis Anterior Muscle Resulting from Maximal Voluntary Contraction Exercise (최대수의적 수축훈련에 의한 앞 정강근의 근전도 신호의 변화)

  • Song, Su-Young;Hwang, Ki-Kyeong;Kim, Moon-Jeong;Lee, Jeong-Woo
    • Journal of the Korean Academy of Clinical Electrophysiology
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    • v.9 no.2
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    • pp.1-6
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    • 2011
  • Purpose : This study aims to examine changes in electromyogram (EMG) signals detected from the tibialis anterior muscle during repetitive contraction exercises in normal female adults. Methods : The subjects of this study were 10 normal adult females without any musculoskeletal or nervous system disorders. A total of 30 contractions were made repetitively with maximal voluntary contraction exercise for six seconds and a resting time for three seconds. Changes in muscle contractions were measured using dynamometer and EMG signals such as root mean square (RMS), integrated EMG (IEMG), and median frequency (MDF). Results : The result of measurement showed no significant differences in IEMG and RMS in accordance with the increase in the number of contractions. MVIC and MDF showed significant differences in accordance with the increase in the number of contractions (p<0.05). Conclusion : This study demonstrated that repetitive tibialis anterior muscle contraction resulted in a significantly different MVIC and MDF but no significant differences in IEMG and RMS. Therefore, compared to other lower leg muscles, the tibialis anterior muscle is a low-frequency muscle and therefore electrophysiological characteristics of the muscle should be considered in different exercise methods.