• 대한물리치료과학회지
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• 제10권1호
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• pp.83-89
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• 2003

An electromyogram (EMG) using surface electrodes is one of the indirect tests most frequently used to ascertain muscle fatigue. An EMG can be used in two ways. The first technique determines the root mean square (RMS), which reflects the amplitude of the EMG signal. The second technique determines the median and mean power frequencies through EMG power spectrum analysis. The purpose of this article is for determine the correlation between work and percent root mean square(%RMS) and between work and MDF of EMG based on muscle contractions. It is used the %RMS, which reflects the amplitude of the EMG signal For MDF, it is used the frequency power spectrum analysis method, which involves the fast Fourier transformation (FFT) of the original Signals.

• 한국HCI학회논문지
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• 제10권2호
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• pp.21-26
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• 2015

NUI(Natural User Interface)는 사용자의 자연스러운 동작이나 동작 시 발생하는 생체 신호를 해석하여 기계에 명령을 내리는 것을 말한다. 물리적인 변화가 있어야 사용이 가능한 가속도 센서나 영상 기반의 NUI와는 달리 특정 동작과 관련된 근육의 표면 근전도(surface Electromyogram, sEMG)를 측정하면 실제 움직임이 발생하지 않아도(isometric contraction) 동작 의도를 예측할 수 있다. 본 연구에서는 근전도 기반으로 손목 동작 의도를 분류할 때 전극 개수에 따른 정확도를 확인하고, 키보드 등에 적용 가능한 인터페이스 기술을 제안한다. 손목의 동작 중 신전(extension, up), 굴곡(flexion, down), 외전(abduction, right), 내전(adduction, left)의 네 가지 동작 의도를 분류하는 실험을 진행하였다. 50ms 간격으로 계산된 제곱평균제곱근(Root Mean Square, RMS)을 특징으로 사용하였고, 동작 의도 인식을 위해 역전파 알고리즘으로 학습한 다층 퍼셉트론 분류기를 사용하였다. 전극 쌍의 개수를 네 개(91.9%), 세 개(87.0%), 두 개(78.9%)로 줄여가며 정확도를 확인했다. 전극 쌍의 개수가 네 개에서 두 개로 줄었을 때 정확도는 약 13% 감소하였다. 두 쌍의 전극만 사용하는 경우의 분류 정확도를 높이기 위하여 직전의 RMS를 특징에 추가하였다. 150 ms 이전까지의 정보를 사용하였을 때, 분류 정확도가 78.9%에서 83.6%로 4.6% 증가하였다. 전극 쌍의 개수가 감소함에 따라 정확도는 감소하였지만, 이전 데이터를 함께 사용한 경우 부분적으로 증가 시킬 수 있음을 확인하였다.

• 감성과학
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• 제11권3호
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• pp.357-364
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• 2008

본 연구에서는 반복적인 동작 행위에 따른 뇌파의 훈련효과를 규명하고자 한다. 훈련 효과를 검증하기 위해 반복적인 동작시의 뇌파 출현량 및 EMG와 EEG의 coherence의 변화를 분석하였다. 피실험자는 5명으로 실험 시간은 총 48분이며, 반복 일에 대한 훈련 효과를 살펴보기 위해 5일간 진행하였다. 반복적인 동작은 손을 오므렸다 폈다 하는 행위로, 5초간의 동작실행과 10초간의 휴식시간으로 나눠 실험하였다. 동작 유무와 반복 일에 따른 뮤파와 베타파량의 차이를 살펴 본 결과, 반복시간에 따라 뮤파 및 베타파량이 증가되는 경향이 있었다. 그러나 5일 동안의 반복 일에 따른 훈련효과는 보이지 않았다. 또한 EMG와 EEG의 coherence는 반복 시간과 반복 일에 대한 훈련 효과를 확인할 수 없었다.

• 대한의용생체공학회:의공학회지
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• 제40권6호
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• pp.223-229
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• 2019

The number of knee-related disease patients and knee joint surgeries is steadily increasing every year, and for knee rehabilitation training for these knee joint patients, it is necessary to strengthen the muscle of vastus medialis and quadriceps femoris. However, because of the cost and time-consuming difficulties of receiving regular hospital treatment in the course of knee rehabilitation, we developed knee exoskeleton using rapid prototype for knee rehabilitation with feedback from the electromyogram (EMG) and inertia motion unit (IMU) sensor. The modules was built on the basis of EMG and an IMU sensor applied complementary filter, measuring muscle activity in the vastus medialis and the range of joint operation of the knee, and then performing the game based on this measurement. The IMU sensor performed up to 97.2% accuracy in experiments with ten subjects. The functional game contents consisted of an exergaming platform based on EMG and IMU for the real-time monitoring and performance assessment of personalized isometric and isotonic exercises. This study combined EMG and IMU-based functional game with knee rehabilitation training to enable voluntary rehabilitation training by providing immediate feedback to patients through biometric information, thereby enhancing muscle strength efficiency of rehabilitation.

• 한국정밀공학회지
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• 제31권11호
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• pp.1051-1058
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• 2014

In this study, we investigated the improvement effect of obesity by treatment with a developed low frequency electrical stimulation system. Thirty female in their 20's as an experiment subjects divided 3 groups(control, commercialized device, developed device) were treated with electrical stimulation on abdomen for 4 weeks. The body weight, body mass index(BMI), waist-hip ratio(WHR), muscle strength, muscle(transverse abdominis(TrA), internal obliquus abdominis(IO), external obliquus abdominis(EO)), fat thickness and abdominal surface temperature were measured by electromyogram(EMG), ultrasound and digital infrared thermal image(DITI). In the result, the body weight and BMI were decreased. Subcutaneous abdominal fat were significantly reduced after 4 weeks. The muscle strength and TrA muscle thickness was increased 13.2%(p<0.05), and 35.5%, respectively. The fat thickness showed decrease in abdomen (p<0.05). Infrared measurement on abdominal surface temperature as a parameter of improvement in blood circulation was significantly increased(p<0.05). Therefore, the low frequency stimulation showed positive effects on parameters of the obesity improvement.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1588-1593
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• 2008

This paper describes a real-time isometric pinch force prediction algorithm from surface electromyogram (sEMG) using multilayer perceptron (MLP) for human robot interactive applications. The activities of seven muscles which are observable from surface electrodes and also related to the movements of the thumb and index finger joints were recorded during pinch force experiments. For the successful implementation of the real-time prediction algorithm, an off-line analysis was performed using the recorded activities. Four muscles were selected for the force prediction by using the Fisher linear discriminant analysis among seven muscles, and the four muscle activities provided effective information for mapping sEMG to the pinch force. The MLP structure was designed to make training efficient and to avoid both under- and over-fitting problems. The pinch force prediction algorithm was tested on five volunteers and the results were evaluated using two criteria: normalized root mean squared error (NRMSE) and correlation (CORR). The training time for the subjects was only 2 min 29 sec, but the prediction results were successful with NRMSE = 0.112 ${\pm}$ 0.082 and CORR = 0.932 ${\pm}$ 0.058. These results imply that the proposed algorithm is useful to measure the produced pinch force without force sensors in real-time. The possible applications include controlling bionic finger robot systems to overcome finger paralysis or amputation.

• PNF and Movement
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• 제10권4호
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• pp.25-31
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• 2012

Purpose : The purpose of present study was to investigate the effects of proprioceptive neuromuscular facilitation (PNF) lifting on contralateral leg muscle activities in a seated position. Methods : Twenty healthy subjects were recruited for this study. Lifting was performed from each of the three position. An surface electromyogram (EMG) was used to record the EMG activities from vastus medialis (VM), biceps femoris (BF), tibialis anterior (TA), and gastrocnemius medialis (GM) in contralateral leg muscle. The data were analyzed using a repeated measures of one-way analysis of variance (ANOVA) with post-hoc Bonferroni's correction to determine the statistical significance. Results : The results of this study were summarized as follows: In comparison to the start position, percentage maximal voluntary isometric contraction (%MVIC) values of the VM, TA and GM demonstrated a significantly higher activities in the end position(p<.05). Conclusion : The result shows that contralateral leg muscles activities significantly more increase in the end position when PNF lifting was applied. Therefore, this study will be used to prove effect of indirect approach for the stability and strengthening in patients with leg impairments.

• 대한의용생체공학회:의공학회지
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• 제27권3호
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• pp.101-109
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• 2006

It has been known that there is strong relationship between human voices and the movements of the articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The EMG signals were acquired from three articulatory facial muscles. Preliminary, 10 Korean digits were used as recognition variables. The various feature parameters including filter bank outputs, linear predictive coefficients and cepstrum coefficients were evaluated to find the appropriate parameters for EMG-based speech recognition. The sequence of the EMG signals for each word is modelled by a hidden Markov model (HMM) framework. A continuous word recognition approach was investigated in this work. Hence, the model for each word is obtained by concatenating the subword models and the embedded re-estimation techniques were employed in the training stage. The findings indicate that such a system may have a capacity to recognize speech signals with an accuracy of up to 90%, in case when mel-filter bank output was used as the feature parameters for recognition.

• 대한기계학회논문집B
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• 제37권12호
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• pp.1121-1127
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• 2013

본 논문은 인체 견관절의 재활훈련을 위하여 견관절 근육에서 근전도를 측정하고 기능적 전기자극을 인가하는 실험적 연구를 다룬다. 견관절 근골격계의 구성 및 운동형상과 주요 기능을 토대로, 시상면 운동에서 주요 역할을 하는 견관절 근육을 실험대상으로 선정하였다. 첫 번째 실험으로 관절 각도에 따른 주요 근육의 표면근전도를 측정하였다. 관절 각도 변화와 표면면근전도 변화가 선형 비례하는 경향이 나타났다. 두 번째 실험으로 견관절 근육에 기능적 전기자극을 인가하면서 관절 각도를 측정하였다. 전기자극의 일정 범위에서 자극 전류 증가에 따라 관절 각도가 증가하는 경향이 나타났다. 능동형 재활훈련의 방안으로, 근전도 측정에 의해 근육의 운동의지를 감지하고 기능적 전기자극으로 근육의 장력 발생을 보조하는 게 가능함을 확인하였다.

• 한국소음진동공학회논문집
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• 제21권10호
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• pp.934-939
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• 2011

This paper experimentally deals with the relationship between the ankle electromyogram(EMG) and walking motion in order to activate the ankle joint of a walking-assistance robot for rehabilitation. Based on the anatomical structure and motion pattern of an ankle joint, major muscles were selected for EMG measurements. Surface EMG signals were monitored for several human bodies at various stride distances and stride frequencies. Root-mean-squared magnitude of EMG signals were related with the walking conditions. It appeared that the magnitude of the ankle EMG signal was linearly proportional to the stride distance and stride frequency, and thus to the walking speed.