• 한국의류산업학회지
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• 제18권6호
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• pp.755-765
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• 2016

Recently, interest in monitoring health and sports is growing because of the emphasis on wellness, which is accelerating the development and commercialization of smart clothing for biosignal monitoring. In addition to exerciseeffect monitoring clothing that tracks heart rate and respiration, recently developed clothing makes it possible to monitor muscle balance using electromyogram (EMG). The electrode for EMG have to attached to an accurate location in order to obtain high-quality signals in surface EMG measurement. Therefore, this study develops monitoring clothing suitable for different types of human bodies and aims to extract suitable range of EMG according to movements in order to develop self-fitness monitoring clothing based on EMG measurement. This study identified and attached electrodes on six upper muscles and two lower muscles of ten males in their 20s. After selecting six main motions that create a load on muscles, the 8-ch wireless EMG system was used to measure amplitude value, noise, SNR and SNR (dB) in each part and statistical analysis was conducted using SPSS 20.0. As a result, the suitable range for EMG measurement to apply to clothing was identified as four parts in musculus pectoralis major; three parts in muscle rectus abdominis, two parts each in shoulder muscles, backbone erector, biceps brachii, triceps brachii, and musculus biceps femoris; and four part in quadriceps muscle of thigh. This was depicted diagrammatically on clothing, and the EMG-monitoring sensing locations were presented for development of self-fitness monitoring.

• 센서학회지
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• 제12권2호
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• pp.88-94
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• 2003

근전도는 근육의 수축을 관장하는 신경다발의 전기적 흥분에 의해 생기는 생체전기신호이다. 따라서 근육운동에 따라 발생하는 근전도 신호를 측정, 분석하면 운동기능의 정상여부를 판단할 수 있을 뿐 아니라 사용자의 동작에 의해 컴퓨터나 전자장치를 작동시키는 인간-기계 인터페이스(man-machine interface)용 입력신호로도 사용할 수 있다. 본 연구에서는 사용자의 일상생활에서의 자연스러운 동작과 관련된 근전도 신호를 측정할 수 있는 소형의 무선 생체신호 측정시스템을 개발하였다. 기존의 근전도 측정 시스템에서 전극과 증폭기 사이에 존재하는 전선은 동적잡음의 원인이 되고 사용자의 동작을 방해할 수 있으므로 소형의 증폭회로를 전극 바로 위에 일체형으로 제작하였고 증폭기와 컴퓨터 사이에 무선 데이터 전송을 사용하여 사용자의 일상적인 원활한 동작을 가능케 하였다. 개발된 측정 시스템의 크기는 $60{\times}40{\times}25mm$이고 무게는 100g이다. 개발된 시스템에 대한 성능 평가결과 컴퓨터를 위한 새로운 인터페이스 장치, 운동선수의 훈련결과 분석, 환자의 재활훈련 성과 측정 그리고 가상현실 입력장비 등의 용도로 사용될 수 있음을 확인하였다.

• 대한치과보철학회지
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• 제24권1호
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• pp.165-176
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• 1986

The purpose of this study was to investigate electromyographically the relationship between preferred chewing side and side of initial muscle pains. In this study, 20 normal healthy subjects were selected , and each subject chewed randomly chewing gum for 20 minutes to establish preferred chewing side. To induce initial muscle pains, biting force of 10Kg on the gnathodynamometer was maintained by the subjects. And the Bioelectric processor EM2(Myo-Ironies Research, Inc. U.S.A.) with the surface electrodes was used to record the EMG activity during all experimental procedures. The results were as follows; 1. A majority of the present subjects (60%) had a preferred chewing side, but with few exceptions, subjects were unable to explain why a given side was preferred; explanations were only 'comfort' and 'habit' 2. The chewing, or working side was determined largely by the mean voltage of the surface electromyogram (EMG); in comparison with EMG from the non-wlring (contralateral) side, the working (ipsilateral) side showed a higher amplitude. 3. After the effort, the right masseter muscle is the most frequent site of pains, followed by the left masseter muscle, the anterior part of the right temporalis muscle and tile anterior part of the left temporalis muscle. 4. After the effort, mean voltages of masseter muscles were slightly increased, but mean voltages of temporalis anterior were slightly decreased at physiologic rest position. 5. No relationships could be established between preferred chewing side and side of initial muscle pains.

• PNF and Movement
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• 제9권3호
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• pp.11-17
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• 2011

Purpose : The purpose of this study was to analyze the effects of proprioceptive neuromuscular facilitation (PNF) leg flexion patterns according to the hip joint angle on electromyographic activity of the trunk. Methods : Thirty healthy adults volunteered to participate in this study. Subjects were required to complete following the PNF leg flexion patterns on three different hip joint flexion $30^{\circ}$, $60^{\circ}$ and $90^{\circ}$. An surface electromyogram (SEMG) was used to record the electromyographic activities of the trunk muscle in rectus abdominis, internal oblique abdominal, external oblique abdominal, erector spinae. The data were analyzed using the a repeated measures of one-way ANOVA with post-hoc Bonferroni's correction. Result : The results of this study are summarized as follows: The EMG activities of internal abdominal oblique and elector spinae muscle showed a statistically significant difference (p<.05). Conclusion : The result show that electromyographic activity of the trunk muscles significantly changed on PNF leg flexion patterns with difference hip joint angle. Therefore, this study used to basis for the intervention of the trunk muscle strength and stabilization.

• Transactions on Control, Automation and Systems Engineering
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• 제4권1호
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• pp.49-55
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• 2002

A decrease in the birthrate and aging are progressing in Japan and several countries. In that society, it is important that physically weak persons such as elderly persons are able to take care of themselves. We have been developing exoskeletal robots for human (especially for physically weak persons) motion support. In this study, the controller controls the angular position and impedance of the exoskeltal robot system using multiple fuzzy-neuro controllers based on biological signals that reflect the human subject's intention. Skin surface electromyogram (EMG) signals and the generated wrist force by the human subject during the elbow motion have been used as input information of the controller. Since the activation level of working muscles tends to vary in accordance with the flexion angle of elbow, multiple fuzzy-neuro controllers are applied in the proposed method. The multiple fuzzy-neuro controllers are moderately switched in accordance with the elbow flexion angle. Because of the adaptation ability of the fuzzy-neuro controllers, the exoskeletal robot is flexible enough to deal with biological signal such as EMG. The experimental results show the effectiveness of the proposed controller.

• 한국정밀공학회지
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• 제25권3호
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• pp.141-146
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• 2008

The purpose of this study is to develop the algorithm which can control muscle power assist robot especially for elderly. Recently, wearable robots for power assistance are developed by many researchers, and its application fields are also variable such as for medical or military equipment. However, there are many technical barriers to develop the wearable robot. This study suggest a control method improving performance of a wearable robot system by using a EMG signal of major muscles and a force sensor signal as command signal of system. The result of the robot Prototype efficiency experiment, the case of Maximum Isometric motion it suggest 100% power of muscle, the man need only 66% of MVIC(Maximum Voluntary Isometric Contraction) to lift 5kg dumbbell without robot assist. However the man needs only 52% of MVIC to lift 5kg dumbbell with robot assist. Therefore 20% muscle power increased with robot assist. Also, we designed light weight robot mechanism that extract the command signal verified and drive the wanted motions.

• 한국전문물리치료학회지
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• 제14권4호
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• pp.21-27
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• 2007

The purposes of this study were to compare core muscle activities with and without the use of Pilates resistive equipment during bridging exercises and to investigate the efficacy of a Pilates device. Fourteen healthy individuals (6 males, 8 females) between 20 to 26 years of age were examined. They were engaged in a bridging exercise with and without a magic circle. Three consecutive repetitions of each exercise were performed. Surface electromyography (sEMG) was used to measure the electrical activities of the right side internal oblique, the adductor longus, the multifidus, and the gluteus maximus muscles. Normalized EMG activities were compared using a paired t-test and the level of significance was set at =.05. The results showed that the EMG activities of the internal oblique (p=.0078), the adductor longus (p=.0007), and the gluteus maximus (p=.0001) muscles were significantly higher when using the magic circle during the Pilates bridging exercise. Also, statistically significant change existed in the multifidus muscle (p=.0106). The bridging exercise, combined with hip adduction using the magic circle, may enhance core stabilization. Therefore, using a magic circle during hip adduction combined with bridging exercise may be recommended usefully for individuals wanting to strength the core muscles. Further research is needed to access the nature of motor control of the Pilates mat exercises and to deliver exercise intervention for lower back pain patients.

• 대한의용생체공학회:의공학회지
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• 제16권2호
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• pp.157-166
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• 1995

The Electroencephalogram (EEG) and evoked potential (EP) t;ave widely been used for study of brain functions. The EEG and EP signals acquired from multi-channel electrodes placed on the head surface are often interfered by other relatively large physiological signals such as electromyogram (EMG) or electroculogram (EOG). Since these artifact-affected EEG signals degrade EEG mapping, the removal of the artifact-affected EEGs is one of the key elements in neuro-functional mapping. Conventionally this task has been carried out by human experts spending lots of examination time. In this paper a neural-network based classification is proposed to replace or to reduce human expert's efforts and time. From experiments, the neural-network based classification performs as good as human experts : variation of decisions between the neural network and human expert appears even smaller than that between human experts.

• 한국운동역학회지
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• 제21권4호
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• pp.429-436
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• 2011

In this study, we have experimented with 9 players at the national delegate level. Although there were some differences in the average effects of 3 types of one-two straight movements after the application of wheel axle, there were no statistical differences in the case of surface reacting forces, electromyograms, and impact forces. When the right fist was impacted using the one-two straight movements and the wheel axle was applied with 3 segmentations, high impact forces were obtained for the pronation in the following order-72.01 $m/s^2$ (type 2), 70.93 $m/s^2$ (type 3), and 58.19 $m/s^2$ (type 1). Higher values of the surface reacting force were found for type 1 that did not exhibit pronation in the left foot, whereas in the case of the vertical direction of the right foot, type 2 with pronation exhibited higher values and impact forces. In the right electromyogram, high impact forces due to the activation of the muscular electric potential were obtained for lumbar erector (LE) spinae and triceps brachii (TB) with type 1; LE spina, latissimus dosi (LD), and upper trapezius (UT) with type 2; and brachioradialis (BR), UT, and rectus abdominal (RA) with type 3. Due to pronation and complex motions of the 3 pronation segmentations, the efficiency was higher for impacts due to one-two straight movements.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1995년도 춘계학술대회
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• pp.160-163
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• 1995

An optimal EEG and artifact classifier is proposed using neural network operating characteristics. The neural network operating characteristics are two dimensional parametric representations of the right and false identification probabilities of the network classifier. Since the EEG and EP signals acquired from multi -channel electrodes placed on the head surface are often interfered by other relatively large physiological signals such as electromyogram (EMG) or electroculogram (EOG), the removal of the artifact-affected EEGs is one of the key elements in neuro-functional mapping. Conventionally this task has been carried out by human experts spending lots of examination time. Using the neural-network based classification, human expert's efforts and time can be substantially reduced. From experiments, the neural-network based classification performs as good as human experts: variation of decisions between the neural network and human expert appears even smaller than that between human experts.