• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.379-386
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• 1996

This paper describes an approach for classifying myoelectric patterns using a multilayer perceptrons (MLP's) and hidden Markov models (HMM's) hybrid classifier. The dynamic aspects of EMG are important for tasks such as continuous prosthetic control or vari- ous time length EMG signal recognition, which have not been successfully mastered by the most neural approaches. It is known that the hidden Markov model (HMM) is suitable for modeling temporal patterns. In contrasts the multilayer feedforward networks are suitable for static patterns. Ank a lot of investigators have shown that the HMM's to be an excellent tool for handling the dynamical problems. Considering these facts, we suggest the combination of MLP and HMM algorithms that might lead to further improved EMG recognition systems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.358-363
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• 1992

A two-dimensional static biomechanical model of lower extremity in the seated posture was developed to assess muscular activities of lower extremity required for a variety of foot pedal operations. Muscle forces of the model were predicted using the double linear optimization scheme. For the model validation, three subjects performed the experiments which measured EMG activities of six lower extremity muscles. Predicted muscle forces were compared with the corresponding rectified intergrated EMG amplitudes and it showed reasonable results.

• Journal of Oral Medicine and Pain
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• v.13 no.1
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• pp.23-33
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• 1988

The purpose of this study was to standardized and classify the coordination pattern among the chewing side and non-chewing side masseter and anterior muscles, in terms of EMG values on lateral excursion, clenching, and mastication in presence of the non-chewing side. In this study, 25 subjects were selected for experiment of lateral excursion, clenching and mastication and EMG value of the masseter and anterior temporal muscle on both sides were recored 2 times respectively. The bioelectric processor model EM2(Myo-tonic research, INC. U.S.A.) with the surface electrodes were used to record the EMG activity during all experimental procedures. The results were as follows : 1. During lateral excursion on intereference of non-chewing side, the EMG values of the temporal muscle were significantly more prominent than those of the temporal muscle on the non-chewing side. The EMG values of non-chewing side were significantly more prominent than those of chewing side on the both side masseter muscle and those of chewing side were significantly more prominent than those of non-chewing side on the both side temporal muscle. 2. During clenching on the occlusal interferance, the EMG values of non-chewing side masseter muscle were most prominent. 3. During mastication on the occlusal interferance, the EMG values of the chewing side temporal muscle were most prominent and those of non-chewing side temporal muscle were the lowest. 4. The EMG values of temporal muscle of non-chewing side on interferance were significantly more prominent than those of canine guidance during lateral excursion. 5. During clenching on the occlusal interferance, the EMG values of the masseter and the temporal muscles of the non-chewing side were significantly more prominent than canine guidance, but those of chewing side temporal muscle on canine guidance were significantly more prominent than those of interferance. 6. During mastication on canine guidance, the EMG Values of the temporal muscle on the chewing side, the masseter muscle on the chewing side and the temporal muscle on the non-chewing side were more prominent than those of interferance, but temporal muscle of non-chewing side was not different between canine guidance and occlusal interferance on non-chewing side.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.632-640
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• 2007

The low force estimation method of skeletal muscle was proposed by using ICA(independent component analysis) and neuro-transmission model. An EMG decomposition is the procedure by which the signal is classified into its constituent MUAP(motor unit action potential). The force index of electromyography was due to the generation of MUAP. To estimate low force, current analysis technique, such as RMS(root mean square) and MAV(mean absolute value), have not been shown to provide direct measures of the number and timing of motoneurons firing or their firing frequencies, but are used due to lack of other options. In this paper, the method based on ICA and chemical signal transmission mechanism from neuron to muscle was proposed. The force generation model consists of two linear, first-order low pass filters separated by a static non-linearity. The model takes a modulated IPI(inter pulse interval) as input and produces isometric force as output. Both the step and random train were applied to the neuro-transmission model. As a results, the ICA has shown remarkable enhancement by finding a hidden MAUP from the original superimposed EMG signal and estimating accurate IPI. And the proposed estimation technique shows good agreements with the low force measured comparing with RMS and MAV method to the input patterns.

• Journal of Korean Institute of Industrial Engineers
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• v.9 no.2
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• pp.9-25
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• 1983

The purpose of this study was to film up computerized analyses for both kinematic posture(film analysis) and muscle dynamics (EMG) during a weight-lifting motion. (Snatch, Clean and Jerk) Using a motor drive camera (3.5 frames/sec) and a Location Analyzer, motion tracks of 13 landmarks, which were attached to the major joints, during the motion were converted into digital values. At the same time, EMG amplitudes from 11 major muscle groups were recorded. Recorded data were processed via analog/hybrid computer (ADAC 480) and digital computer (PDP 11/44). Landmark locations and EMG amplitude were integrated by a computerized routine. Computer output included graphic reproductions on sepuential dislocations of body segments, center of gravity of body segments and the associated changes on EMG amplitude such as % EMG's of major muscle group during a weight lifting motion. The results strongly suggest that the computerized motion-EMG integration can provide a further working knowledge in selection and in training of workers and athletes. Suggestions for a further study include additional device for velocity measurement, expansion of the link model for biomechanical analysis and other implementations necessary for athletic application.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.22 no.3
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• pp.257-264
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• 2012

Objectives: This study's aims were to evaluate the effects of load center of gravity within an object lifted and feet placements on peak EMG amplitude acting on bilateral low back muscle groups, and to suggest adequate foot strategies with an aim to reducing low back pain incidence while lifting asymmetric load. Methods: The hypotheses that asymmetric load imposes more peak EMG amplitude on low back muscles contralateral to load center of gravity than symmetric load and maximum peak EMG amplitude out of bilateral ones can be relieved by locating one foot close to load center of gravity in front of the other were established based on biomechanics including safety margin model and previous researches. 11 male subjects were required to lift symmetrically a 15.8kg object during 2sec according to each conditions; symmetric load-parallel feet (SP), asymmetric load-parallel feet (AP), asymmetric load-one foot contralateral to load center of gravity in front of the other (AL), and asymmetric load-one foot ipsilateral to load center of gravity in front of the other (AR). Bilateral longissimus, iliocostalis, and multifidus on right and left low back area were selected as target muscles, and asymmetric load had load center of gravity 10cm deviated to the right from the center in the frontal plane. Results: Greater peak EMG amplitude in left muscle group than in right one was observed due to the effect of load center of gravity, and mean peak EMG amplitudes on both sides was not affected by load center of gravity because of EMG balancing effect. However, the difference of peak EMG amplitudes between both sides was significantly affected by it. Maximum peak EMG amplitude out of both sides and the difference of peak EMG amplitude between both sides could be reduced with keeping one foot ipsilateral to load center of gravity in front of the other while lifting asymmetric load. Conclusions: It was likely that asymmetric load lead to the elevated incidence of low back pain in comparison with symmetric load based on maximum peak EMG amplitude occurrence and greater imbalanced peak EMG amplitude between both sides. Changing feet positions according to the location of load center of gravity was suggested as one intervention able to reduce the low back pain incidence.

• Proceedings of the ESK Conference
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• 1997.04a
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• pp.107-113
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• 1997

In this paper, an interfacing method to control rehabilitation assitance system with bio-signal is proposed. Controlling with EMG signals method has certain advantage on signal-collecting, but has some drawbacks in the function resolution of EMG signals because data-processing process is not efficient. To improve function-resolution and to increase the efficiency of EMG signal interfacing with rehabilitation assistance system, Multi-layer Perception which is highly effective with static signal and hidden-Markov model for dynamic signal resolving are fused together. In proposed method. The direction and average speed of the rehabilitation assitance system are controlled by the trajectory control and estimation of the moving direction result from the fused model. From the experiment, proposed GMM and 2-level MLP hybrid-classifier yielded 8.6% perception-error rate, improving function resolution. New acceleration control method constructed with 3 nested linear filter produced continuous acceleration paths without the information of destination point. Thus, the mass output caused by non- continuous acceleration-deceleration was eliminated. In the simulation, the necessary calculation, in the case of multiplication, was reduced by 11.54%.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.560-567
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• 2003

EMG recordings of the electrical activity of muscle have proved to be a valuable tool in studying muscle function and reflex activity. SP(silent period) is elicited by a electrical stimulation on the chin during isometric contraction of jaw muscle. This paper proposes a model of the inhibitory reflex mechanism of jaw muscle after electrical stimulation. The SPs of jaw muscle after a electrical stimulation to the chin were divided into SP1 and SP2. SP1 is produced by the activation of periodontal receptors. The activation of nociceptors contributes to the SP2. As a result, the EMG signal generated by a proposed a model of inhibitory reflex mechanism is similar to real both EMG signal including SP1 and SP2. The present study have shown differences of SP1 and SP2 induced by inhibitory reflex mechanism.

• Journal of Biomedical Engineering Research
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• v.17 no.4
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• pp.459-468
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• 1996

This paper considers the problem of realising a parallel EMG identifier used in FES (functional electrical stimulation) system on a fixed dimension transputer array. This involves using an identifiestion algorithm in the wavelet transform domain. This algorithm have suggested by the authors in a previous paper(6). The transputer serial links permit higtlly varied and economic network-type connections and the structure enables rapid topological reconfiguration. Analysing the results Showed that the Speed-UPS ranged from 1.82 to 3.44 With 2-4 transputers for corresponding model order, and from 1.82 to 3.97 with increasing the model orders when two and four transputers are used respectively.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.799-804
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• 1991

This paper is concerned with the artificial control of prosthetic devices using the electromyographic(EMG) activities of biceps and triceps in human subject during isometric contraction adjustments at the elbow. And it was analysised about recognition of EMG signals and dynamic characteristics at arm movements of human. For this study the error signal of autoregressive(AR) model were used to discriminate arm movement patterns of human. Interaction of dynamic characteristics (Position, Velocity, Acceleration) and EMG of biceps and triceps at arm movements of human was measured.