• Journal of rehabilitation welfare engineering & assistive technology
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• v.7 no.1
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• pp.39-43
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• 2013

In this paper, we present a effective method of gait rehabilitation training using critical point of median frequency in muscle fatigue analysis using EMG. To target the five healthy volunteers, EMG signal were measured in the quadriceps femoris muscle and the tibialis anterior muscle in order to determine muscle fatigue. We performed a test targeting three adult male for 30 minutes on a treadmill at a speed of 6km/h same. EMG signal analysis in frequency and median frequency is calculated to quantification of muscle fatigue, and calculated the critical point which is saturated by muscle fatigue during 30 minutes. We set saturated point the threshold which muscle can withstand. The results of this paper, we are able to quantify the threshold of the muscle.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1035-1043
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• 2021

The shoulder is less stable than other joints, making it easier to onset of various shoulder disorders. In addition, limited range of motion and pain in the shoulder due to shoulder disorders restricts daily life and social activities. The problem with exercise therapy can be reduced in exercise effect by causing boredom through simple repetition of motion, thus reducing the patient's willingness to participate. Therefore, this paper aims to provide a treatment method that can induce active participation of patients by developing devices capable of passive, active, and resistance exercise and serious game contents using them. Furthermore, sEMG was used to verify whether the rotational exercise in the horizontal and vertical using serious game contents helps the shoulder movement actually. The measured sEMG signal was classified as 5 phases according to the angle of rotation and calculated the mean integrated EMG. The mean integrated EMG for the experimental results was higher in all phases when rotational was performed compared to those when both horizontal and vertical rotational exercise remained initial posture, indicating an increase in muscle activity.

• Physical Therapy Korea
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• v.10 no.1
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• pp.37-50
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• 2003

The purpose of this study was to compare visual analogue scale (VAS), pain threshold (PT), $%RMS_{RVC}$, and EMG gaps before and after applying transcutaneous electrical nerve stimulation (TENS) on the upper trapezius muscle at the patients with myofascial pain syndrome (MPS). The subjects were 4 men and 10 women composed of both the inpatients and outpatients who were diagnosed as MPS at Wonju Medical Center. VAS and PT measurements were performed to assess the subjective pain level. The reference voluntary contraction (RVC) test was performed for 15 seconds for normalization on the bilateral trapezius muscle using surface electromyography (sEMG). After 3-minute resting time, the EMG signal was recorded while performing a typing activity for 2 minutes and then TENS was applicated with a comfortable intensity for 10 minutes. The EMG activity of the upper trapezius muscle was recorded during typing for 2 minutes. The results of study were as follows: 1) VAS score was significantly decreased on the more painful side after treatment, however, it was not significantly different on the less painful side. 2) PT was increased after treatment on both sides, however, it was not significantly different between before and after the TENS application. 3) The EMG activity during typing was significantly decreased after treatment, and 4) The EMG gaps were significantly increased after TENS treatment compared to before it. Consequently, the study showed that TENS was effective in decreasing VAS, $%RMS_{RVC}$, and in increasing EMG gaps. The EMG gap analysis could be a useful method to measure pain in patients with MPS in the upper trapezius.

• Physical Therapy Korea
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• v.20 no.2
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• pp.28-37
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• 2013

This study examined differences in the activity of upper limb muscles according to how an ultrasound head is gripped. Twenty-two adult males were participated in the study. Each participant was asked to apply ultrasound treatment on to a lump of pork meat by two different ultrasound head grip patterns: spherical and cylindrical grips. Muscle activity was measured in the extensor carpi radialis longus (ECRL), flexor carpi ulnaris (FCU), and pronator teres (PT), triceps brachii (TB), middle deltoid (MD), and upper trapezius (UT) muscles. There were no significant differences in the EMG signals of any muscle according to the ultrasound head grip pattern (p>.05). There were significant differences in the EMG signal of each type of muscle (p<.05). The EMG signal of UT was the lowest and that of TB was lower than ECRL and FCU. There were interactions between ECRL and FCU, between ECRL and PT, between FCU and ECRL, and between FCU and MD. The EMG signal of ECRL using the cylindrical head was low and that of FCU with the cylindrical head was high, while the opposite was the case with the spherical head ($p_{adj}$ <.05/15). The results of this study indicate that the wrist muscles worked actively when the participants applied ultrasound therapy using both spherical and cylindrical heads. A spherical head might induce imbalanced muscle activity among the wrist muscles, leading to deviation of the wrist joint. Therefore, the cylindrical head is recommended for ultrasound therapy because it produced a constant, repeated force.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.1009-1018
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• 2019

This paper describes the design and implementation of a rehabilitation medical device based on a EMG measurement. Rehabilitation systems are controlled using BLDC motors and motor drives. The BLDC motor drive controls the operation and the speed controls the drive through the external servo motor. In addition, potentiometer coupled to the outside of the motor transmits information about the position of the load being rotated by the motor. The rehabilitation algorithm is controlled by limiting the maximum angle of 0 to 120 by utilizing the motor according to the user setting stage during the rehabilitation exercise. The walking algorithm compensates motor control for the low leg of the signal using the difference value of the signal obtained with the surface denser attached to both inner muscles. The motor and surface denser are utilized for the walk motion to control the maximum angle of 0 to 80.

• Journal of IKEEE
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• v.23 no.2
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• pp.727-734
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• 2019

This paper confirms whether the movement or specific operation of the muscles in the process of transferring a person from the brain can find a signal showing an essential feature of a certain part of the brain. As a rule, the occurrence of EEG(Electroencephalogram) changes when a signal is received from a specific action or from an induced action. These signals are very vague and difficult to distinguish from the naked eye. Therefore, it is necessary to define a signal for analysis before classification. The EEG form can be divided into the alpha, beta, delta, theta and gamma regions in the frequency ranges. The specific size of these signals does not reflect the exact behavior or intention, since the band or energy difference of the activated frequencies varies depending on the EEG measurement domain. However, if different actions are performed in a specific method, it is possible to classify the movement based on EEG activity and to determine the EEG tendency affecting the movement. Therefore, in this article, we first study the EEG expression pattern based on the activation of the left and right biceps EMG, and then we determine whether there is a significant difference between the EEG due to the activation of the left and right muscles through EEG. If we can find the EEG classification criteria in accordance with the EMG activation, it can help to understand the form of the transmitted signal in the process of transmitting signals from the brain to each muscle. In addition, we can use a lot of unknown EEG information through more complex types of brain signal generation in the future.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.240-244
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• 2008

This paper presents an EMG-based wireless and wearable computer interface. The wearable device contains 4 channel EMG sensors and is able to acquire EMG signals using signal processing. Obtained signals are transmitted to a host computer through wireless communication. EMG signals induced by the volitional movements are acquired from four sites in the lower limb to extract a user's intention and six classes of wrist movements are discriminated by employing an artificial neural network (ANN). This interface could provide an aid to the limb disabled to directly access to computers and network environments without conventional computer interface such as a keyboard and a mouse.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.41-49
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• 2005

Electromyogram (EMG) signal generated by voluntary contraction of muscles is often used in rehabilitation devices because of its distinct output characteristics compared to other bio-signals. This paper proposes a novel EMG-based human-computer interface for electric-powered wheelchair users with motor disabilities by C4 or C5 spine cord injury. User's commands to control the electric-powered wheelchair are represented by shoulder elevation motions, which are recognized by comparing EMG signals acquired from the levator scapulae muscles with a preset double threshold value. The interface commands for controlling the electric-powered wheelchair consist of combinations of left-, right- and both-shoulders elevation motions. To achieve a real-time interface, we implement an EMG processing hardware composed of analog amplifiers, filters, a mean absolute value circuit and a high-speed microprocessor. The experimental results using an implemented real-time hardware and an electric-powered wheelchair showed that the EMG-based human-computer interface is feasible for the users with severe motor disabilities.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.9-16
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• 2003

We proposed a method of a virtual robot arm controlled by the EMG pattern recognition using an improved SOFM method. The proposed method is simple in that the EMG signals are used as SOFM's input directly without preprocessing but nevertheless input patterns are reliably classified and then used for fuzzy logic systems to automatically tune the neighborhood and the learning rate. In order to verify the effectiveness of the proposed method, we experimented on EMG pattern recognition of 6 movements from the shoulder, wrist, and elbow. Experimental results show that the proposed SOFM method has 21.7% higher recognition rate than the general SOFM method, the average number of learning iterations has been decreased, and then the virtual robot arm is controlled by EMG pattern recognition.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2729-2732
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• 2003

This paper proposes a real-time method to recognize shoulder elevation motions by comparing EMG signals on the Levator scapulae muscles with double threshold values. To achieve real-time, we implement a EMG signal processing hareware embedded band-rejection filter, low-pass filter, full rectifier and moving average circuits. And a high speed microprocessor is used for implementing the double thresholds method. The available shoulder motions for the human-computer interface are elevation of left, right and both shoulders. From experimental results we show that the proposed real-time processing hardware and double thresholds method are useful for the real-time EMG-based human-computer interface.