• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.815-816
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• 2006

In this paper, an EMG (Electromyography) sensor for utilizing an EMGl-based HCI are described. The EMG sensor is a dry type and has high gain (1000-10000). Therefore, this sensor can be properly applied to HCI devices using EMG signals without additional amplification circuit.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1014-1020
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• 2011

This presents a motion and force estimation system of human fingers by using an Electromyography (EMG) sensor module and a data glove system to be proposed in this paper. Both EMG sensor module and data glove system are developed in such a way to minimize the number of hardware filters in acquiring the signals as well as to reduce their sizes for the wearable. Since the onset of EMG precedes the onset of actual finger movement by dozens to hundreds milliseconds, we show that it is possible to predict the pattern of finger movement before actual movement by using the suggested system. Also, we are to suggest how to estimate the grasping force of hand based on the relationship between RMS taken EMG signal and the applied load. Finally we show the effectiveness of the suggested estimation system through several experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1231-1235
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• 2016

In this study, it measures electromyogram to estimate scoliosis by using sensors in both sides of spinal erector muscle. A device is measured raw data to input mcu through a filter and amplifier. MCU is named "arduino" that is calculated muscle activity with algorithm by inputting data. By comparing with both sides of spinal erector muscle's activity, it studies about estimation of scoliosis

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1634-1637
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• 2004

We developed a communication device for person with serious disability to use slight movement. This device is developed mainly for patients suffering from ALS or a cerebral infarction. They often have communication difficulty because of deterioration of muscle functions. A feature of this device is that slight movements of user's finger, eyes or lips can be detected by using a vision sensor. Due to the features of the vision sensor, it is quite easy even for person with serious disability to use a communication device. By the field test it is confirmed that the vision sensors have superior performances as an input device for communication device. Experiments to use an EMG (electromyography) sensor and a rotary sensor are also tested to compare the performances.

• Journal of Sensor Science and Technology
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• v.25 no.5
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• pp.365-370
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• 2016

The study about VR (Virtual Reality) has been done from the 1960s, but technical limits and high cost made VR hard to commercialize. However, in recent, high resolution display, computing power and 3D sensing have developed and hardware has become affordable. Therefore, normal users can get high quality of immersion and interaction. However, HMD devices which offer VR environment have high latency, so it disrupts the VR environment. People are usually sensitive to relative latency over 20ms. In this paper, as adding the Electromyogram (EMG) sensors to typical IMU sensor only system, the latency reduction method is proposed. By changing software and hardware components, some cases the latency was reduced significantly. Hence, this study covers the possibility and the experimental verification about EMG sensors for reducing the latency.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.194-195
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• 2015

Methods for measuring the physical workload of construction workers are classified into posture assessment techniques (i.e., OWAS, RULA, etc.) and physiological measurement techniques (i.e., EMG, heart rate, etc.). The one does not quantify the workload on a specific body part of a worker by considering the weight of the hand tools or materials on hand and time for holding a particular posture. This paper presents a procedure for evaluating a physical demand using the electromyography (EMG) sensor. This study compares the EMG measurement and the posture assessment. The case study is carried out on a masonry operation.

• Journal of International Academy of Physical Therapy Research
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• v.10 no.4
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• pp.1868-1872
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• 2019

Background: Lower trapezius muscle function is important for the prevention and treatment of shoulder injuries. However, scapular posterior tilt movement has been overlooked in lower trapezius strengthening exercise programs. Objective: To examine the effects of prone arm lifting with scapular posterior tilt (PALSPT) on trapezius muscles. Design: Crossover study Methods: 17 healthy males were recruited for participation in this study. Participants performed backward rocking diagonal arm lifting (BRDAL) and PALSPT. To train participants in scapular posterior tilt movements for PALSPT, visual biofeedback of scapular movements was provided using a motion sensor. Electromyography (EMG) activities of the middle and lower trapezius were recorded using a surface EMG system. Differences in middle and lower trapezius muscle activity between BRDAL and PALSPT exercises were analyzed. Results: Lower trapezius muscle activity was significantly greater during PALSPT than during BRDAL (p=.006). Although greater EMG activity was observed in the middle trapezius during PALSPT than during BRDAL, this difference was not significant (p=.055). Conclusions: The results of the present study indicate that scapular posterior tilt movements must be considered in lower trapezius muscle strengthening programs.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1732-1739
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• 2018

With the explosion of digital devices, interaction technologies between human and devices are required more than ever. Especially, hand gesture recognition is advantageous in that it can be easily used. It is divided into the two groups: the contact sensor and the non-contact sensor. Compared with non-contact gesture recognition, the advantage of contact gesture recognition is that it is able to classify gestures that disappear from the sensor's sight. Also, since there is direct contacted with the user, relatively accurate information can be acquired. Electromyography (EMG) and force-sensitive resistors (FSRs) are the typical methods used for contact gesture recognition based on muscle activities. The sensors, however, are generally too sensitive to environmental disturbances such as electrical noises, electromagnetic signals and so on. In this paper, we propose a novel contact gesture recognition method based on Flexible Epidermal Tactile Sensor Array (FETSA) that is used to measure electrical signals according to movements of the wrist. To recognize gestures using FETSA, we extracted feature sets, and the gestures were subsequently classified using the support vector machine. The performance of the proposed gesture recognition method is very promising in comparison with two previous non-contact and contact gesture recognition studies.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.5
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• pp.21-27
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• 2008

Despite recent studies on development of pulse diagnosis systems and needs for commercializing them, the reproducibility is one of the most controversial issues as ever. Because the pulse pressure value, which is one of the important parameters to evaluate reproducibility, is very vulnerable to moving artifacts, the reproducibility can not be obtained easily. In this paper, we suggested a moving artefacts detection system for a pulse diagnosis system so that a pulse diagnosis system can be robust to theses kinds of artefacts by excluding the contaminated parts from the pulse wave signal to be analyzed. This moving artifacts detection system was designed to consist of a three-axis accelerometer, an electromyography amplifier and a two-axis tilt sensor. To assess the suitability of the system, we examined the characteristics of each sensor's output signals with regard to the three specific motions such as extension, flexion and rotation. And, we also examined the each sensor's response to the high-frequency and low-frequency moving artifacts while the pulse wave signal was acquired from a pressure sensor for the pulse diagnosis. From these results, we could find that the response to subject's motions would be reflected in electromyography signal first, in accelerometer signals and in tilt sensor sequently. And, the facts that a stable pulse wave can be acquired in two seconds after high frequency or low frequency motions ended, were also found. Consequently, based on these findings, we set up some rules on the moving artifacts detection and designed an algorithm which is fit for our moving artifacts detection system.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.41-50
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• 2023

This study aims to develop electromyography (EMG) textile electrodes and assess their performance and signal stability by examining variations in layer count and fabric types. We fabricated the electrodes through layering and pressing techniques, focusing on configurations with different layer counts (Layer-0, Layer-1, and Layer-2). Our findings indicate that layer presence significantly influences muscle activation measurements, with enhanced performance correlated with increased layer numbers. Subsequently, we created electrodes from five distinct fabrics (neoprene, spandex cushion, 100% polyester, nylon spandex, and cotton canvas), each maintaining a Layer-2 structure. In performance tests, nylon spandex fabric, particularly heavier variants, outperformed others, while the spandex cushion electrodes showed superior stability in muscle activation signal acquisition. This research elucidates the connection between electrode performance and factors like layer number and electrode-skin contact area. It suggests a novel approach to electrode design, focusing on layer properties and targeted pressure application on specific sensor areas, rather than uniformly increasing sleeve pressure.