The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The field of Sign Language Recognition (SLR) has become an increasingly popular research topic. The goal of this study is an SLR system that will be capable of identifying a subset of 50 of the most common American Sign Language (ASL) word signs using surface electromyography and accelerometer data for multiple signers. All data was collected from deaf, fluent ASL users. A windowing approach is used...
Gesture recognition has multiple applications in medical and engineering fields. The problem of hand gesture recognition consists of identifying, at any moment, a given gesture performed by the hand. In this work, we propose a new model for hand gesture recognition in real time. The input of this model is the surface electromyography measured by the commercial sensor the Myo armband placed on the...
An EMG (electromyogram)-angle neural network was built to estimate elbow movement in a lifting task from sEMG signals in this study. The movement conditions vary with 6 different weights and no load. Subsequently the predicted angle could be utilized as the control signal of a 2DOF powered exoskeleton. Sixteen-channel EMG raw data sets were acquired from two commercial wearable MYO gesture armbands...
The proliferation of multimedia technology and its wide adoption by users has created the need for more effective metrics for Quality of Experience (QoE). Objective video quality metrics usually under-perform in terms of perceptual quality, thus evaluation is usually performed offline by people, an arduous and time consuming task that is also affected by external conditions and by user preferences...
With the elderly and disabled population increasing worldwide, the functionalities of smart wheelchairs as mobility assistive equipment are becoming more enriched and extended. Although there is a well-established body of literature on fatigue detection methods and systems, fatigue detection for wheelchair users has still not been widely explored. This paper proposes a neuro-fuzzy fatigue tracking...
Most studies estimate the grasping force from electromyography (EMG) signals without the feature extraction. However, feature extraction can find the information which reflect the muscle contraction in greatest degree and eliminate the noise and redundancy. In order to find the feature with the highest accuracy, this paper selected 6 features which could represent the contraction of muscle. What's...
Fatigue is a state that the muscle could not able to maintain the contraction. Electromyography signals can be used to determine the state of muscle fatigue. Quantization of muscle fatigue needs to be defined clearly so that it can be used as an indicator or a compensator in the control system. Electromyography signal which is produced during dynamic motion during muscle fatigue assessment is a non-stationary...
Chronic pain is a disease that the patients suffers a lot in their daily life and it is difficult to be released completely. It is difficult to manage because pain can come anytime and it is unpredictable. However, the pain can be represented by the pain related behaviors such as guiding and abrupt actions. In this paper, we will develop a machine learning based system that can detect the pain related...
Researchers have developed diverse methods for detecting hand gestures using EMG signal. The signal of EMG sensor can be measured on a human skin surface. There are two approaches to recognizing hand gestures. One approach is to fuse EMG sensor with others sensors. It is possible to extract various motion features. Other approach uses algorithms that improve the recognition accuracy. We survey two...
Feature extraction is an important part in the classifier systems. In this study, feature extraction was used to extract the information of the surface electromyography (sEMG) and to predict upper limb elbow joint angle. To predict the upper limb elbow joint angle, we explored the EMG signal characteristics on biceps, triceps lateral head and triceps long head. Time domain of feature extraction is...
This paper discusses a non-pattern recognition method for the exoskeleton implementation. The exoskeleton was controlled using electromyography signal (EMG). The EMG signals were collected at the biceps and processed digitally to control the exoskeleton. The proposed method was a modified low pass filter (LPF) 2nd order using zero crossing (ZC) as a feature extraction. In this study, the proposed...
Electromyography (EMG) signals have been used for the control of prosthetics, orthotics and rehabilitation devices as a result of developments in hardware and software technology. A number of signal processing is required because of very low amplitude and noisy structure of the EMG signal. Feature extraction is the most important attribute of the EMG signal processing and there are many different...
The aim of this work is to develop an accurate method for pattern recognition of human hand motions. Eight surface EMG electrodes (dual type) were placed on the forearm of healthy subjects while performing individual wrist and finger motions. A total of 1080 signals that incorporated all the selected nine hand motions were acquired from 12 volunteers, preprocessed, and then time-domain features were...
In recent years, the EEG-based brain-computer interface (BCI) has become one of the most promising areas of research in computer science and robotics. Many internationally renewned research teams combining engineers and doctors, experts in neuroscience are trying to develop useful applications and devices offering disabled people to lead a normal life. Useful BCIs for disabled people suffering from...
This article presents the design of movement sequences for arm rehabilitation of stroke patient. The objective of this research is to develop the best movement sequences suitable for arm rehabilitation of hemiparesis sufferers based on the features analyzed that represent muscle activity. 8 healthy subjects including both male and female performed four arm movement sequences task consist of arm lifting...
Stress is a common part of daily life which most people struggle in different occasions. However, having stress for a long time, or a high level of stress will jeopardize our safety, and will disrupt our normal life. Consequently, performance and management ability in critical situations degrade significantly. Therefore, it is necessary to have information in stress cognition and design systems with...
The aim of this work is to assess the muscle fatigue condition using multimodal system. Muscle fatigue is a common muscle condition which experiences in our daily activity. There were 20 subjects participated in this study. Electromyogram (EMG) (shows the electrical activity of the muscle), Mechanomyogram (MMG) (shows a mechanical activity of the muscle) and Acoustic myogram (AMG) (is audible produced...
Any movement is generated by synergistic actions of muscle groups. The analytical description of how muscles are combined into synergies to produce their coordination actions remains to be established. Here, we have introduced the wavelet-based analysis to identify common information among major leg muscles during a locomotor tasks with and without asymmetric adaptation.
Communication and sign-language learning of the people with hearing disabilities in Thailand has been problematic due to limited number of sign-language experts. To facilitate the sign-language learning and communication between the hearing disability and ordinary people, the sign language-to-alphabet spelling conversion was developed based on electromyography (EMG) signal recorded from the forearm...
Muscle fatigue is a common muscle condition which experiences in our daily activity. Muscle fatigue occur when the muscle fail to provide expected force. Electromyography (EMG) has commonly been used to detect muscle fatigue. Effort has been made to improve the current detection using different Myography. Mechanomyogram (MMG) and acoustic myogram (AMG) were used to record mechanical activity of the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.