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This paper presents a study of speech recognition based on electromyographic biosignals captured from the articulatory muscles in the face using surface electrodes. This paper compares the speech recognition system for spoken English and Malay words by a group of Malay native speakers. Feature extraction was done in both temporal and time-frequency domains. Temporal features used are integrated EMG...
the aim of this paper is to introduce an integrated system for accurate and easy rehabilitation process. A small gadget and an installed android application for on line follow up and continuous enhancement with affordable cost. The gadget consists of instrumentation amplifier, filtration process and rectifier. The gadget is communicating with android application via Bluetooth device which send the...
A sitting knee rehabilitation robot has been developed in order to work with biological signals of patients muscles (EMG). This type of robot is capable to perform all active and passive exercises to improve the functionality of injured knee and thigh muscles. Intention of patients/operators to move their knee is detected by electrical activities of knee muscles (EMG) recorded above an observed muscle...
This paper studies the effect of preparation instruction on pre-motor activity in EMG signals. Two kinds of trials are investigated, the first one uses a warning signal for mental preparation of a contraction while the second one does not use any preparation warning. Time domain analysis has been carried out in order to select Relative Power (RP) and Preparation Duration (PD) as relevant features...
This paper presents a classification method for multi-class classification of electromyography (EMG) signals from eight hand movements. The data were collected from 15 subjects. The EMG signals were extracted using 16 time-domain feature extraction methods. The 16 features are reduced using principal component analysis (PCA) to enhance the classification accuracy. The features results from PCA are...
This research focuses on development of EMG circuit to detect the EMG signal from quadriceps muscle. The circuit used Surface self-adhesive electrodes to capture muscle activity during the knee extension. The two electrodes were placed at a distance of 10mm from each other in the middle rectus femoris muscle. This is the initial effort to investigate the output signal stage by stage from EMG circuit...
Since last decade, the diabetes risks are increasing in children and adults. Various approaches have been proposed for early detection of the diabetes and prevention on it. Some methods use EMG signals for diabetes classification, due to motion artifacts in the EMG signals during acquisition of signal, these approaches are not able to classify the signal efficiently. To overcome this we propose anew...
Many people suffer from a brain injury that requires rehabilitation. Rehabilitation might be exhausting and difficult. Therefore, it is necessary to develop mechanisms to engage the patients, e.g. a videogame. We propose the design of an immersive videogame that integrates motion capture, electromyography (EMG) sensing and Virtual Reality (VR) in one unique system using Unity engine and the design...
This paper deals with muscles behavior analysis during pre-motor activity and during transition step from preparation to effective muscle activity. It aims evaluating gender differences and determining the relationship between pre-motor activity and transition step. Three features are used, they are Relative Power RP and Preparation Duration PD for pre-motor activity and Transition Slope TS for transition...
Electromyography (EMG) signal can be defined as a measure of electrical activity produced by skeletal muscles. It can be used in handling electronic devices or prosthesis. If we are able recognize the hand gesture captured using EMG signal with greater reliability and classification rate, it could serve a good purpose for handling the prosthesis and to provide the good quality of life to amputees...
Ankle Foot Orthoses is a supportive equipment attached to the lower part of the leg to support patient's walking posture, gait. It has been developed for several years using many kinds of actuator that can be controlled electronically. In this paper, a controller development by experiment for Passive Control Ankle Foot Orthoses (PICAFO) is presented. A Fuzzy Logic Controller is proposed to control...
Generally, Negative emotions can lead to health problems. In order to detect negative emotions, an advanced method of the EMG signal analysis is presented. Negative emotions of interest in this work are: fear, disgust and sadness. These emotions are induced with presentation of IAPS (International Affective Picture System) images. The EMG signal is chosen to extract a set of characteristic parameters...
In the field of Robotics, prosthesis hand amputees are highly benefited for various active hand movements based on wrist-hand mobility. The development of an advanced human-machine interface has been an interesting research topic in the field of rehabilitation, in which biomedical signals such as electromyography (EMG) signals, plays a significant role. Identification, pre-processing, feature extraction...
A feature extraction scheme based on discrete cosine transform (DCT) of electromyography (EMG) signals is proposed for the classification of normal event and a neuromuscular disease, namely the amyotrophic lateral sclerosis. Instead of employing DCT directly on EMG data, it is employed on the motor unit action potentials (MUAPs) extracted from the EMG signal via a template matching-based decomposition...
Using bio-metric signals such as muscle and neuron signals through intelligent control systems to mimic human behavior, recovery of human organ function and rehabilitation in health care or remove human beings from hard or dangerous working condition has been an active research area especially in recent decades. This research attempts to develop a cost effective bio-driving robotic system for hand...
The probability density function (PDF) of surface electromyography (sEMG) signals can be modelled with the Gaussian and Laplacian PDFs. However, the sEMG PDF is dependent on the levels of contraction of the muscles. Different techniques have been proposed for testing Gaussianity levels of sEMG, i.e., kurtosis, negentropy, and mean bicoherence power, whereas the suitable technique has not been reported...
Muscle force models have many applications in human-machine motion analysis, human-machine interfacing, rehabilitation and robotics. A Hill-type model was used to estimate muscle force. In this work, we are going to introduce a new model to estimate human muscle force. Our model, estimates human muscle force based on a rectified smoothed electromyography (RSEMG) signal using the back-propagation Artificial...
W pracy przedstawiono stanowisko do badań dynamicznych aktywności mięśnia. Zaproponowano rozwiązanie, w którym istnieje możliwość pomiaru wybranych grup mięśniowych w czasie ruchu. Ze względu na fakt, że ból mięśni może być spowodowany poprzez niewłaściwe ułożenie ciała, jak również niekontrolowane napięcie mięśni, zaproponowano rozwiązanie, w którym istnieje możliwość kontroli i automatycznej reakcji...
A novel feature selection method was proposed for electromyography (EMG)-based affective recognition. First of all, correlation analysis was used to reduce the dimension of original feature subset; then adaptive Tabu search algorithm combined with intensification and diversification strategies was adopted for feature selection, and mutation operator of genetic algorithm (GA) was implemented as the...
Today's advanced muscular sensing and processing technologies have made the acquisition of electromyography (EMG) signal which is valuable. EMG signal is the measurement of electrical potentials generated by muscle cells which is an indicator of muscle activity. Other than rehabilitation engineering and clinical applications, EMG signals can also be employed in the field of human computer interaction...
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