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Sign language recognition (SLR) could help the deaf better communicate with individuals who do not understand sign language, which could also be used in human-computer interaction (HCI). In this paper, surface Electromyography (sEMG) signals and accelerometer (ACC) signals are acquired from the right forearm, wrist and the back of the hand for 18 isolated Chinese Sign Language (CSL) signs. A new position...
Myoelectric control with surface EMG signal has achieved great success in clinics, but only limited to the control of 2-Degrees-of-freedom prosthesis. With the appearance of multiple-channel and high-density EMG system and the advances of pattern recognition technology, it becomes possible to control a multi-degree smart prosthesis using EMG signals. However, it requires high performance EMG systems...
To the present day, a multitude of studies aims to understand how the Central Nervous System (CNS) translates neural pulses to muscle motor tasks, through the analysis of surface EMG (sEMG) recordings. One of the most considerable methods applies the Non-Negative Matrix Factorization (NMF) to data recorded from sEMG electrodes, to extract coordinated motor patterns, the so-called muscle synergies,...
Electromyography is gaining prominence in wearable electronic devices with improved design of surface electrodes and increased demand in various fields such as health monitoring, prosthetic control and assistive technology. Surface electromyogram signals have been analyzed using conventional time-domain, frequency-domain, and time-frequency domain features as well as high-order spectral analysis since...
In this paper, we propose a method to estimate muscular fatigue in exercises with load fluctuations. Muscular fatigue is an important property when evaluating the state of a muscle. However, it is extremely difficult to apply general methods, which depend on the relative changes in the signal power or frequency characteristics of a surface EMG, during exercise. We define two qualitative factors of...
We are working the recognition of inaudible Japanese speech by using surface electromyography. During natural speech, muscle activity changes continuously and gently under the influence of the preceding or succeeding phoneme, even within the utterance of a single vowel. We need to detect the temporal positions of such changes to extract stable features of phonemes. In our previous works, we expected...
Design of modern prosthetic hand that have multiple degrees of freedom and able to move multiple fingers and wrist simulataneously, it has been important to use different sensor structures having advantegous in both size and energy usage. In this study, it is investigated whether piezoelectricity-based force sensors can be used instead of EMG sensors in prosthetic hand design or not. As a result of...
In this study, two channels, multifunctional myoelectric prosthesis hand is designed and operated for biomedical and control engineering departments laboratory as experiment apparatus. Various analog signal processing steps are implemented to the surface EMG signals which received on the triceps and biceps muscles. After that signals are conveyed to microcontroller and compared with a threshold value...
This paper investigate a fuzzy logic based high performance surface EMG classification algorithm for multifunctional upper limb prostheses. In this paper, we record 4 channels EMG data with surface electrodes from the forearm and aimed to recognize 8 different upper limb movements using heuristic fuzzy logic methods from these data. We use 50 surface EMG data for every function and evaluate the performance...
In surface electromyography, electrodes are placed on skin surface above the muscles being monitored, to record the electrical potentials generated in the muscles when an activity is performed. These signals are useful in wearable electronic devices such as those used for human-machine interface, health monitoring and prosthetic limb control. High-order spectra, such as bispectrum, have been used...
The work aims at estimating the elbow kinematics under fatigue and non-fatigue conditions at the same time classifying the surface EMG signal into fatigue or non-fatigue conditions using the Multiple Time Domain (MTD) features extracted from the sEMG signal. For the purpose, sEMG data is acquired from the bicep muscle of 30 individuals together with elbow kinematics data. The most suitable time domain...
In this paper, we propose a muscle gesture-computer interface (MGCI) system for a five-fingered robotic hand control employing a commercial wearable MYO gesture armband. Eight channels of surface EMG (sEMG) signals were acquired and segmented. Then four levels of Daubechies 5 Wavelet family were performed to analyze the EMG signal. Totally 72 features were extracted from the EMG raw data for 16 hand...
The purpose of this work is to characterize Electrode-Skin interface, and compare different electrode types and skin treatments. The effects, evaluated in terms of individual Electrode-Skin impedance, impedance mismatch and noise, due to the electrode type (wet or dry contact), the skin treatment type (abrasion, keratolytic agents, sweat) and the contact time, were investigated. The inter- and intra-subject...
A linear electrode array was used to investigate the relationship between inter-electrode distance (IED) and frequency content of the surface EMG during isometric contraction of the elbow flexor muscles. It is shown that mean and median frequencies decrease as IED is increased from 5mm to 15mm. No effect of joint angle was observed, but it was noted that the spectral parameters differ with muscle.
Rational behind conducting this randomized trial was to examine the therapeutic effect of functional electrical stimulation (FES) in stroke survivors having hand grasp problem. For this we used novel approach of tracking the motor condition changes instead of traditional method of measuring functional assessment scores. In the study subjects less than 9 months of stroke history with hand grasp difficulty...
Wearable technology for assistive medical applications and physical activity recognition has emerged as a fast growing research field in recent years. However, the design of such systems still poses challenges, including restricted physical size, limited computational resources, and the availability of constrained energy sources. In this paper, we present a practical design space exploration of a...
Great co-contraction, i.e. simultaneous contraction of agonist and antagonist muscles crossing a joint, of ankle muscles during the stance phase has been identified as one of the typical features of the immature gait. The goal of the present study was the assessment of the co-contractions of tibialis anterior (TA) and gastrocnemius lateralis (GL) during walking in 20 healthy 6-to-8-year-old children,...
Electrocardiogram (ECG) represents, with the electroencephalogram (EEG), the principal bio-vital signals, providing information on the human physical condition. Although surface electromyogram (sEMG) is not classified as bio-vital, it is frequently used to integrate and increase information obtained from ECG and EEG, making these three signals the main electric-biological signals. The sEMG is widely...
Estimation of human lower limb motions is elementary to enable power-assist robotic systems used for lower limb disabled persons. These robotic systems are based on lower limb muscles electromyographic (EMG) signals. EMG allows for the measurement of the change in the membrane as voltage from our muscles relates to work done. Apparently, there is no particular technique to estimate the mathematical...
Hand kinematics or joints angle estimation using sensors to control prosthetic devices is one of the growing research areas in today’s biomedical engineering. The need for continuous and proportional control of movements makes the regression methods more suitable than classification approaches. In system identification like regression it is possible to find a model which tracks the behavior of an...
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