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We propose a joint force estimation method to compute elbow flexion force using surface electromyogram (sEMG) considering time-varying effects in a fatigue condition. Muscle fatigue is a major cause inducing sEMG changes with respect to time over long periods and repetitive contractions. The proposed method composed the muscle-twitch model representing the force generated by a single spike and the...
In this study, the motion characteristics and techniques of Tai Chi push-hand, a fixed step, single-handed concentric sparring method, were investigated using biomechanical measurements. The FAB system was utilized to obtain the kinematic and foot pressure data, and an MYO armband was used to record the sEMG signals. After the measurements, a single concentric motion was divided into four stages....
This paper proposed a VR-based self-rehabilitation system which utilizes the virtual training model rendered by OpenGL and collects electromyography (EMG) signals from the subjects to perform hand motion recognition. EMG signals are biomedical signals generated in muscles and can be applied in many fields such as clinical diagnosis and biomedical applications. The subjects were asked to manipulate...
This research aims to develop electric prosthetic hand that electrically activated using 2-channel surface electromyography (sEMG'), relied on physiological principle, biomedical electronics and microcontroller programming. Our development and designing controller are a 3-fingers robotic hand. A prototype consisted of 4 main components: 1) sEMG signal detector with electrodes, 2) signal conditioning...
Surface electromyography (sEMG) signals have been extensively studied in the area of intention detection, force estimation and control of rehabilitation devices. Studies regarding sEMG based jaw muscle force estimation are necessary towards building intuitive neural-controlled soft oral rehabilitation robot (SORR). This paper presents a force estimation algorithm based on masseter muscle sEMG signals...
In this paper a new protocol for vibro-tactile robotic rehabilitation is proposed that combines the usage of vibrations with robotic movement assistance to augment rehabilitation outcomes for patients with spasticity. A simple protocol is proposed for focal vibration timing and position in respect to the muscle in order to accomplish the best muscle performance outcome. The results show an increase...
The electromyography (EMG) signals give information about different features of muscle function. A vast body of literature is devoted to the description and analysis of the muscular system abnormalities, the appearance of the fatigue and some factors who influence the muscular force, etc., recording EMG signals, which are very usefully in medical diagnosis and not only. This study is concerned with...
The aim of this paper is to estimate muscle fatigue by using wavelet analysis method in SEMG signal analysis. A signal acquisition system is designed and forearm muscle fatigue experiments under static and dynamic contractions are performed. The wavelet analysis method is proposed to group the wavelet coefficients of SEMG signal into high frequency-band (100Hz-350Hz) and low frequency-band (13-22Hz)...
Parallel cascade identification (PCI) is used as a dynamic estimation tool to map surface electromyography recordings from upper-arm muscles to the elbow-induced force at the wrist. PCI mapping is composed of parallel connection of a cascade of linear dynamic and nonlinear static blocks. Experimental comparison between PCI and previously published orthogonalization scheme has shown superior force...
The architecture of human motion information acquisition system based on surface electromyography (EMG) was described. Motion information is one of the most important techniques in the intelligent assistant production design, and it is a basis for the assistant system to supply appropriate and necessary actions. Thinking of the characteristics of daily tasks, this system adopted surface EMG as signal...
Human motion and its intention sensing from noninvasive biosignals is one of the significant issues in the field of physical human-machine interactions (pHMI). This paper presents a real-time upper limb motion prediction method using surface electromyography (sEMG) signals for pHMI. The sEMG signals from 5 channels were collected and used to predict the motion by an artificial neural network (ANN)...
We investigated muscle activation levels or patterns determined during two-joint arm movements. Twelve subjects were instructed to move their right (dominant) wrists in a horizontal plane. Surface electromyographic activities were recorded from the brachioradialis, biceps brachii, and triceps brachii. The muscle activation level was demonstrated as a function of both the elbow and shoulder torque...
With the goal of developing human-like dextrous manipulation, we investigate how the central nervous system uses the redundant control space of the human hand to perform tasks with force-stiffness requirements. Specifically, while the human hand is actuated by several muscles with varying mechanical advantage (called the moment arm), it is unclear how each muscle is used. Using the anatomically correct...
The state-of-the-art in control of hand prosthetics is far from optimal. The main control interface is represented by surface electromyography (EMG): the activation potentials of the remnants of large muscles of the stump are used in a non-natural way to control one or, at best, two degrees-of-freedom. This has two drawbacks: first, the dexterity of the prosthesis is limited, leading to poor interaction...
Surface electromyography (sEMG) technology is used to record and display the electrical activities of human muscles, by which researchers are able to make a muscle force evaluation. In this study, in order to accurately feedback the information about athletes' forearm force training, the Maximum Voluntary Contraction (MVC) is proved as the indicator of maximum forearm muscle force by developing a...
Surface electromyography (sEMG) has been widely used to estimate muscle activity. However, satisfying both low variability and rapid responsiveness of muscle activities using standard signal processing techniques such as the moving average (MAV), root mean square (RMS), and low-pass filter continues to present challenges. To address these issues, we propose a new method for EMG amplitude estimation...
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