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The work discusses the construction of a measurement system for determining the relationship between EMG signals and hand grip movements. The relationship is necessary for the synthesis of control of the hand bioprosthesis. The measurement system is based on commercial Myo armband with EMG signals sensors and sensory glove with bend and pressure sensors. There are presented possibilites, advantages...
Electromyogram (EMG) signal can be defined as the electrical activity of muscles cells. It is commonly used in motion recognition, treatment of neuromuscular disorders and prosthetic hand control. In this study, classification of EMG signals obtained from 6 different hand shapes of holding object was proposed. At first Short Time Fourier Transform of the EMG signal were evaluated to obtain their Time-Frekans...
Many common activities of daily living like open a door or fill a glass of water, which most of us take for granted, could be an insuperable problem for people who have limited mobility or impairments. For years the unique alternative to overcame this limitation was asking for human help. Nowadays thanks to recent studies and technology developments, having an assistive devices to compensate the loss...
The paper proposes a new algorithm that combines the EMG (Electromyography) signals and pressure signals for detecting subtle hand gestures. First, the algorithm uses Myo armband to acquire the forearm EMG signals and the algorithm uses an array of five force sensitive resistors (FSRs) to acquire the muscle expansion pressure signals of the back of the hand. Then the algorithm has an activity detection...
The present work is part of the “Hand of Hope” project, which seeks to develop low-cost robotic prostheses with the aim of contributing to the social and labor inclusion of people with motor disabilities of their upper extremities. The specific objective to address in this work is the design and development of the system architecture to recognition of EMG (Electromyography) signal patterns, the purpose...
This paper demonstrates the application of electromyography (EMG) signals for controlling home devices. To achieve this we have used an armband called MYO® that has an array of eight sEMG sensors around the forearm. We have studied 15 different hand gestures to create a dictionary of gesture control. We have achieved gesture recognition using Support Vector Machines (SVMs) as a classification method...
Nowadays, humans can play an important role in control of robots. Some researches have used signals that coming directly from humans for control interfaces. In this paper, electromyogram (EMG) signals from the muscles of the human's upper limb are used as the control interface between the user and a robot arm. A Multi-Layer Perceptron (MLP) is trained by additional unsupervised pre-training to decode...
Electromyogram signal is a biomedical signal that measures electrical activity produced in a muscle during its contraction. This work presents a prototype system for moving a prosthetic lower arm, without prior operation intervention, using electrodes that measure electromyogram (EMG) signals placed on two muscles only. The signals are then read by sensors connected to Arduino microcontroller, processed...
This paper shows the design of a PC mouse commanded by electromyographic (EMG) signals from two muscles of the forearm, palmar longus and extensor digitorum, there were classified four hand movements (including rest): flexion, extension and closure. To fulfill this objective the problem was divided into two stages, the first consisting of the hardware design to allow the acquisition of EMG signal...
Trapezoidal stimulation profile has been used for many years in clinical applications to activate the weak tibialis anterior muscle during gait for correcting foot drop. However, this stimulation profile could not well adapt to the different types of terrain, such as level ground, upstairs and downstairs. Thus an environment aware and adaptive stimulation mode would be needed to help drop foot patients...
Using EMG signals as control signals has been a widely accepted option in the last decades. Using a wide array of techniques, EMG signals can be used in a variety of practical ways, from prostethics to exoesqueletons, however a concrete functional relationship between EMG signals and the dynamic and kinematic aspects of the upper limbs has not been established. Nowadays, almost every device that uses...
In this paper, a technique to classify seven different forearm movements using surface electromyography (sEMG) data which were received from 8 able bodied subjects was proposed. A 2-channel sEMG system was used for data acquisition and recording, then this raw electromyography (EMG) signals were applied to the wavelet denoising. In the next step, time-frequency feature is extracted calculating wavelet...
Integrity analysis of knee joint involves a detail study of several anatomical parts such as bones, cartilage, tendons etc. The disorderness or damage of these anatomical parts causes several knee diseases, like osteoarthritis (OA), which is generally found in an increasing tendency particularly, in an aged society. Although, the reasoning of OA in knee joint does not concentrated to the present paper,...
In order to solve the issue of the paraplegias and upper limb disabilities to operate electronic devices, a barrier-free human-computer interaction (HCI) method based on electromyography (EMG) and gyroscopes was researched in this paper. After the analysis and test, the EMG signals of temporal muscle were selected as the control source. To bite as a trigger action, depending on different tooth movements,...
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. Sensing of EMG signals concerns with the signal...
At times, people are born with physical disabilities with respect to their limbs, or lose their fingers as a result of various scenarios. This work aims to achieve maximum replication of the human finger through the use of mechanical prosthetic replacements using surface-based acquisition of Electromyogram (EMG) bioelectric signals pertaining to the underlying muscle tissue. This can be achieved by...
This study deals with a new identification approach, based on Recursive Least Squares algorithm (RLS) to reconstruct the electromyographic signals (EMG) of the forearm muscle. The present study uses the relationship between EMG signals and the velocities profiles of the pen-tip moving on (x, y) plane during the human handwriting motion.
This paper proposes a novel class selection method based on the Kullback-Leibler (KL) information measure and outlines its application to optimal motion selection for bioelectric signal classification. When a user has no experience of controlling devices using bioelectric signals, for instance controlling a prosthetic hand using EMG signals, it is well known that voluntary generation of such signals...
The main focus of our research is to control the load of selected muscles by using a power-assisting device, thus enabling pinpointed motion support, rehabilitation and training by explicitly specifying the target muscles. In our past research, a control method was proposed for static human motion. And the result of simulation and experiments showed that it is possible to control the force of selected...
Sleep Disordered Breathing describes a group of disorders characterized by abnormalities of respiratory pattern or the quantity of ventilation during sleep. Sleep Disordered Breathing causes disruptions in sleep, yielding waking somnolence, diminished neurocognitive performance, adverse cardiovascular outcomes, insulin resistance and other metabolic dysfunctions. Electroencephalography and Electromyography...
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