Abstract
Due to damage of the nervous system, patients experience impediments in their daily life: severe fatigue, tremor or impaired hand dexterity, hemiparesis, or hemiplegia. Surface electromyography (sEMG) signal analysis is used to identify motion; however, standardization of electrode placement and classification of sEMG patterns are major challenges. This paper describes a technique used to acquire sEMG signals for five hand motion patterns from six able-bodied subjects using an array of recording and stimulation electrodes placed on the forearm and its effects over functional electrical stimulation (FES) and volitional sEMG combinations, in order to eventually control a sEMG-driven FES neuroprosthesis for upper limb rehabilitation. A two-part protocol was performed. First, personalized templates to place eight sEMG bipolar channels were designed; with these data, a universal template, called forearm electrode set (FELT), was built. Second, volitional and evoked movements were recorded during FES application. 95% classification accuracy was achieved using two sessions per movement. With the FELT, it was possible to perform FES and sEMG recordings simultaneously. Also, it was possible to extract the volitional and evoked sEMG from the raw signal, which is highly important for closed-loop FES control.
Highlights
Neurological disabilities are caused by damage of the nervous system; this damage results in the loss of capacity to move and manipulate things, especially if fine movements are required [1]
Its analysis is one of the standard procedures used to identify muscle actions in normal and pathologic conditions. surface electromyography (sEMG) signals can be used for various applications, which include identifying neuromuscular diseases, controlling signals for orthotic or prosthetic devices [4], anticipating movements of the muscles [5], controlling machines or robots, or detecting hand gestures to improve the quality of life [6]
The sEMG signals acquired for open hand and power grasp were used to evaluate the right position of the recording electrodes at the forearm electrode set (FELT)
Summary
Neurological disabilities are caused by damage of the nervous system (which includes the brain and spinal cord); this damage results in the loss of capacity to move and manipulate things, especially if fine movements are required [1]. Stroke survivors may have great difficulty to modulate muscle activation, and their ability to span region is curtailed [3]. Biomedical signals, such as surface electromyography (sEMG), play a significant role in the measurement of the electrical muscle contraction. Its analysis is one of the standard procedures used to identify muscle actions in normal and pathologic conditions. SEMG signals can be used for various applications, which include identifying neuromuscular diseases, controlling signals for orthotic or prosthetic devices [4], anticipating movements of the muscles [5], controlling machines or robots, or detecting hand gestures to improve the quality of life [6] Its analysis is one of the standard procedures used to identify muscle actions in normal and pathologic conditions. sEMG signals can be used for various applications, which include identifying neuromuscular diseases, controlling signals for orthotic or prosthetic devices [4], anticipating movements of the muscles [5], controlling machines or robots, or detecting hand gestures to improve the quality of life [6]
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