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Identification and Modeling of Surface EMG Signals, Skeletal-Muscle Forces, Skeletal-Muscle Fatigue, and Finger Joint-Angles for Smart Prosthetic Hand Design.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Identification and Modeling of Surface EMG Signals, Skeletal-Muscle Forces, Skeletal-Muscle Fatigue, and Finger Joint-Angles for Smart Prosthetic Hand Design./
Author:	Kumar, Parmod.
Description:	179 p.
Notes:	Source: Dissertation Abstracts International, Volume: 73-06, Section: B, page: .
Contained By:	Dissertation Abstracts International73-06B.
Subject:	Engineering, Biomedical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3497840
ISBN:	9781267195180

Identification and Modeling of Surface EMG Signals, Skeletal-Muscle Forces, Skeletal-Muscle Fatigue, and Finger Joint-Angles for Smart Prosthetic Hand Design.
Kumar, Parmod.

Identification and Modeling of Surface EMG Signals, Skeletal-Muscle Forces, Skeletal-Muscle Fatigue, and Finger Joint-Angles for Smart Prosthetic Hand Design. - 179 p.

Source: Dissertation Abstracts International, Volume: 73-06, Section: B, page: .

Thesis (Ph.D.)--Idaho State University, 2011.

Providing the functionality to upper-extremity amputees for normal activities for daily living can improve their lives tremendously. Therefore, for effective use of suitable upper-extremity prosthesis, we need to address two main critical aspects of prosthetic control (i.e., force and position). The natural choice of a control input for prosthesis is the surface electromyographic (sEMG) signal, also simply referred to as EMG signal. The sEMG can be used to decipher the meaningful information, which correlates with the skeletal-muscle force and the finger joint-angles. By virtue of its nature, the sEMG signal is random and the influence of skeletal-muscle fatigue, which is a complex phenomenon, further enhances its randomness. Forces generated by the muscles decline with the prolonged activation of the muscles and cause them to fatigue. Literature indicates that sEMG analysis is a well-accepted method for muscle-fatigue assessment. The research undertaken for this dissertation covers the three main aspects for the control of a prosthetic hand with the available sEMG signals. These three aspects are force, finger joint-angle motion, and influence of the skeletal-muscle fatigue on the sEMG, which in turn affects the generated skeletal-muscle force and the finger joint-angles. Different experiments were designed to capture the sEMG, skeletal-muscle force, finger joint-angles, and effect of muscle-fatigue on the sEMG. The measured signals are filtered with best available filters and processed to capture the dynamic models for force and motion using system identification (SI), and other intelligent techniques. For fatigue analysis, different frequency-domain methods are used to analyze the change in the sEMG signals. All these research approaches are novel in the field and have a wide scope of applications for prosthetic control and rehabilitation purposes. This dissertation discusses these critical results and provides information on the future designs to study sEMG -- skeletal-muscle force, skeletal-muscle fatigue, and hand finger-joints movement relationships.

ISBN: 9781267195180Subjects--Topical Terms:

845403
Engineering, Biomedical.

Identification and Modeling of Surface EMG Signals, Skeletal-Muscle Forces, Skeletal-Muscle Fatigue, and Finger Joint-Angles for Smart Prosthetic Hand Design.
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245 1 0 $a Identification and Modeling of Surface EMG Signals, Skeletal-Muscle Forces, Skeletal-Muscle Fatigue, and Finger Joint-Angles for Smart Prosthetic Hand Design.
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500 $a Source: Dissertation Abstracts International, Volume: 73-06, Section: B, page: .
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