Surface electromyography : fundamentals, computational techniques and clinical applications / Denise Mitchell, editor.
Material type: TextSeries: Physical medicine and rehabilitationPublisher: New York : Nova Biomedical, [2016]Description: 1 online resourceContent type:- text
- computer
- online resource
- 9781536102222
- 1536102229
- 616.7/407547 23
- RC77.5
Item type | Home library | Collection | Call number | Materials specified | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|---|
Electronic-Books | OPJGU Sonepat- Campus | E-Books EBSCO | Available |
Includes bibliographical references and index.
Description based on print version record and CIP data provided by publisher.
Preface; Chapter 1; Neuromuscular Activation in Swimming and Water Polo; Abstract; Introduction; Brief Highlight on the sEMG Fundamentals; Frequency Analysis of the Studied Topics; Muscles; Populations; Types of Equipment and Data Collection; Data Treatment and Variables; Main Results; Relevance to Practice and Further Research Interests; Conclusion; References; Biographical Sketch; Chapter 2; The Clinical Use of sEMG in the Fields of Kinesiology and Rehabilitation: A Review; Abstract; Introduction; Processing Method and Application of EMG Data
1. Applications of sEMG in the Evaluation of the Quality and Quantity of Muscle Activity in Movement2. Applications of sEMG in Neuromuscular Re-Training with Biofeedback; 3. Application of sEMG in the Evaluation of Muscle Fatigue; Conclusion; Acknowledgment; References; Biographical Sketch; Chapter 3; The Use of sEMG Signals as a Natural Control Interface; Abstract; Introduction; Experimental Methodology; sEMG Signal Acquisition; Digital Filter; Signal Segmentation; Signal Rectification and Normalization; Feature Extraction; Time Domain; Integrated EMG (IEMG); Mean Absolute Value (MAV)
Root Mean Square (RMS)Variance (VAR); Waveform Length (WL); Zero Crossing (ZC); Kurtosis (KURT); Skewness (SKW); Frequency Domain; Auto-Regressive coefficients (AR); Median Frequency (MDF); Mean Frequency (MNF); sEMG Signal Processing and Classification; Signal Processing; Signal Classification; Support Vector Machines; Logistic Regression; Study Cases Using LR and SVM Methods; Conclusion; References; Chapter 4; Use of Surface Electromyography (SEMG) in the Evaluation of the Effectiveness of Orthopedic Insoles; Institute of Sport Sciences, Saarland University,; Saarbruecken, Germany; Abstract
IntroductionEMG Measurement; Test Procedure; EMG Data Evaluation; Results; Conclusion; References; Biographical Sketch; Related Nova Publications; Electromyography: New Developments, Procedures and Applications; Graduate School of Engineering, University of Fukui, Japan; Bibliography; Index; Blank Page
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