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Feature Extraction and Classification Between Control and Parkinson’s Using EMG Signal

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Cognitive Informatics and Soft Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1040))

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Abstract

The main objective of the proposed work is to classify and differentiate Parkinson’s disease from other neuromuscular disease with the help of Electromyogram (EMG) signal. An Electromyogram signal detects the electric potential generated by muscle cells when these muscle cells contract or relax. However, these electromyography signal itself failed to differentiate between these neuromuscular diseases as their symptoms are almost the same. Therefore, certain features were examined and studied like average distance peaks, discrete wavelet functions, entropy, band power, peak-magnitude-to-RMS ratio, mean complex cepstrum and maximum value of single-sided amplitude, etc. These features were extracted, and with these features, we can differentiate between these neuromuscular diseases including Parkinson’s disease. Two classifiers were used for detection and classification of Parkinson’s, they were Decision Tree and Naive Bayes. However, the accuracy in Decision Tree was found out to be 88.38%, while the accuracy in Naive Bayes was found out to be 54.07%.

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Authors and Affiliations

  1. Department of Electrical & Electronics Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Gangtok, Sikkim, India

    Roselene Subba & Akash Kumar Bhoi

Authors
  1. Roselene Subba
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  2. Akash Kumar Bhoi
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Corresponding author

Correspondence to Akash Kumar Bhoi .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Bhubaneswar, Odisha, India

    Pradeep Kumar Mallick

  2. Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  3. Department of Electrical and Electronics Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Rangpo, India

    Akash Kumar Bhoi

  4. Division of Information and Communication, Baekseok University, Cheonan-si, Ch’ungch’ong-namdo, Korea (Republic of)

    Gyoo-Soo Chae

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Subba, R., Bhoi, A.K. (2020). Feature Extraction and Classification Between Control and Parkinson’s Using EMG Signal. In: Mallick, P., Balas, V., Bhoi, A., Chae, GS. (eds) Cognitive Informatics and Soft Computing. Advances in Intelligent Systems and Computing, vol 1040. Springer, Singapore. https://doi.org/10.1007/978-981-15-1451-7_5

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