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Journals / Turkish Journal of Electrical Engineering and Computer Science / 1999 / Cilt: 7 - Sayı: 1-3

Differentiating Type of Muscle Movement via AR Modeling and Neural Network Classification

Bekir KARLIK
Pages
45–52
Publication Date
1999-01-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

At the output layer, for 5000 iterations, six movements were distinguished at a high accuracy of 97.6%.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of this study is to classify electromyogram (EMG) signals for controlling multifunction proshetic devices.
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Key Findings & Data:Autoregressive (AR) parameters of a1, a2, a3, a4 and their signal power obtained from different arm muscle motions were applied to the input of ANN, which is a multilayer perceptron.
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Conclusion & Impact:At the output layer, for 5000 iterations, six movements were distinguished at a high accuracy of 97.6%.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Myoelectric signals · artificial neural networks · classification

Abstract

The aim of this study is to classify electromyogram (EMG) signals for controlling multifunction proshetic devices. An artificial neural network (ANN) implementation was used for this purpose. Autoregressive (AR) parameters of a1, a2, a3, a4 and their signal power obtained from different arm muscle motions were applied to the input of ANN, which is a multilayer perceptron. At the output layer, for 5000 iterations, six movements were distinguished at a high accuracy of 97.6%.

Özet

The aim of this study is to classify electromyogram (EMG) signals for controlling multifunction proshetic devices. An artificial neural network (ANN) implementation was used for this purpose. Autoregressive (AR) parameters of a1, a2, a3, a4 and their signal power obtained from different arm muscle motions were applied to the input of ANN, which is a multilayer perceptron. At the output layer, for 5000 iterations, six movements were distinguished at a high accuracy of 97.6%.

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Cite This Article

KARLIK, B. (1999). Differentiating Type of Muscle Movement via AR Modeling and Neural Network Classification. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 7 - Sayı: 1-3, 45–52. https://ajindex.com/articles/189214

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