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All Journal Indonesian Journal of Electronics and Instrumentation Systems
Catur Atmaji
Faculty of Mathematics and Natural Sciences, Gadjah Mada University, Bulaksumur, Yogyakarta, Indonesia 55281
Electrical & Electronics Engineering

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Journal : Indonesian Journal of Electronics and Instrumentation Systems

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Analisis Parameter Windowing STFT Pada Klasifikasi Gerakan Jari Berbasis EMG Widagdo, Rohadi; Kusumaning Putri, Diyah Utami; Atmaji, Catur
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 14, No 2 (2024): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.90046

Abstract

A spectrogram is essential in analyzing EMG signals for finger motion recognition. It relies on STFT parameters like window size, overlap, and window type for accuracy. Optimal parameter selection is challenging due to EMG sensitivity to minor changes affecting recognition accuracy. The study employs AlexNet to recognize spectrograms from EMG signals, using various STFT parameter combinations for five finger movements.Results show that a window size of 100, 50% overlap, and Hamming window outperform other combinations. A window size of 100 consistently outperforms 200 and 300, while a 50% overlap is better than 25% and 75%. Hanning window types consistently outperform Hamming, Blackman, and Tukey. This research streamlines EMG spectrogram analysis for efficient finger motion recognition.
Co-Authors Kusumaning Putri, Diyah Utami widagdo, rohadi