Author

Alviandiky Firmansyah

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Evaluation of Random Forest and LSTM for IMU-Based Wrist Movement Classification with sEMG Monitoring

This study evaluates Random Forest and Long Short-Term Memory and Long Short-Term Memory for five-class wrist-movement classification using six-channel inertial measurement unit (IMU) data, while surface electromyography (sEMG) is used for RMS-based muscle-activity monitoring.

M. Restu, Alviandiky Firmansyah, Alwi Harliansyah Hrp · 0 citations