Finger Movements Recognition Using Naive Bayes Algorithm in Frequency Domain

Daniel Pamungkas, Novi Dharmayani

2022

Abstract

Rapid technological developments have led to various innovations to overcome existing problems, one of which is prosthetic hands to facilitate daily activities. The field of biomechanics studies and applies the concepts of technology, treatment, and diagnosis related to human activities, resulting in new technology in the form of electromyography (EMG). EMG signals are signals originating from human muscles when they contract or relax. This study aims to identify the Myo Armband sensor’s movement pattern of the human fingers. The Myo Armband sensor is placed on the forearm of the subject’s right hand to receive signals from the EMG. The data obtained will be converted to the frequency domain using FFT, then 70 percent of the data from the EMG signal is used as training data to get the results of each movement. The training results will be tested using 30 percent of the EMG signal data and classified using the Naive Bayes algorithm. The study’s results show that this system manages to identify the gesture around 80%.

Paper Citation

in Harvard Style

Pamungkas D. and Dharmayani N. (2022). Finger Movements Recognition Using Naive Bayes Algorithm in Frequency Domain. In Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES; ISBN 978-989-758-619-4, SciTePress, pages 777-780. DOI: 10.5220/0011880100003575

in Bibtex Style

@conference{icast-es22,
author={Daniel Pamungkas and Novi Dharmayani},
title={Finger Movements Recognition Using Naive Bayes Algorithm in Frequency Domain},
booktitle={Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES},
year={2022},
pages={777-780},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011880100003575},
isbn={978-989-758-619-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES
TI - Finger Movements Recognition Using Naive Bayes Algorithm in Frequency Domain
SN - 978-989-758-619-4
AU - Pamungkas D.
AU - Dharmayani N.
PY - 2022
SP - 777
EP - 780
DO - 10.5220/0011880100003575
PB - SciTePress