Pengenalan Pola Gerakan Jari dengan Algoritma LDA Secara Waktu Sesungguhnya

Daniel S Pamungkas (Politeknik Negeri Batam)
Wahyu Pardede (Politeknik Negeri Batam)
Sumantri K Risandrya (Politeknik Negeri Batam)

Proceeding Applied Business and Engineering Conference
Vol. 10 (2022): 10th Applied Business and Engineering Conference

Hands are one of the body parts that have an important role for living things, especially humans.Most of the activities that humans do require the help of hands. But not all humans have perfect hands orfunction like hands in general because of the impact of genetic disorders or the result of accidents. This iscertainly a very disturbing problem for people with disabilities to live their daily lives. In this study, the authoruses a fabricated device from Thalmic Labs named Myo Armband. This tool was created for gaming purposes,computer control, and so on. However, this tool is also widely used for the benefit of technology development,especially in the health sector. Myo Armband has eight Electromyograph (EMG) sensors that are able to recordand recognize every activity of arm muscle movement. In this study, the EMG signal is recorded and processedwhich is intended to distinguish each hand movement based on the muscle signal read by the EMG sensor. Afterthe EMG signal is recorded, the EMG signal will be read and continued with the training phase. After obtainingthe training weights, the results will be used at the testing phase and classification will be carried out. In theclassification process, the writer chose the Linear Discriminant Analysis (LDA) method. This method waschosen as a method for classifying finger movement pattern recognition. The percentage of success in the studyup to 76% Furthermore, after getting the conclusions from this study, the authors hope that this research can be areference for the development of making hand robots, especially for medical needs.