Recognition of Hand Movement for Training Motor Skill of Children With Autism Spectrum Disorder (ASD) Using Myo Gestures Control Armband and Artificial Neural Network

Autor:	M. F. Syahputra, A. Prasetyo, S. M. Hardi
Rok vydání:	2021
Předmět:	History medicine.medical_specialty Artificial neural network Movement (music) Training (meteorology) medicine.disease Computer Science Applications Education Physical medicine and rehabilitation Autism spectrum disorder medicine Control (linguistics) Psychology Motor skill Gesture
Zdroj:	Journal of Physics: Conference Series. 1898:012005
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1898/1/012005
Popis:	Autism disorder causes sufferers to tend to lag behind other children in understanding and accepting the stimuli given, due to the patient’s inability to focus attention on the stimulation given. One of the therapies used to train autistic sufferers is the help of technology. One of the technologies used is the Myo Gestures Control Armband which is equipped with several sensors that can recognize hand and arm movements using the Artificial Neural Network method which adopts a thought through a mechanism that affects the human brain, both for processing various signal elements received, tolerance of errors, and also parallel processing. In this study, there are five movements classified as Ok, Fist, Like, Rock, and Spock movements to train motor movements of children with autism. With this system in the future it can become a method of therapy that is carried out at home with the supervision and control of a therapist so that it can improve the development of hand motor skills in children with autism which can be seen through a graph of the development of movements per day displayed on the system.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::42b5cfd69115f8049cb4ec6948be127a https://doi.org/10.1088/1742-6596/1898/1/012005 Zobrazit plný text záznamu