Athaya Pradipa Adiwangsa, Pradini Puspitaningayu, Hapsari Peni Agustin Tjahyaningtijas, Lusia Rakhmawati, Nurhayati, Nobuo Funabiki
The rising of chronic degenerative diseases in global society due to changes in health trends has been a major concern in the last decade. Strength training has been proven to be effective in improving one's metabolism and regulating blood glucose levels, potentially the solution to the current situation. However, not everyone has the time, resources, and access to strength training facilities such as the gym or personal trainer. This paper proposed Strength Training Posture Repetition Recognition for Automated Exercise Trainer or STRAPS to assist people in exercising strength training by themselves. STRAPS offers image content for 2 strength training types, bicep curl and back squat, containing model action of the instructor to be followed by the user and real-time dynamic pose evaluation based on the number of successful repetition. The evaluation was done by applying STRAPS with 2 types of strength training to 4 people of various ages and body proportions from Indonesia, and to confirm the proposal's effectiveness. © 2024 IEEE.
Universitas Negeri Surabaya, Dept. of Electrical Engineering, Surabaya, Indonesia; Okayama University, Graduate School of Natural Science and Technology, Okayama, Japan
