Developing a Body Posture Detection for Fitness

The Body Posture Detection System for Fitness is an innovative technology that aims to enhance exercise technique and movement patterns by providing real-time monitoring and feedback.It utilizes computer vision and machine learning algorithms to track and analyze body movements during fitness.The system's ability to provide immediate feedback and correction significantly improves exercise effectiveness and user safety.It also comes with the userfriendliness of the system, potentially incorporating a Graphical User Interface (GUI) for easy navigation and accessibility.To address time and budget constraints, the approach of this research will choose the Rapid Application Development (RAD) Model as the system development approach.This methodology consists of four phases which are: requirement planning, user design, rapid construction, and transition, and each is accompanied by deliverables.These efforts are aimed at enhancing the functionality and usability of the Body Posture Detection System for Fitness while addressing user needs and optimizing fitness training experiences.

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Publication Details

Journal
Proceedings of International Conference on Artificial Life and Robotics
Published
2025-02-13
DOI
https://doi.org/10.5954/icarob.2025.os20-4
Primary Topic
Human Pose and Action Recognition
Type
article
Field-Weighted Citation Impact
0.00
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article

Developing a Body Posture Detection for Fitness

Kasthuri Subaramaniam, Abdul Samad Shibghatullah, Chit Su Mon, Kai Xuan Chong
Proceedings of International Conference on Artificial Life and Robotics
Human Pose and Action Recognition
article

Developing a Body Posture Detection for Fitness

Kasthuri Subaramaniam, Abdul Samad Shibghatullah, Chit Su Mon, Kai Xuan Chong
article en

Abstract

The Body Posture Detection System for Fitness is an innovative technology that aims to enhance exercise technique and movement patterns by providing real-time monitoring and feedback.It utilizes computer vision and machine learning algorithms to track and analyze body movements during fitness.The system's ability to provide immediate feedback and correction significantly improves exercise effectiveness and user safety.It also comes with the userfriendliness of the system, potentially incorporating a Graphical User Interface (GUI) for easy navigation and accessibility.To address time and budget constraints, the approach of this research will choose the Rapid Application Development (RAD) Model as the system development approach.This methodology consists of four phases which are: requirement planning, user design, rapid construction, and transition, and each is accompanied by deliverables.These efforts are aimed at enhancing the functionality and usability of the Body Posture Detection System for Fitness while addressing user needs and optimizing fitness training experiences.

Proceedings of International Conference on Artificial Life and RoboticsVol. 30
University of Malaya (MY), Heriot-Watt University Malaysia (MY), UCSI University (MY), Universiti Tenaga Nasional (MY)
Openalex Percentile: Top 68%
Human Pose and Action Recognition
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