Embedded system application development on Raspberry Pi 4 – personal A.I trainer (PAT) device for injury prevention
The fitness industry has experienced significant growth in recent years, with an increasing number of people signing up for gym memberships. When it comes to working out however, there may be some who struggle with maintaining the proper form, which can lead to injury and reduce the effectiveness of...
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التنسيق: | Final Year Project |
اللغة: | English |
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Nanyang Technological University
2023
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الوصول للمادة أونلاين: | https://hdl.handle.net/10356/167224 |
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sg-ntu-dr.10356-1672242023-07-07T15:44:26Z Embedded system application development on Raspberry Pi 4 – personal A.I trainer (PAT) device for injury prevention Muhammad Al-Safiq Bin Sapari Chong Yong Kim School of Electrical and Electronic Engineering EYKCHONG@ntu.edu.sg Engineering::Electrical and electronic engineering::Computer hardware, software and systems The fitness industry has experienced significant growth in recent years, with an increasing number of people signing up for gym memberships. When it comes to working out however, there may be some who struggle with maintaining the proper form, which can lead to injury and reduce the effectiveness of their workouts. To address this issue, this project aims to develop a portable Personal A.I Trainer (PAT) device that uses the MediaPipe pose estimation model to detect key points on the user's body and classify their form. By identifying areas where form correction is needed, the PAT device can help users exercise more safely and effectively. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-24T14:03:50Z 2023-05-24T14:03:50Z 2023 Final Year Project (FYP) Muhammad Al-Safiq Bin Sapari (2023). Embedded system application development on Raspberry Pi 4 – personal A.I trainer (PAT) device for injury prevention. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167224 https://hdl.handle.net/10356/167224 en A3077-221 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering::Computer hardware, software and systems |
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Engineering::Electrical and electronic engineering::Computer hardware, software and systems Muhammad Al-Safiq Bin Sapari Embedded system application development on Raspberry Pi 4 – personal A.I trainer (PAT) device for injury prevention |
description |
The fitness industry has experienced significant growth in recent years, with an increasing number of people signing up for gym memberships. When it comes to working out however, there may be some who struggle with maintaining the proper form, which can lead to injury and reduce the effectiveness of their workouts. To address this issue, this project aims to develop a portable Personal A.I Trainer (PAT) device that uses the MediaPipe pose estimation model to detect key points on the user's body and classify their form. By identifying areas where form correction is needed, the PAT device can help users exercise more safely and effectively. |
author2 |
Chong Yong Kim |
author_facet |
Chong Yong Kim Muhammad Al-Safiq Bin Sapari |
format |
Final Year Project |
author |
Muhammad Al-Safiq Bin Sapari |
author_sort |
Muhammad Al-Safiq Bin Sapari |
title |
Embedded system application development on Raspberry Pi 4 – personal A.I trainer (PAT) device for injury prevention |
title_short |
Embedded system application development on Raspberry Pi 4 – personal A.I trainer (PAT) device for injury prevention |
title_full |
Embedded system application development on Raspberry Pi 4 – personal A.I trainer (PAT) device for injury prevention |
title_fullStr |
Embedded system application development on Raspberry Pi 4 – personal A.I trainer (PAT) device for injury prevention |
title_full_unstemmed |
Embedded system application development on Raspberry Pi 4 – personal A.I trainer (PAT) device for injury prevention |
title_sort |
embedded system application development on raspberry pi 4 – personal a.i trainer (pat) device for injury prevention |
publisher |
Nanyang Technological University |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/167224 |
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1772827905353580544 |