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Investigation of the optimal sensor location and classifier for human motion classification

Human motion monitoring by means of wearable technologies is not uncommon nowadays. This demonstrates the growing awareness of the importance of healthy lifestyle. Human body motion involves the movement of multiple muscles and joints. However, the optimal location of sensor placement on the body to...

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Main Authors: Anuar, Mohamed, Nur Aqilah, Othman, Hamzah, Ahmad, Mohd Hasnun Ariff, Hassan
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/39343/1/Investigation%20of%20the%20optimal%20sensor%20location%20and%20classifier%20for%20human.pdf
http://umpir.ump.edu.my/id/eprint/39343/2/Investigation%20of%20the%20optimal%20sensor%20location%20and%20classifier%20for%20human%20motion%20classification_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39343/
https://doi.org/10.1109/ICCSCE54767.2022.9935635
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spelling my.ump.umpir.393432023-11-21T01:11:56Z http://umpir.ump.edu.my/id/eprint/39343/ Investigation of the optimal sensor location and classifier for human motion classification Anuar, Mohamed Nur Aqilah, Othman Hamzah, Ahmad Mohd Hasnun Ariff, Hassan T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures Human motion monitoring by means of wearable technologies is not uncommon nowadays. This demonstrates the growing awareness of the importance of healthy lifestyle. Human body motion involves the movement of multiple muscles and joints. However, the optimal location of sensor placement on the body to record the motion in daily activities has not been well understood. This study aims to find the best sensor location for this purpose among three locations on the body, that is on the back, shank, or wrist. In addition, this study seeks to find the best classification algorithm for human daily activities. The data recorded at these three locations were analysed using several classification algorithms in both Orange software and MATLAB. The results show that the sensor on the wrist provided the best classification result, thereby suggesting that wrist is the best place on the body to place the sensor for human motion monitoring. With regards to classification algorithm, we found that Neural Network provides the most accurate classification as compared to other algorithms. Future development of wearables should look into integrating classification algorithm in the system, thus the human motion monitoring will provide a richer information and not only limited to number of steps and calories burned. Institute of Electrical and Electronics Engineers Inc. 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39343/1/Investigation%20of%20the%20optimal%20sensor%20location%20and%20classifier%20for%20human.pdf pdf en http://umpir.ump.edu.my/id/eprint/39343/2/Investigation%20of%20the%20optimal%20sensor%20location%20and%20classifier%20for%20human%20motion%20classification_ABS.pdf Anuar, Mohamed and Nur Aqilah, Othman and Hamzah, Ahmad and Mohd Hasnun Ariff, Hassan (2022) Investigation of the optimal sensor location and classifier for human motion classification. In: ICCSCE 2022 - Proceedings: 2022 12th IEEE International Conference on Control System, Computing and Engineering, 21-22 October 2022 , Penang. pp. 142-146. (184194). ISBN 978-166548339-1 https://doi.org/10.1109/ICCSCE54767.2022.9935635
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
TS Manufactures
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
TS Manufactures
Anuar, Mohamed
Nur Aqilah, Othman
Hamzah, Ahmad
Mohd Hasnun Ariff, Hassan
Investigation of the optimal sensor location and classifier for human motion classification
description Human motion monitoring by means of wearable technologies is not uncommon nowadays. This demonstrates the growing awareness of the importance of healthy lifestyle. Human body motion involves the movement of multiple muscles and joints. However, the optimal location of sensor placement on the body to record the motion in daily activities has not been well understood. This study aims to find the best sensor location for this purpose among three locations on the body, that is on the back, shank, or wrist. In addition, this study seeks to find the best classification algorithm for human daily activities. The data recorded at these three locations were analysed using several classification algorithms in both Orange software and MATLAB. The results show that the sensor on the wrist provided the best classification result, thereby suggesting that wrist is the best place on the body to place the sensor for human motion monitoring. With regards to classification algorithm, we found that Neural Network provides the most accurate classification as compared to other algorithms. Future development of wearables should look into integrating classification algorithm in the system, thus the human motion monitoring will provide a richer information and not only limited to number of steps and calories burned.
format Conference or Workshop Item
author Anuar, Mohamed
Nur Aqilah, Othman
Hamzah, Ahmad
Mohd Hasnun Ariff, Hassan
author_facet Anuar, Mohamed
Nur Aqilah, Othman
Hamzah, Ahmad
Mohd Hasnun Ariff, Hassan
author_sort Anuar, Mohamed
title Investigation of the optimal sensor location and classifier for human motion classification
title_short Investigation of the optimal sensor location and classifier for human motion classification
title_full Investigation of the optimal sensor location and classifier for human motion classification
title_fullStr Investigation of the optimal sensor location and classifier for human motion classification
title_full_unstemmed Investigation of the optimal sensor location and classifier for human motion classification
title_sort investigation of the optimal sensor location and classifier for human motion classification
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/39343/1/Investigation%20of%20the%20optimal%20sensor%20location%20and%20classifier%20for%20human.pdf
http://umpir.ump.edu.my/id/eprint/39343/2/Investigation%20of%20the%20optimal%20sensor%20location%20and%20classifier%20for%20human%20motion%20classification_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39343/
https://doi.org/10.1109/ICCSCE54767.2022.9935635
_version_ 1822923860270383104
score 13.239859

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