Human activity recognition based on wrist PPG via the ensemble method
Human activity recognition via Electrocardiography (ECG) and Photoplethysmography (PPG) is extensively researched. While ECG requires less filtering and is less prone to disturbance and artifacts, nonetheless, PPG is cheaper and widely available in smart devices, making it a desired alternative. In...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Korean Institute of Communication Sciences
2022
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/35111/ http://umpir.ump.edu.my/id/eprint/35111/1/Human%20activity%20recognition%20based%20on%20wrist%20PPG%20via%20the%20ensemble%20method.pdf |
| _version_ | 1848824693008629760 |
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| author | Almanifi, Omair Rashed Abdulwareth Ismail, Mohd Khairuddin Mohd Azraai, Mohd Razman Musa, Rabiu Muazu Anwar, P. P. Abdul Majeed |
| author_facet | Almanifi, Omair Rashed Abdulwareth Ismail, Mohd Khairuddin Mohd Azraai, Mohd Razman Musa, Rabiu Muazu Anwar, P. P. Abdul Majeed |
| author_sort | Almanifi, Omair Rashed Abdulwareth |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Human activity recognition via Electrocardiography (ECG) and Photoplethysmography (PPG) is extensively researched. While ECG requires less filtering and is less prone to disturbance and artifacts, nonetheless, PPG is cheaper and widely available in smart devices, making it a desired alternative. In this study, we explore the employment of the ensemble method with several pre-trained machine learning models namely Resnet50V2, MobileNetV2, and Xception for the classification of wrist PPG data of human activity, in comparison to its ECG counterpart. The study produced promising results with a test classification accuracy of 88.91% and 94.28% for PPG and ECG, respectively. |
| first_indexed | 2025-11-15T03:17:05Z |
| format | Article |
| id | ump-35111 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:17:05Z |
| publishDate | 2022 |
| publisher | Korean Institute of Communication Sciences |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-351112022-10-27T00:55:12Z http://umpir.ump.edu.my/id/eprint/35111/ Human activity recognition based on wrist PPG via the ensemble method Almanifi, Omair Rashed Abdulwareth Ismail, Mohd Khairuddin Mohd Azraai, Mohd Razman Musa, Rabiu Muazu Anwar, P. P. Abdul Majeed T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures Human activity recognition via Electrocardiography (ECG) and Photoplethysmography (PPG) is extensively researched. While ECG requires less filtering and is less prone to disturbance and artifacts, nonetheless, PPG is cheaper and widely available in smart devices, making it a desired alternative. In this study, we explore the employment of the ensemble method with several pre-trained machine learning models namely Resnet50V2, MobileNetV2, and Xception for the classification of wrist PPG data of human activity, in comparison to its ECG counterpart. The study produced promising results with a test classification accuracy of 88.91% and 94.28% for PPG and ECG, respectively. Korean Institute of Communication Sciences 2022 Article PeerReviewed pdf en cc_by_nc_nd_4 http://umpir.ump.edu.my/id/eprint/35111/1/Human%20activity%20recognition%20based%20on%20wrist%20PPG%20via%20the%20ensemble%20method.pdf Almanifi, Omair Rashed Abdulwareth and Ismail, Mohd Khairuddin and Mohd Azraai, Mohd Razman and Musa, Rabiu Muazu and Anwar, P. P. Abdul Majeed (2022) Human activity recognition based on wrist PPG via the ensemble method. ICT Express. pp. 1-5. ISSN 2405-9595. (In Press / Online First) (In Press / Online First) https://doi.org/10.1016/j.icte.2022.03.006 https://doi.org/10.1016/j.icte.2022.03.006 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures Almanifi, Omair Rashed Abdulwareth Ismail, Mohd Khairuddin Mohd Azraai, Mohd Razman Musa, Rabiu Muazu Anwar, P. P. Abdul Majeed Human activity recognition based on wrist PPG via the ensemble method |
| title | Human activity recognition based on wrist PPG via the ensemble method |
| title_full | Human activity recognition based on wrist PPG via the ensemble method |
| title_fullStr | Human activity recognition based on wrist PPG via the ensemble method |
| title_full_unstemmed | Human activity recognition based on wrist PPG via the ensemble method |
| title_short | Human activity recognition based on wrist PPG via the ensemble method |
| title_sort | human activity recognition based on wrist ppg via the ensemble method |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/35111/ http://umpir.ump.edu.my/id/eprint/35111/ http://umpir.ump.edu.my/id/eprint/35111/ http://umpir.ump.edu.my/id/eprint/35111/1/Human%20activity%20recognition%20based%20on%20wrist%20PPG%20via%20the%20ensemble%20method.pdf |