Rizal, Aminuddin and Taufiqqurrachman, Taufiqqurrachman (2020) Step Rate Estimator from Wearable Photopletysmography Signal. In: 5th International Conference on New Media Studies, 9-11 Oct. 2019, Bali, Indonesia.
Full text not available from this repository.Abstract
Smart wearable watch (smartwatch) currently becomes popular device as personal activity companion. Nowadays, most of smartwatch has been equipped for gait monitoring. However, the performance of the system for step measurement is relying on conventional sensor such as accelerometer. In this paper we describe our new novel system about step rate estimation by using Photopletysmography (PPG) signal. One of our main goal is to reduce the number of sensor used. Our backbone method are based on an adaptive intrinsic mode function (IMF) selection method for Complete Ensemble Empirical Mode Decomposition (CEEMD) in step measurement. We made our own public dataset recorded from 5 subjects with 3 different activity state (stand still, walk, and run). The experimental results show our system achieve overall over 90% accuracy for all activity.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Keywords: | complete ensemble empirical mode decomposition , exercise activity , photopletysmography , wearable device |
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 004 Computer Science, Data Processing, Hardware 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming 600 Technology (Applied Sciences) > 600 Technology > 600 Technology 600 Technology (Applied Sciences) > 610 Medicine and Health > 613 Personal Health and Safety |
| Divisions: | Faculty of Engineering & Informatics > Computer Engineering |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 02 Dec 2021 14:09 |
| Last Modified: | 02 Dec 2021 14:09 |
| URI: | https://kc.umn.ac.id/id/eprint/19318 |
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