Ankita Dewan
NEAT Activity Detection using Smartwatch at Low Sampling Frequency
Dewan, Ankita; Gunturi, Venkata M.V.; Naik, Vinayak; Dutta, Kousik Kumar
Authors
Dr Venkata Maruti Viswanath Gunturi V.Gunturi@hull.ac.uk
Lecturer in Computer Science
Vinayak Naik
Kousik Kumar Dutta
Abstract
Our paper aims to build a classification model to discern the typical NEAT (Non-Exercise Activity Thermogenesis) activities done in a home setting. The concept of NEAT is broadly defined as the energy spent in everything which is not sleeping, eating, or a traditional form of physical exercise. We focus on the following NEAT and non-NEAT activities in this paper - cooking, sweeping, mopping, walking, climbing up, climbing down, and non-NEAT activities (e.g., watching television and working on a desk). This aim is to build a classification model which can work with data sampled at a low frequency of 1Hz. However, building such a classifier is non-trivial because the NEAT activities are not easily separable in low-frequency data. The state-of-the-art in the area of human activity recognition either uses multiple physical devices (e.g., accelerometers on arms, waist, and feet) for data collection or use data that is sampled at high frequency (20Hz or above). In contrast, our model performs NEAT activity recognition using data sampled at 1Hz and from a single smartwatch worn on the dominant hand. Thus, making it more energy-efficient and easily usable for widespread use. We evaluate our proposed model using actual data collected on a smartwatch, and we compare it with alternative models. Our results indicate that the proposed model is able to achieve much higher accuracy than the alternative approaches.
Citation
Dewan, A., Gunturi, V. M., Naik, V., & Dutta, K. K. (2021, October). NEAT Activity Detection using Smartwatch at Low Sampling Frequency. Presented at 2021 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People, and Smart City Innovations, SmartWorld/ScalCom/UIC/ATC/IoP/SCI 2021, Atlanta, GA, USA
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 2021 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People, and Smart City Innovations, SmartWorld/ScalCom/UIC/ATC/IoP/SCI 2021 |
Start Date | Oct 18, 2021 |
End Date | Oct 21, 2021 |
Acceptance Date | Jul 14, 2021 |
Online Publication Date | Nov 18, 2021 |
Publication Date | Nov 18, 2021 |
Deposit Date | Sep 27, 2023 |
Publicly Available Date | Jan 13, 2025 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Pages | 25-32 |
Series Title | Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC |
ISBN | 9781665412360 |
DOI | https://doi.org/10.1109/SWC50871.2021.00014 |
Public URL | https://hull-repository.worktribe.com/output/4388320 |
Files
Accepted manuscript
(3.1 Mb)
PDF
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