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NEAT Activity Detection using Smartwatch at Low Sampling Frequency

Dewan, Ankita; Gunturi, Venkata M.V.; Naik, Vinayak; Dutta, Kousik Kumar

Authors

Ankita Dewan

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

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Accepted manuscript (3.1 Mb)
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© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.





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