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Towards a Toolkit for Free Living Wearable Development

Published: 24 April 2023 Publication History

Abstract

Real-world Data collection and analysis is a significant pain point in wearable device development, requiring multidisciplinary skills in: embedded systems, application development, data science, and domain expert knowledge. In this work, we first build motivation based on previous experiences in wearable development, then introduce a toolkit for data collection and iterative development to reduce engineering efforts for free living experimentation of wearable devices. This toolkit utilizes Bluetooth Low Energy and an adaptive mobile application to help researchers quickly test new hardware, collect meaningful data, and assist in developing embedded algorithms with minimal intermediary code changes. We demonstrate the utility of our toolkit by collecting data in-the-wild from multiple sensors using a prototype wearable and a ground truth heart rate sensor. In addition, we demonstrate the toolkit’s capabilities with a baseline throughput test. Finally, we show how this tool has helped in early development of a new custom device. Our work is released as open source and welcomes contributions in an effort to broaden the tookit’s utility for the wearable research community.

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cover image ACM Conferences
UbiComp/ISWC '22 Adjunct: Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers
September 2022
538 pages
ISBN:9781450394239
DOI:10.1145/3544793
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 24 April 2023

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Author Tags

  1. Health
  2. Machine Learning
  3. Wearables

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  • DARPA

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Overall Acceptance Rate 764 of 2,912 submissions, 26%

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