research-article

MindfulWatch: A Smartwatch-Based System For Real-Time Respiration Monitoring During Meditation

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Linlin TuAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 1, Issue 3

Article No.: 57, Pages 1 - 19

https://doi.org/10.1145/3130922

Published: 11 September 2017 Publication History

Abstract

With a wealth of scientifically proven health benefits, meditation was enjoyed by about 18 million people in the U.S. alone, as of 2012. Yet, there remains a stunning lack of convenient tools for promoting long-term and effective meditation practice. In this paper, we present MindfulWatch, a practical smartwatch-based sensing system that monitors respiration in real-time during meditation -- offering essential biosignals that can potentially be used to empower various future applications such as tracking changes in breathing pattern, offering real-time guidance, and providing an accurate bio-marker for meditation research. To this end, MindfulWatch is designed to be convenient for everyday use with no training required. Operating solely on a smartwatch, MindfulWatch can immediately reach the growing population of smartwatch users, making it ideal for longitudinal data collection for meditation studies. Specifically, it utilizes motion sensors to sense the subtle “micro” wrist rotation (0.01 rad/s) induced by respiration. To accurately capture breathing, we developed a novel self-adaptive model that tracks changes in both breathing pattern and meditation posture over time. MindfulWatch was evaluated based on data from 36 real-world meditation sessions (8.7 hours, 11 subjects). The results suggest that MindfulWatch offers reliable real-time respiratory timing measurement (70% errors under 0.5 seconds).

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Index Terms

MindfulWatch: A Smartwatch-Based System For Real-Time Respiration Monitoring During Meditation
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 1, Issue 3

September 2017

2023 pages

EISSN:2474-9567

DOI:10.1145/3139486

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Copyright © 2017 ACM.

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Publication History

Published: 11 September 2017

Accepted: 01 July 2017

Revised: 01 May 2017

Received: 01 February 2017

Published in IMWUT Volume 1, Issue 3

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Cited By

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https://dl.acm.org/doi/10.1145/3678568
Xie WXu CGong YWang YLiu YZhang JZhang QZheng ZYang S(2024)DeepBreath: Breathing Exercise Assessment with a Depth CameraProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785198:3(1-26)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678519
Lin YChu E(2024)Evaluation of the Practicability of Internet of Things in Fighting Against COVID-19IEEE Internet of Things Journal10.1109/JIOT.2023.331724811:5(8064-8077)Online publication date: 1-Mar-2024
https://doi.org/10.1109/JIOT.2023.3317248
Song YLi BLuo DXie ZPhillips BKe YSong W(2024)Engagement-Free and Contactless Bed Occupancy and Vital Signs MonitoringIEEE Internet of Things Journal10.1109/JIOT.2023.331667411:5(7935-7947)Online publication date: 1-Mar-2024
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Yin YXie LJiang ZXiao FCao JLu S(2024)A Systematic Review of Human Activity Recognition Based on Mobile Devices: Overview, Progress and TrendsIEEE Communications Surveys & Tutorials10.1109/COMST.2024.335759126:2(890-929)Online publication date: 23-Jan-2024
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