Smart Homes that Monitor Breathing and Heart Rate
Open accessAbstract
The evolution of ubiquitous sensing technologies has led to intelligent environments that can monitor and react to our daily activities, such as adapting our heating and cooling systems, responding to our gestures, and monitoring our elderly. In this paper, we ask whether it is possible for smart environments to monitor our vital signs remotely, without instrumenting our bodies. We introduce Vital-Radio, a wireless sensing technology that monitors breathing and heart rate without body contact. Vital-Radio exploits the fact that wireless signals are affected by motion in the environment, including chest movements due to inhaling and exhaling and skin vibrations due to heartbeats. We describe the operation of Vital-Radio and demonstrate through a user study that it can track users' breathing and heart rates with a median accuracy of 99%, even when users are 8~meters away from the device, or in a different room. Furthermore, it can monitor the vital signs of multiple people simultaneously. We envision that Vital-Radio can enable smart homes that monitor people's vital signs without body instrumentation, and actively contribute to their inhabitants' well-being.
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High frequency and sub-millimetre wavelength radio technologies have demonstrated the ability to capture physiological signals without body contact.
“In the past decade, high frequency and sub-millimetre wavelength radio technologies have demonstrated the ability to capture physiological signals without body contact.”
From The future of sleep health: a data-driven revolution in sleep science and medicine (2020) · cites this paper as [74]
Through signal processing, it is possible to extract biological information, such as breathing patterns, heart rate and full-body motion, from radio signals.
“Through signal processing, it is possible to extract biological information, such as breathing patterns, heart rate and full-body motion from these findings71,73–75.”
From The future of sleep health: a data-driven revolution in sleep science and medicine (2020) · cites this paper as [74]
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Wireless Sensing for Human Activity: A Survey
Liu, J., Liu, H., Chen, Y., Wang, Y., & Wang, C. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2934489 · Cited by 414 · see citing works
The future of sleep health: a data-driven revolution in sleep science and medicine
Perez-Pozuelo, I., Zhai, B., Palotti, J., Mall, R., Aupetit, M., Garcia-Gomez, J. M., Taheri, S., Guan, Y., & Fernandez-Luque, L. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0244-4 · Cited by 311 · see citing works
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Self-citationAllen, N. B., Nelson, B. W., Brent, D., & Auerbach, R. P. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.03.044 · Cited by 115 · see citing works
BodyCompass: Monitoring Sleep Posture with Wireless Signals
Yue, S., Yang, Y., Wang, H., Rahul, H., & Katabi, D. (2020) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · doi:10.1145/3397311 · Cited by 112 · see citing works
Self-citation“Combating replay attacks against voice assistants,”
Pradhan, S., Sun, W., Baig, G., & Qiu, L. (2019) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · doi:10.1145/3351258 · Cited by 67 · see citing works
Smart Insole-Based Indoor Localization System for Internet of Things Applications
Chen, D., Cao, H., Chen, H., Zhu, Z., Qian, X., Xu, W., & Huang, M.-C. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2915791 · Cited by 51 · see citing works
- Authors
- Adib, F., Mao, H., Kabelac, Z., Katabi, D., & Miller, R. C.
- Affiliations
- Massachusetts Institute of Technology (US)
- Venue
- Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2015-04-18
- Pages
- 837-846
- OpenAlex
- W2065726711
- Cited by
- 916
- References
- 1
- Citations by year
- 2026: 43 · 2025: 69 · 2024: 75 · 2023: 81 · 2022: 110 · 2021: 119 · 2020: 131 · 2019: 92 · 2018: 91 · 2017: 66 · 2016: 31 · 2015: 8
- FWCI
- 125.65
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- wireless sensing, respiratory monitoring, heart rate monitoring, home automation, ubiquitous sensing, skin vibration, remote patient monitoring
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