Monitoring a person’s heart rate and respiratory rate on a shared bed using geophones

Zhenhua Jia, Chenren Xu, Amelie Bonde, Jingxian Wang, Sugang Li, Yanyong Zhang, Richard E. Howard, Pei Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

31 Scopus citations

Abstract

Using geophones to sense bed vibrations caused by ballistic force has shown great potential in monitoring a person’s heart rate during sleep. It does not require a special mattress or sheets, and the user is free to move around and change position during sleep. Earlier work has studied how to process the geophone signal to detect heartbeats when a single subject occupies the entire bed. In this study, we develop a system called VitalMon, aiming to monitor a person’s respiratory rate as well as heart rate, even when she is sharing a bed with another person. In such situations, the vibrations from both persons are mixed together. VitalMon first separates the two heartbeat signals, and then distinguishes the respiration signal from the heartbeat signal for each person. Our heartbeat separation algorithm relies on the spatial difference between two signal sources with respect to each vibration sensor, and our respiration extraction algorithm deciphers the breathing rate embedded in amplitude fluctuation of the heartbeat signal. We have developed a prototype bed to evaluate the proposed algorithms. A total of 86 subjects participated in our study, and we collected 5084 geophone samples, totaling 56 hours of data. We show that our technique is accurate – its breathing rate estimation error for a single person is 0.38 breaths per minute (median error is 0.22 breaths per minute), heart rate estimation error when two persons share a bed is 1.90 beats per minute (median error is 0.72 beats per minute), and breathing rate estimation error when two persons share a bed is 2.62 breaths per minute (median error is 1.95 breaths per minute). By varying sleeping posture and mattress type, we show that our system can work in many different scenarios.

Original languageEnglish (US)
Title of host publicationSenSys 2017 - Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems
EditorsRasit Eskicioglu
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450354592
DOIs
StatePublished - Nov 6 2017
Event15th ACM Conference on Embedded Networked Sensor Systems, SenSys 2017 - Delft, Netherlands
Duration: Nov 6 2017Nov 8 2017

Publication series

NameSenSys 2017 - Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems
Volume2017-January

Other

Other15th ACM Conference on Embedded Networked Sensor Systems, SenSys 2017
Country/TerritoryNetherlands
CityDelft
Period11/6/1711/8/17

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Computer Networks and Communications

Keywords

  • Amplitude Modulation
  • Blind Source Separation
  • Geophone
  • Time-frequency Masking
  • Unobtrusive Sensing
  • Vital Signs

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