Unobtrusive monitoring of ECG-derived features during daily smartphone use
Conference Proceeding Article
Heart rate variability (HRV) is known to be one of the representative ECG-derived features that are useful for diverse pervasive healthcare applications. The advancement in daily physiological monitoring technology is enabling monitoring of HRV in people's everyday lives. In this study, we evaluate the feasibility of measuring ECG-derived features such as HRV, only using the smartphone-integrated ECG sensors system named Sinabro. We conducted the evaluation with 13 subjects in five predetermined smartphone use cases. The result shows the potential that the smartphone-based sensing system can support daily monitoring of ECG-derived features; The average errors of HRV over all participants ranged from 1.65% to 5.83% (SD: 2.54~10.87) for five use cases. Also, all of individual HRV parameters showed less than 5% of average errors for the three reliable cases.
Medicine and Health Sciences | Software Engineering
Software and Cyber-Physical Systems
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC): Proceedings: 26-30 August, Chicago
City or Country
Kwon, Sungjun; Kang, Seungwoo; LEE, Youngki; Yoo, Chungkuk; and Park, Kwangsuk.
Unobtrusive monitoring of ECG-derived features during daily smartphone use. (2014). 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC): Proceedings: 26-30 August, Chicago. 4964-4967. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/2660