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Updated: Jan 14, 2026

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice
Published on: August 2, 2017
Association between heart failure events and nighttime respiratory stability measured using a piezoelectric
Tetsuroh Tamaru1,2, Makoto Ogawa3, Yasuyuki Kurasawa4
1Department of Rehabilitation, Nagano Chuo Hospital, Nagano, Nagano Prefecture, Japan.
Background:
Noninvasive remote monitoring can improve the home management of heart failure. However, the low specificity of current parameters limits their effectiveness. This study examined the association between respiratory rate stability (RRS), detected using a piezoelectric noncontact vibration sensor, and heart failure-related adverse events. We explored the relationship between the RRS measured during hospitalization and the occurrence of adverse events, including mortality and rehospitalization, within one year after discharge.
Methods:
This prospective observational study was conducted between 2022 and 2024. Patients with heart failure were monitored using a piezoelectric sensor placed under their mattress; the RRS was quantified through frequency analysis. The primary endpoints were postdischarge events, including all-cause mortality, heart failure-related rehospitalization, all-cause rehospitalization, and composite events. Patients were stratified into the low (RRS < median) and normal (RRS ≥ median) RRS groups. Survival analysis was performed.
Results:
A total of 57 patients were included in this analysis. The median composite event time was 203 and 477 days in the low and normal RRS groups, respectively. The log-rank test showed significant differences between the groups. The hazard ratio for event occurrence in the low RRS group compared with that in the normal RRS group was 3.25. Significant differences were observed for all individual postdischarge events, including mortality and rehospitalization.
Conclusions:
Evaluating the RRS using a piezoelectric sensor identified patients at a high risk of mortality and rehospitalization within a year of discharge. These findings support the use of this noninvasive method for risk stratification and remote heart failure management.
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