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January 23, 2013Physiological Measurement

Robust inter-beat interval estimation in cardiac vibration signals

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Why the study?

Does a novel Bayesian algorithm accurately estimate inter-beat intervals from ballistocardiogram signals in normal and insomniac subjects?

Population

n=33 subjects with over-night ballistocardiogram recordings containing approximately one million heart beats

Design

Other

Follow-up

over-night

Authors

CBChristoph BrüserFraunhofer Institute for Translational Medicine and PharmacologySWStefan WinterLMU KlinikumSLSteffen LeonhardtHeart Failure & Transplant

Discussion

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Implication

May support unobtrusive IBI monitoring in sleep studies; leaves open clinical adoption pending prospective validation.

Structured PICO

Does a novel Bayesian algorithm accurately estimate inter-beat intervals from ballistocardiogram signals in normal and insomniac subjects?

P
Population
n=33 subjects (8 normal, 25 insomniacs) with over-night ballistocardiogram (BCG) recordings containing approximately one million heart beats
I
Intervention
A new flexible algorithm combining three short-time estimators using a Bayesian approach to continuously estimate inter-beat intervals from cardiac vibration signals (BCGs) recorded by an unobtrusive bed-mounted sensor
O
Outcome
Mean beat-to-beat interval error and coveragesurrogate

A novel Bayesian algorithm can robustly estimate beat-to-beat intervals from unobtrusive bed-mounted ballistocardiogram sensors with low error.

Cite This Study

Brüser et al. (2013) studied this question.

synapsesocial.com/papers/6a8bb2fd60c8c47a9ee3df04https://doi.org/10.1088/0967-3334/34/2/123
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Also Consider

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  1. 1Development and Preliminary Validation of Heart Rate and Breathing Rate Detection Using a Passive, Ballistocardiography-Based Sleep Monitoring System2008 · 198 citations
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