Adaptive Heartbeat Modeling for Beat-to-Beat Heart Rate Measurement in Ballistocardiograms.

We present a method for measuring beat-to-beat heart rate from ballistocardiograms acquired with force sensors. First, a model for the heartbeat shape is adaptively inferred from the signal using hierarchical clustering. Then, beat-to-beat intervals are detected by finding positions where the heartbeat shape best fits the signal.

Unobtrusive online monitoring of sleep at home.

We describe an online sleep monitoring service, based on unobtrusive ballistocardiography (BCG) measurement in an ordinary bed. The novelty of the system is that the sleep tracking web application is based on measurements from a fully unobtrusive sensor. The BCG signal is measured with a piezoelectric film sensor under the mattress topper, and sent to the web server for analysis.

Quantifying respiratory variation with force sensor measurements.

Measuring the variation of the respiratory rate makes it possible to analyze the structure of sleep. The variation is high when awake or in REM sleep, and decreases in deep sleep. With sleep apnea, the respiratory variation is disturbed.

A respiratory latent variable model for mechanically measured heartbeats.

The effect of respiration on heartbeats in a mechanically measured cardiac signal was noticed already in the first respiratory ballistocardiography studies in the 1920s. The effect was described as a modulation of the heartbeat amplitude, and that view has persisted. Although a reasonable approximation, amplitude modulation is not an accurate description of the respiratory effect.