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Related Experiment Videos

Selective vibration sensing: a new concept for activity-sensing rate-responsive pacing.

C P Lau1, J R Stott, W D Toff

  • 1Department of Cardiological Sciences, St. George's Hospital Medical School, London, England.

Pacing and Clinical Electrophysiology : PACE
|September 1, 1988
PubMed
Summary

Activity-sensing pacemakers use body vibration for rate response, but lack specificity. Accelerometer data, particularly with filtering, shows better correlation with exertion, suggesting improved algorithms for activity pacing.

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Area of Science:

  • Biomedical Engineering
  • Cardiovascular Technology

Background:

  • Activity-sensing pacemakers, like Activitrax, use body vibration to adjust heart rate during exercise.
  • Current models have limitations in specificity and correlation with exertion levels, and are prone to interference from extraneous vibrations.

Purpose of the Study:

  • To evaluate the correlation between pacemaker rate response and actual sinus rate during various exercises.
  • To assess the effectiveness of accelerometer-measured vibration in predicting exertion levels.
  • To explore improvements for activity pacing algorithms.

Main Methods:

  • 20 healthy subjects were fitted with an external Activitrax pacemaker.
  • Subjects underwent various exercises while pacemaker rate, sinus rate, and multi-axis vibration were recorded.

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  • Correlation analyses were performed between pacemaker rate, sinus rate, and acceleration data (including filtered data).

    • Main Results:

    • A fair correlation (r=0.51) was found between the pacemaker rate and sinus rate.
    • A stronger correlation (r=0.8) was observed between sinus rate and the total root mean square acceleration.
    • Low-frequency accelerations (0.1-4 Hz) during physical activity were identified, suggesting the utility of low-pass filtering.

    Conclusions:

    • The Activitrax pacemaker's vibration-based rate response has limitations in accuracy.
    • Accelerometer-based measurements, especially when filtered for low frequencies, offer a more reliable indicator of physical exertion.
    • Selective sensing of acceleration could enhance future activity pacing algorithms.