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Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
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Published on: April 13, 2016

Mapping the human body for vibrations using an accelerometer.

David Barbosa Rendón1, Juan L Rojas Ojeda, Luis F Crespo Foix

  • 1Grupo de Investigación en Automática, Procesamiento de Señales e Ingeniería de Sistemas" (GAPSIS), University of Cádiz, Spain. david.barbosa@uca.es

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 16, 2007
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Summary
This summary is machine-generated.

This study uses an accelerometer to detect sleep apnea by analyzing neck and thorax vibrations from heartbeats, breathing, and snoring. Finding the optimal sensor location aids in accurate sleep apnea diagnosis.

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Area of Science:

  • Biomedical Engineering
  • Medical Diagnostics
  • Signal Processing

Background:

  • Sleep apnea diagnosis often relies on polysomnography, which is resource-intensive.
  • Vibration signals from physiological activities like breathing and snoring may indicate sleep apnea.

Purpose of the Study:

  • To investigate the use of accelerometers for detecting sleep apnea.
  • To identify optimal accelerometer placement on the neck and thorax for sleep apnea signal detection.

Main Methods:

  • An accelerometer was used to measure vibrations on the neck and thorax.
  • Signal analysis in different frequency bands was performed.
  • Matlab was used to map and fit vibration data from 15 sensor locations.

Main Results:

  • Accelerometer signals captured heartbeats, breathing movements, and snoring.
  • Mean power levels in specific frequency bands varied with accelerometer location.
  • Surface mapping identified key areas for signal detection.

Conclusions:

  • Accelerometer-based vibration analysis shows potential for sleep apnea diagnosis.
  • Optimal accelerometer placement is crucial for effective sleep apnea detection.
  • This method offers a potential non-invasive approach to sleep apnea diagnosis.