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Validating Force Sensitive Resistor Strip Sensors for Cardiorespiratory Measurement during Sleep: A Preliminary
Mostafa Haghi1, Akhmadbek Asadov1, Andrei Boiko1
1Ubiquitous Computing Laboratory, Department of Computer Science, HTWG Konstanz, 78462 Konstanz, Germany.
Sensors (Basel, Switzerland)
|April 28, 2023
Summary
This study introduces a low-cost, noninvasive Out of Center Sleep Testing (OCST) system using under-mattress sensors to monitor heart rate and respiration rate during sleep, offering a comfortable alternative to polysomnography.
Area of Science:
- Biomedical Engineering
- Sleep Medicine
- Wearable Technology
Background:
- Traditional sleep studies like polysomnography are costly and intrusive.
- There is a need for convenient, noninvasive home-based sleep monitoring solutions.
- Accurate measurement of cardiorespiratory parameters is crucial for diagnosing sleep disorders.
Purpose of the Study:
- To develop and validate a low-cost, noninvasive Out of Center Sleep Testing (OCST) system for measuring cardiorespiratory parameters at home.
- To assess the accuracy and reliability of the OCST system compared to reference methods.
- To evaluate the system's performance across different sleep positions and demographics.
Main Methods:
- Utilized two low-cost force-sensitive resistor strip sensors placed under a bed mattress to capture ballistocardiogram signals.
- Employed discrete wavelet transform and Butterworth bandpass filtering for signal processing.
- Recruited 20 healthy subjects (12 males, 8 females) for system validation.
Main Results:
- Achieved a total error of 3.24 bpm for heart rate and 2.32 rates/min for respiration rate.
- Demonstrated minimal dependency on sleeping positions, with the thoracic sensor showing optimal configuration.
- Reported comparable accuracy for male and female subjects.
Conclusions:
- The developed OCST system offers a reliable and unobtrusive method for in-home cardiorespiratory monitoring.
- The system shows potential as a comfortable and cost-effective alternative to traditional sleep studies.
- Further validation with larger, diverse patient groups and frequency bandwidth analysis is recommended.
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