Characterization of Wearable Respiratory Sensors for Breathing Parameter Measurements
Controlling and treating respiratory diseases requires monitoring of the respiratory system. Conventional monitoring systems lack portability, which makes continuous monitoring difficult. The accuracy and reliability of portable monitoring technologies, such as wearable sensors, have rarely been characterized. This study characterized measurements of a commercial respiratory sensor in measuring tidal volume, inhalation time, and respiratory rate (RR) based on the measurement of abdominal/thoracic movements. The respiratory sensor was evaluated when placed at the thoracic spine (at the T6 and T12 vertebrae) and the abdomen (at the L3 vertebra) to find a suitable sensor location. Each test also included three breathing patterns (shallow normal, and deep) to calibrate the respiratory sensor against a flow sensor. The results showed that the respiratory sensor placement on either thorax location offered more accurate tidal volume estimation. Additionally, implementing an individualized calibration formula outperformed using a universal formula for all participants. The study involved two visits for each participant to assess how accurately the calibration formulation for estimating tidal volume, determined during the first visit, was performed during the second visit. The maximum mean relative error of tidal volume increased from 19% at the first visit to 35% at the second visit. The mean relative error of respiration rate and inhalation time remained below 13% and 26%, respectively, across all breathing patterns studied. This highlights the necessity of recalibration before each measurement to obtain more accurate tidal volume estimations. These observations may explain the extent of reliability of the wearable respiratory sensor for at-home daily monitoring.
Authors
- Hossein Rouhani
- Mozhgan Sabz
- Joanna E. MacLean (ORCID: https://orcid.org/0000-0001-7994-9910)
- Andrew R. Martin (ORCID: https://orcid.org/0000-0002-5501-5811)
Institutions
- University of Alberta (CA)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2024-09-02
- DOI
- https://doi.org/10.1109/jsen.2024.3448539
- Citations
- 5
- Primary Topic
- Air Quality Monitoring and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 1.03
Funders
- RES’EAU-WaterNET