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.

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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

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article

Characterization of Wearable Respiratory Sensors for Breathing Parameter Measurements

Hossein Rouhani, Mozhgan Sabz, Joanna E. MacLean, Andrew R. Martin
5 citations
IEEE Sensors Journal
Air Quality Monitoring and Forecasting
1.03
article

Characterization of Wearable Respiratory Sensors for Breathing Parameter Measurements

Hossein Rouhani, Mozhgan Sabz, Joanna E. MacLean, Andrew R. Martin
article en
5 citations

Abstract

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.

IEEE Sensors JournalVol. 24(20)
University of Alberta (CA)
RES’EAU-WaterNET
Zero hunger
Openalex Percentile: Top 27%
Air Quality Monitoring and Forecasting
1.03
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