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Conference proceeding
An Adaptively Parameterized Algorithm Estimating Respiratory Rate from a Passive Wearable RFID Smart Garment
2021 IEEE 45TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE (COMPSAC 2021), v 2021, pp 774-784
01 Jan 2021
PMID: 34568878
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Currently, wired respiratory rate sensors tether patients to a location and can potentially obscure their body from medical staff. In addition, current wired respiratory rate sensors are either inaccurate or invasive. Spurred by these deficiencies, we have developed the Bellyband, a less invasive smart garment sensor, which uses wireless, passive Radio Frequency Identification (RFID) to detect bio-signals. Though the Bellyband solves many physical problems, it creates a signal processing challenge, due to its noisy, quantized signal. Here, we present an algorithm by which to estimate respiratory rate from the Bellyband. The algorithm uses an adaptively parameterized Savitzky-Golay (SG) filter to smooth the signal. The adaptive parameterization enables the algorithm to be effective on a wide range of respiratory frequencies, even when the frequencies change sharply. Further, the algorithm is three times faster and three times more accurate than the current Bellyband respiratory rate detection algorithm and is able to run in real time. Using an off-the-shelf respiratory monitor and metronome-synchronized breathing, we gathered 25 sets of data and tested the algorithm against these trials. The algorithm's respiratory rate estimates diverged from ground truth by an average Root Mean Square Error (RMSE) of 4.1 breaths per minute (BPM) over all 25 trials. Further, preliminary results suggest that the algorithm could be made as or more accurate than widely used algorithms that detect the respiratory rate of non-ventilated patients using data from an Electrocardiogram (ECG) or Impedance Plethysmography (IP).
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Details
- Title
- An Adaptively Parameterized Algorithm Estimating Respiratory Rate from a Passive Wearable RFID Smart Garment
- Creators
- Robert Ross - Drexel UniversityWilliam M. Mongan - Drexel UniversityPatrick O'Neill - Drexel UniversityIlhaan Rasheed - Drexel UniversityAdam Fontecchio - Drexel UniversityGenevieve Dion - Drexel UniversityKapil R. Dandekar - Drexel University
- Publication Details
- 2021 IEEE 45TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE (COMPSAC 2021), v 2021, pp 774-784
- Conference
- 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), 45th (Madrid, Spain, 12 Jul 2021–16 Jul 2021)
- Series
- Proceedings International Computer Software and Applications Conference
- Publisher
- IEEE
- Number of pages
- 11
- Grant note
- CNS-1816387 / National Science Foundation Division of Computer and Network Systems R01 EB029364-01; U01EB023035 / National Institutes of Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA Commonwealth of Pennsylvania through the Commonwealth Universal Research Enhancement (CURE) program
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; Fashion Design; College of Engineering
- Web of Science ID
- WOS:000706529000099
- Scopus ID
- 2-s2.0-85107213097
- Other Identifier
- 991019167627104721
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- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Computer Science, Software Engineering