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Naik GR, Breen PP, Jayarathna T, Tong BK, Eckert DJ, Gargiulo GD. Morphic Sensors for Respiratory Parameters Estimation: Validation against Overnight Polysomnography. BIOSENSORS 2023; 13:703. [PMID: 37504102 PMCID: PMC10377422 DOI: 10.3390/bios13070703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 06/19/2023] [Accepted: 06/26/2023] [Indexed: 07/29/2023]
Abstract
Effective monitoring of respiratory disturbances during sleep requires a sensor capable of accurately capturing chest movements or airflow displacement. Gold-standard monitoring of sleep and breathing through polysomnography achieves this task through dedicated chest/abdomen bands, thermistors, and nasal flow sensors, and more detailed physiology, evaluations via a nasal mask, pneumotachograph, and airway pressure sensors. However, these measurement approaches can be invasive and time-consuming to perform and analyze. This work compares the performance of a non-invasive wearable stretchable morphic sensor, which does not require direct skin contact, embedded in a t-shirt worn by 32 volunteer participants (26 males, 6 females) with sleep-disordered breathing who performed a detailed, overnight in-laboratory sleep study. Direct comparison of computed respiratory parameters from morphic sensors versus traditional polysomnography had approximately 95% (95 ± 0.7) accuracy. These findings confirm that novel wearable morphic sensors provide a viable alternative to non-invasively and simultaneously capture respiratory rate and chest and abdominal motions.
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Affiliation(s)
- Ganesh R Naik
- Adelaide Institute for Sleep Health (Flinders Health and Medical Research Institute: Sleep Health), College of Medicine and Public Health, Flinders University, Bedford Park, SA 5042, Australia
- College of Science and Engineering, Flinders University, Bedford Park, SA 5042, Australia
| | - Paul P Breen
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
| | - Titus Jayarathna
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
| | - Benjamin K Tong
- Neuroscience Research Australia, Randwick, NSW 2031, Australia
- Sleep Research Group, Charles Perkins Centre, School of Medicine, University of Sydney, Camperdown, NSW 2006, Australia
| | - Danny J Eckert
- Adelaide Institute for Sleep Health (Flinders Health and Medical Research Institute: Sleep Health), College of Medicine and Public Health, Flinders University, Bedford Park, SA 5042, Australia
- Neuroscience Research Australia, Randwick, NSW 2031, Australia
| | - Gaetano D Gargiulo
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
- School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia
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Jayarathna T, Gargiulo GD, Lui GY, Breen PP. Electrodeless Heart and Respiratory Rate Estimation during Sleep Using a Single Fabric Band and Event-Based Edge Processing. SENSORS (BASEL, SWITZERLAND) 2022; 22:6689. [PMID: 36081149 PMCID: PMC9460329 DOI: 10.3390/s22176689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 08/26/2022] [Accepted: 09/01/2022] [Indexed: 06/15/2023]
Abstract
Heart rate (HR) and respiratory rate (RR) are two vital parameters of the body medically used for diagnosing short/long-term illness. Out-of-the-body, non-skin-contact HR/RR measurement remains a challenge due to imprecise readings. "Invisible" wearables integrated into day-to-day garments have the potential to produce precise readings with a comfortable user experience. Sleep studies and patient monitoring benefit from "Invisibles" due to longer wearability without significant discomfort. This paper suggests a novel method to reduce the footprint of sleep monitoring devices. We use a single silver-coated nylon fabric band integrated into a substrate of a standard cotton/nylon garment as a resistive elastomer sensor to measure air and blood volume change across the chest. We introduce a novel event-based architecture to process data at the edge device and describe two algorithms to calculate real-time HR/RR on ARM Cortex-M3 and Cortex-M4F microcontrollers. RR estimations show a sensitivity of 99.03% and a precision of 99.03% for identifying individual respiratory peaks. The two algorithms used for HR calculation show a mean absolute error of 0.81 ± 0.97 and 0.86±0.61 beats/min compared with a gold standard ECG-based HR. The event-based algorithm converts the respiratory/pulse waveform into instantaneous events, therefore reducing the data size by 40-140 times and requiring 33% less power to process and transfer data. Furthermore, we show that events hold enough information to reconstruct the original waveform, retaining pulse and respiratory activity. We suggest fabric sensors and event-based algorithms would drastically reduce the device footprint and increase the performance for HR/RR estimations during sleep studies, providing a better user experience.
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Affiliation(s)
- Titus Jayarathna
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
| | - Gaetano D. Gargiulo
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
- School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2750, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW 2052, Australia
- Translational Health Research Institute, Westmead, NSW 2145, Australia
| | - Gough Y. Lui
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
| | - Paul P. Breen
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW 2052, Australia
- Translational Health Research Institute, Westmead, NSW 2145, Australia
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Continuous Vital Monitoring During Sleep and Light Activity Using Carbon-Black Elastomer Sensors. SENSORS 2020; 20:s20061583. [PMID: 32178307 PMCID: PMC7146453 DOI: 10.3390/s20061583] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 03/06/2020] [Accepted: 03/10/2020] [Indexed: 11/26/2022]
Abstract
The comfortable, continuous monitoring of vital parameters is still a challenge. The long-term measurement of respiration and cardiovascular signals is required to diagnose cardiovascular and respiratory diseases. Similarly, sleep quality assessment and the recovery period following acute treatments require long-term vital parameter datalogging. To address these requirements, we have developed “VitalCore”, a wearable continuous vital parameter monitoring device in the form of a T-shirt targeting the uninterrupted monitoring of respiration, pulse, and actigraphy. VitalCore uses polymer-based stretchable resistive bands as the primary sensor to capture breathing and pulse patterns from chest expansion. The carbon black-impregnated polymer is implemented in a U-shaped configuration and attached to the T-shirt with “interfacing” material along with the accompanying electronics. In this paper, VitalCore is bench tested and compared to gold standard respiration and pulse measurements to verify its functionality and further to assess the quality of data captured during sleep and during light exercise (walking). We show that these polymer-based sensors could identify respiratory peaks with a sensitivity of 99.44%, precision of 96.23%, and false-negative rate of 0.557% during sleep. We also show that this T-shirt configuration allows the wearer to sleep in all sleeping positions with a negligible difference of data quality. The device was also able to capture breathing during gait with 88.9–100% accuracy in respiratory peak detection.
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