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Chen A, Rhoades RD, Halton AJ, Booth JC, Shi X, Bu X, Wu N, Chae J. Wireless Wearable Ultrasound Sensor to Characterize Respiratory Behavior. Methods Mol Biol 2022; 2393:671-682. [PMID: 34837206 DOI: 10.1007/978-1-0716-1803-5_36] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
A wireless wearable sensor on a paper substrate was used to continuously monitor respiratory behavior that can extract and deliver clinically relevant respiratory parameters to a smartphone. Intended to be placed horizontally at the midpoint of the costal margin and the xiphoid process as determined through anatomical analysis and experimental test, the wearable sensor is compact at only 40 × 35 × 6 mm3 in size and 6.5 g weight including a 2.7 g lithium battery. The wearable sensor, consisting of an ultrasound emitter, an ultrasound receiver, wireless transmission system, and associated data acquisition, measures the linear change in circumference at the attachment location by recording and analyzing the changes in ultrasound pressure as the distance between the emitter and the receiver changes. Changes in ultrasound pressure corresponding to linear strain are converted to temporal lung volume data and are wirelessly transmitted to an associated custom-designed smartphone app. Processing the received data, the mobile app is able to display the temporal volume trace and the flow rate vs. volume loop graphs, which are standard plots used to analyze respiration. From the plots, the app is able to extract and display clinically relevant respiration parameters, including forced expiratory volume delivered in the first second of expiration (FEV1) and forced vital capacity (FVC). The sensor was evaluated with eight volunteers, showing a mean difference of the FEV1/FVC ratio as bounded by 0.00-4.25% when compared to the industry-standard spirometer results. By enabling continuous tracking of respiratory behavioral parameters, the wireless wearable sensor helps monitor the progression of chronic respiratory illnesses, including providing warnings to asthma patients and caregivers to pursue necessary medical assistance.
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Affiliation(s)
- Ang Chen
- School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA.
| | - Rachel Diane Rhoades
- School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA
| | - Andrew Joshua Halton
- School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA
| | - Jayden Charles Booth
- School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA
| | - Xinhao Shi
- College of Electrical and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Xiangli Bu
- College of Electrical and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Ning Wu
- College of Electrical and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Junseok Chae
- School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA
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Anderson WC, Stukus DR. Pediatric Asthma Masqueraders. THE JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY-IN PRACTICE 2019; 6:1083-1084.e9. [PMID: 29747972 DOI: 10.1016/j.jaip.2017.09.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 09/06/2017] [Accepted: 09/18/2017] [Indexed: 10/17/2022]
Affiliation(s)
- William C Anderson
- Department of Pediatrics, Section of Allergy and Immunology, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, Colo
| | - David R Stukus
- Division of Allergy and Immunology, Department of Pediatrics, Nationwide Children's Hospital and The Ohio State University College of Medicine, Columbus, Ohio.
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Chen A, Halton AJ, Rhoades RD, Booth JC, Shi X, Bu X, Wu N, Chae J. Wireless Wearable Ultrasound Sensor on a Paper Substrate to Characterize Respiratory Behavior. ACS Sens 2019; 4:944-952. [PMID: 30855133 DOI: 10.1021/acssensors.9b00043] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Respiratory behavior contains crucial parameters to feature lung functionality, including respiratory rate, profile, and volume. The current well-adopted method to characterize respiratory behavior is spirometry using a spirometer, which is bulky, heavy, expensive, requires a trained provider to operate, and is incapable of continuous monitoring of respiratory behavior, which is often critical to assess chronic respiratory diseases. This work presents a wireless wearable sensor on a paper substrate that is capable of continuous monitoring of respiratory behavior and delivering the clinically relevant respiratory information to a smartphone. The wireless wearable sensor was attached on the midway of the xiphoid process and the costal margin, corresponding to the abdomen-apposed rib cage, based on the anatomical and experimental analysis. The sensor, with a footprint of 40 × 35 × 6 mm3 and weighing 6.5 g, including a 2.7 g battery, consists of three subsystems, (i) ultrasound emitter, (ii) ultrasound receiver, and (iii) data acquisition and wireless transmitter. The sensor converts the linear strain at the wearing site to the lung volume change by measuring the change in ultrasound pressure as a function of the distance between the emitter and the receiver. The temporal lung volume change data, directly converted from the ultrasound pressure, is wirelessly transmitted to a smartphone where a custom-designed app computes to show volume-time and flow rate-volume loop graphs, standard respiratory analysis plots. The app analyzes the plots to show the clinically relevant respiratory behavioral parameters, such as forced vital capacity (FVC) and forced expiratory volume delivered in the first second (FEV1). Potential user-induced error on sensor placement and temperature sensitivity were studied to demonstrate the sensor maintains its performance within a reasonable range of those variables. Eight volunteers were recruited to evaluate the sensor, which showed the mean deviation of the FEV1/FVC ratio in the range of 0.00-4.25% when benchmarked by the spirometer. The continuous measurement of respiratory behavioral parameters helps track the progression of the respiratory diseases, including asthma progression to provide alerts to relevant caregivers to seek needed timely treatment.
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Affiliation(s)
- Ang Chen
- School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona 85281, United States
| | - Andrew Joshua Halton
- School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona 85281, United States
| | - Rachel Diane Rhoades
- School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona 85281, United States
| | - Jayden Charles Booth
- School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona 85281, United States
| | - Xinhao Shi
- College of Electrical and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
| | - Xiangli Bu
- College of Electrical and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
| | - Ning Wu
- College of Electrical and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
| | - Junseok Chae
- School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona 85281, United States
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