Wireless Wearable Ultrasound Sensor on a Paper Substrate to Characterize Respiratory Behavior.

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.