Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise

Abstract

Given the importance of respiratory frequency (fR) as a valid marker of physical effort, there is a growing interest in developing wearable devices measuring fR in applied exercise settings. Biosensors measuring chest wall movements are attracting attention as they can be integrated into textiles, but their susceptibility to motion artefacts may limit their use in some sporting activities. Hence, there is a need to exploit sensors with signals minimally affected by motion artefacts. We present the design and testing of a smart facemask embedding a temperature biosensor for fR monitoring during cycling exercise. After laboratory bench tests, the proposed solution was tested on cyclists during a ramp incremental frequency test (RIFT) and high-intensity interval training (HIIT), both indoors and outdoors. A reference flowmeter was used to validate the fR extracted from the temperature respiratory signal. The smart facemask showed good performance, both at a breath-by-breath level (MAPE = 2.56% and 1.64% during RIFT and HIIT, respectively) and on 30 s average fR values (MAPE = 0.37% and 0.23% during RIFT and HIIT, respectively). Both accuracy and precision (MOD ± LOAs) were generally superior to those of other devices validated during exercise. These findings have important implications for exercise testing and management in different populations.

Estimation of ventilatory thresholds during exercise using respiratory wearable sensors

“…A different approach is the use of face masks equipped with thermistors. 27 This mask, which fully covers the mouth and nose, funnels the airflow into a thermistor located at the front open end of the mask. A validation study in 10 male cyclists results in breath-by-breath RR overall bias and precision of -0.05 bpm and 3.37 bpm, respectively.…”

Insights into Materials, Physics, and Applications in Flexible and Wearable Acoustic Sensing Technology

“…Commercial microphones have been used to capture breath sounds, which, yet, suffer bulky form and poor wearability. [ 209 ] An interesting wearable alternative was a folded double‐layer piezoelectret sensor with an excellent dynamic sensitivity of 591 pC kPa −1 , and a wide frequency bandwidth of 0–600 Hz. [ 205 ] The signal‐to‐noise ratio (SNR) of this sensor was comparable to that of a medical recorder BIOPAC.…”

A Wearable Multimodal Wireless Sensing System for Respiratory Monitoring and Analysis

“…Auscultation, or the listening to and classification of a body’s internal noises, has traditionally required the use of a stethoscope by a qualified expert. The use of electret microphones and piezoelectric sensors for auscultation as well as various sensing approaches for categorization have, however, been the subject of recent research [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ]. Measures of lung health can be obtained from respiratory activities.…”