Paper-Based Humidity Sensor for Respiratory Monitoring

Abstract

Flexible respiratory monitoring devices have become available for outside-hospital application scenarios attributable to their improved system wearability. However, the complex fabrication process of such flexible devices results in high prices, limiting their applications in real-life scenarios. This study proposes a flexible, low-cost, and easy-processing paper-based humidity sensor for sleep respiratory monitoring. A paper humidity sensing model was established and sensors under different design parameters were processed and tested, achieving high sensitivity of 5.45 kΩ/%RH and good repeatability with a matching rate of over 85.7%. Furthermore, the sensor patch with a dual-channel 3D structure was designed to distinguish between oral and nasal breathing from origin signals proved in the simulated breathing signal monitoring test. The sensor patch was applied in the sleep respiratory monitoring of a healthy volunteer and an obstruct sleep apnea patient, demonstrating its ability to distinguish between different respiratory patterns as well as various breathing modes.

Keywords: nasal breathing; oral breathing; paper humidity sensing model; paper-based humidity sensor; respiratory monitoring; sleep-related respiratory disorders.

Figure 1

(a) Humidity sensing principle of the PHS. (b) Processing of designed 3D structure sensor patch. (c) Photo of the flexible PHS.

Figure 2

System flow diagram.

Figure 3

(a) Relationship between PHS resistance and relative humidity in paper humidity sensing model. (b) Resistance-RH% characteristic curve of PHSs under different design parameters. (c) Hysteretic curve of 80 gsm PHS. (d) Response time of 80 gsm PHS. (e) Repeatability of 80 gsm PHS.

Figure 4

(a) Photo of a volunteer wearing a PHS patch. (b,c) Simulated breathing experiments for different breathing modes and various respiratory patterns (*: normal breathing; **: deep breathing; ***: shallow breathing). (d) Schematic diagram of oral and nasal airflows in four respiratory patterns.

Figure 5

Sleep respiratory monitoring of healthy volunteer: (a) Breathing signals throughout the test (I: nasal breathing; II: oral breathing; III: oral–nasal co-breathing). (b–e) Detailed signals for different sleeping stages during the test, including oral breathing (stage ①), nasal breathing (stage ② and stage ④), and oral–nasal co-breathing (stage ③).

Figure 6

Sleep respiratory monitoring of apnea patient: (a) Breathing signals throughout the test (I: nasal breathing; III: oral–nasal co-breathing). Detailed signals for different sleeping stages during the test, including (b,c) oral–nasal co-breathing (stage ⑤ and stage ⑥) and (d) breathing event.