TY - JOUR
T1 - One-step fabrication of paper-based inkjet-printed graphene for breath monitor sensors
AU - Lim, Wei Yin
AU - Goh, Choon Hian
AU - Yap, Keenan Zhihong
AU - Ramakrishnan, Narayanan
N1 - Funding Information:
This research was funded by Monash University Malaysia Postdoctoral Fellowship, STG-000047.
Publisher Copyright:
© 2023 by the authors.
PY - 2023/2
Y1 - 2023/2
N2 - Irregularities in breathing patterns can be detected using breath monitor sensors, and this help clinicians to predict health disorders ranging from sleep disorders to heart failures. Variations in humidity during the inhalation and exhalation of breath have been utilized as a marker to detect breath patterns, and graphene-based devices are the favored sensing media for relative humidity (RH). In general, most graphene-based RH sensors have been used to explore resistance change as a measurement parameter to calibrate against the RH value, and they are prone to noise interference. Here, we fabricated RH sensors using graphene ink as a sensing medium and printed them in the shape of interdigital electrodes on glossy paper using an office inkjet printer. Further, we investigated the capacitance change in the sensor for the RH changes in the range of 10–70%. It exhibited excellent sensitivity with 0.03 pF/% RH, good stability, and high intraday and interday repeatability, with relative standard deviations of 1.2% and 2.2%, respectively. Finally, the sensor was embedded into a face mask and interfaced with a microcontroller, and capacitance change was measured under three different breathing situations: normal breathing, deep breathing, and coughing. The result show that the dominant frequency for normal breath is 0.22 Hz, for deep breath, it is 0.11 Hz, and there was no significant dominant cough frequency due to persistent coughing and inconsistent patterns. Moreover, the sensor exhibited a short response and recovery time (<5 s) during inhalation and exhalation. Thus, the proposed paper-based RH sensor is promising wearable and disposable healthcare technology for clinical and home care health applications.
AB - Irregularities in breathing patterns can be detected using breath monitor sensors, and this help clinicians to predict health disorders ranging from sleep disorders to heart failures. Variations in humidity during the inhalation and exhalation of breath have been utilized as a marker to detect breath patterns, and graphene-based devices are the favored sensing media for relative humidity (RH). In general, most graphene-based RH sensors have been used to explore resistance change as a measurement parameter to calibrate against the RH value, and they are prone to noise interference. Here, we fabricated RH sensors using graphene ink as a sensing medium and printed them in the shape of interdigital electrodes on glossy paper using an office inkjet printer. Further, we investigated the capacitance change in the sensor for the RH changes in the range of 10–70%. It exhibited excellent sensitivity with 0.03 pF/% RH, good stability, and high intraday and interday repeatability, with relative standard deviations of 1.2% and 2.2%, respectively. Finally, the sensor was embedded into a face mask and interfaced with a microcontroller, and capacitance change was measured under three different breathing situations: normal breathing, deep breathing, and coughing. The result show that the dominant frequency for normal breath is 0.22 Hz, for deep breath, it is 0.11 Hz, and there was no significant dominant cough frequency due to persistent coughing and inconsistent patterns. Moreover, the sensor exhibited a short response and recovery time (<5 s) during inhalation and exhalation. Thus, the proposed paper-based RH sensor is promising wearable and disposable healthcare technology for clinical and home care health applications.
KW - breath monitoring
KW - capacitive sensors
KW - graphene ink
KW - inkjet printing
KW - paper sensor
KW - relative humidity sensor
UR - http://www.scopus.com/inward/record.url?scp=85148965655&partnerID=8YFLogxK
U2 - 10.3390/bios13020209
DO - 10.3390/bios13020209
M3 - Article
C2 - 36831975
AN - SCOPUS:85148965655
SN - 2079-6374
VL - 13
JO - Biosensors
JF - Biosensors
IS - 2
M1 - 209
ER -