Respiratory Patterns Recognition and Cough Detection Using Signals from Capacitive Touchpads in Smartphones Commonly Worn in Shirt Pockets

dc.contributor.advisorVyas, Rushi
dc.contributor.authorGupta, Vedant
dc.contributor.committeememberPandey, Richa
dc.contributor.committeememberGinde, Gouri
dc.date.accessioned2024-11-18T18:31:20Z
dc.date.available2024-11-18T18:31:20Z
dc.date.issued2024-11-14
dc.description.abstractThe timely identification of respiratory distress, often indicated by coughs, has become important for public health readiness and response to pandemics like COVID-19, SARS, and Influenza. Traditional methods of monitoring respiratory health, including hospitalization rates, doctor reports, and wearable sensors, have limitations in real-time reporting, extra costs, etc. With smartphones used by 66 out of every 100 persons, they are useful tools in various public health initiatives. Our project studies the use of capacitive touchpad sensors present in smartphones for monitoring respiratory patterns and distress. Specifically, this study examines how different touchpad scan patterns, orientations, and electrode spacings affect respiratory monitoring by detecting capacitive fluctuations. Our measurements with a commercial 5 by 6 element capacitive touchpad sensor array (0.8 cm pitch) worn on the chest or pocket registered fluctuations over the baseline due to cough-related chest surface movements. Furthermore, when the touchpad is placed on the chest or pocket, this method can also detect breathing rate by registering changes in capacitance over the baseline. Through this approach, we were able to measure very low capacitance values (0–100 pF), which are typically challenging to detect with conventional sensors. We also explored how varying electrode spacing impacts the fringing fields in the capacitive touchpad, as different configurations alter the depth and sensitivity of the capacitive field. This investigation allowed us to assess whether specific spacing setups could capture respiratory patterns deeper within body tissue, providing a non-invasive approach to respiratory health monitoring. This pioneering prototype demonstrates the potential for capacitive sensing to offer real-time, accessible respiratory monitoring using widely available smartphone technology.
dc.identifier.citationGupta, V. (2024). Respiratory patterns recognition and cough detection using signals from capacitive touchpads in smartphones commonly worn in shirt pockets (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.
dc.identifier.urihttps://hdl.handle.net/1880/120073
dc.language.isoen
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgary
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectCough Sensor
dc.subjectBreathing rate
dc.subjectSensor
dc.subjectCapacitive Sensor
dc.subjectTouchpad
dc.subjectSmartphone
dc.subjectDigital Health
dc.subject.classificationEngineering--Electronics and Electrical
dc.titleRespiratory Patterns Recognition and Cough Detection Using Signals from Capacitive Touchpads in Smartphones Commonly Worn in Shirt Pockets
dc.typemaster thesis
thesis.degree.disciplineEngineering – Electrical & Computer
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.thesis.accesssetbystudentI require a thesis withhold – I need to delay the release of my thesis due to a patent application, and other reasons outlined in the link above. I have/will need to submit a thesis withhold application.
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