Date of Award
Spring 6-3-2023
Document Type
Thesis
Degree Name
Master of Industrial Design
Department
Industrial Design
First Advisor
Leslie Fontana
Second Advisor
Michael Lye
Third Advisor
Marissa Gray
Abstract
">">Pain perception is a subjective experience that differs significantly among individuals, often leading to inconsistencies in assessment and management. A critical issue within this context is the gender bias in pain evaluation, which contributes to unequal treatment and perpetuates gender inequality within the healthcare system. This thesis presents an in-depth investigation of the problem and proposes the development of a wearable device for objective pain assessment. Physiological parameters — Electrocardiography (ECG) can be collected from cardiac sound signals auscultated by fabrics via nanometre-scale vibrations. Machine learning methods can accurately classify heart rate and acute pain intensity of participants. The device aims to provide an accurate and unbiased measure of pain intensity. The study seeks to validate the device's accuracy and explore potential gender-based differences in pain perception. The overarching goal of this research is to address the gender gap in pain evaluation, ultimately enhancing the quality of pain care for patients across various medical and research settings.
Recommended Citation
Tang, Hanqing, "Unveiling Pain: Wearables for Objective Pain Measurement" (2023). Masters Theses. 1184.
https://digitalcommons.risd.edu/masterstheses/1184
Creative Commons License
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Included in
Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons, Biomedical Engineering and Bioengineering Commons, Digital Circuits Commons, Materials Science and Engineering Commons, Nanotechnology Commons