Date of Award

Spring 2020

Document Type

Thesis - SCU Access Only


Santa Clara : Santa Clara University, 2020.



First Advisor

Emre Araci


We develop a wearable, microfluidic sensor to monitor human emotions. The facial action coding system (FACS) is a system of facial expression analysis that utilizes the anatomical facial movements to create a link between facial muscle movements and facial expressions. We hypothesize, through utilization of FACS, specific human emotions can be detected. With changes in facial expressions, the skin deforms and causes changes in strain to our sensor. The strain is then converted to the displacement of ionic liquids. In order to maximize sensitivity and functionality of the device, we design multiple microfluidic sensors with differing designs and dimensions of both capillary burst valves and microfluidic channels. We test these sensors with ionic liquids of varying chemical properties to maximize sensor performance, ultimately optimizing the device to measure accurate strain values. In addition, the device constraints included being miniaturized, imperceptible, and wireless, for the convenience of the patient. The continued goal of the project is that through the measured values of the microfluidic sensor, we can provide medical professionals with supplemental, analytical information relating to human emotion.

SCU Access Only

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