Available at: https://digitalcommons.calpoly.edu/theses/1019
Date of Award
MS in Electrical Engineering
Throughout the years, sensors have been an integral part of automation, alert, and medical systems. Many of these systems measure physiological characteristics of the human body to alert themselves of their current conditions. Drowsy driver systems, for instance, measure the eyes and facial movements with a camera to determine if the driver is falling asleep at the wheel. Electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG) employ electrodes on the human body to measure electrical activity of a patient’s REM sleep cycle patterns. Pulse oximeters use optical light through a process called photoplethysmography (PPG) to measure heart rate.
As diverse as these all may be, this thesis attempts to prove infrared technology as a single, resourceful, and inexpensive method for implementing all the aforementioned systems. This thesis specifically explores the development of Silicon Laboratories’ Si1143 Infrared Proximity/Ambient Light Sensor into a pair of eye tracking/heart rate detecting glasses. Through the use of a LabVIEW interface, a novel algorithmic solution is also presented to classify the eye movements and detect the heart rate signal.
The results from the tests and calculations show that the Si1143 sensor can detect eye movements using only a 52μW of power. The novel algorithm can also classify the blinking motions robustly, but the algorithm starts to fail when additional motions are added. The results also show that the Si1143 sensor can detect heart rate using Reflection PPG method, but imprecise placement of the sensor on the glasses will render the measurement useless. This thesis concludes that Si1143 sensor is sensitive enough to track the human eye and measure the heart rate, but further work is required to make it robust.