Abstract: Biometric measurements captured from medical devices, such as blood pressure gauges, glucose monitors, and weighing scales, are essential to tracking a patient's health. Trends in these measurements can accurately track diabetes, cardiovascular issues, and assist medication management for patients. Currently, patients record their results and date of measurement in a physical notebook. It may be weeks before a doctor sees a patient’s records and can assess the health of the patient. With a predicted 6.8 billion smartphones in the world by 20221 , health monitoring platforms, such as Apple's HealthKit2 , can be leveraged to providing the right care at the right time. This research presents a mobile application that enables users to capture medical monitor data and send it to their doctor swiftly. A key contribution of this paper is a robust engine that can recognized digits from medical monitors with an accuracy of 98.2%.
Learning Objective 1: We explore the use of computer vision and macine learning in automating biometric monitor data input using smartphones.
Varun Shenoy (Presenter)
Cupertino High School
Oliver Aalami, Stanford University