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Published on Apr 25, 2017
Demo application for research titled "Utilizing Smartphone-Based Machine Learning in Medical Monitor Data Collection: Seven Segment Digit Recognition."
Abstract Biometric measurements captured from medical devices, such as blood pressure gauges, glucose monitors, and weighing scales, are essential tools patients can use to track their own health. Trends in these measurements can accurately track diabetes, cardiovascular issues, and assist medication management for patients. Currently, the majority of 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 2022, health monitoring platforms, such as Apple's HealthKit, can be leveraged to provide the right care at the right time. This research presents a mobile application that enables users to capture medical monitor data using computer vision and automatically record it to Apple's HealthKit. A key contribution of this paper is a robust engine that can recognize seven segment digits from medical monitors with an accuracy of 98.2%.