Development of a Machine Learning Algorithm for Estimating Vital Parameters using a Smart Medical Watch

VitalTracer Ltd.在渥太华和蒙特利尔开展业务，开发了一款智能医疗手表VTLAB，其设计能够连续测量重要的生理参数，如血压（BP）、心率（HR）、血氧饱和度（SpO2）、体温、呼吸频率、ECG（心电图）、PPG（光电容积图）、步数和运动。然后，这组数据用于预测和管理医疗状况。VitalTracer希望通过改进当前用于分析连续生理数据的AI（人工智能）算法来增强他们当前版本的VTLAB。百年学院的可穿戴、互动和移动健康技术访问中心（WIMTACH）和VitalTracer将通过这个Engage项目合作，对新型机器学习和特征工程算法进行系统调查，并开发一种新型机器学习算法，该算法可以分析用运动伪影捕获的VTLAB数据，并估计血压等重要参数。作为该项目的成果，WIMTACH团队将提供一个信号处理和机器学习软件应用程序，该应用程序将使用VTLAB医疗手表无缝地分析、测量和预测重要的身体参数。

VitalTracer Ltd., which operates in Ottawa and Montreal, has developed a smart medical watch, VTLAB, which is designed to be capable of continuously measuring vital physiological parameters such as blood pressure (BP), heart rate (HR), blood oxygen saturation (SpO2), body temperature, respiratory rate, ECG (electrocardiogram), PPG (photoplethysmogram), steps and motion. This array of data is then used for predicting and managing medical conditions. VitalTracer would like to enhance their current version of VTLAB by improving their current AI (artificial intelligence) algorithms for analyzing continuous physiological data. Centennial College's Wearable, Interactive and Mobile Technology Access Center in Health (WIMTACH) and VitalTracer will collaborate through this Engage project, to conduct a systematic investigation into novel machine learning and feature engineering algorithms and develop a novel machine learning algorithm which analyzes VTLAB data captured with motion-artifacts and estimates vital parameters such as blood pressure. As an outcome of this project, the WIMTACH team will deliver a signal processing and machine learning software application that would seamlessly analyze, measure and predict vital body parameters using the VTLAB medical watch.