Cardiovascular healthcare today depends on in-clinic measurements taken just a few times a year — sparse snapshots of a patient’s overall well-being. Continuous monitoring can give us a much more complete picture, but merely tracking signals introduces too many behavioral unknowns to support clinical decisions. Fortunately, recent advances in context recognition and behavior analysis are creating an opportunity to transform our approach to many health conditions. By combining wearable physiological sensors with advanced algorithms, our group seeks to derive unprecedented levels of insight from continuous, ambulatory health data.
To make this vision a reality, we’re leveraging our key areas of technical expertise. Novel sensors and sensor technologies are essential to monitoring cardiovascular signals effectively in ambulatory settings. Signal processing and machine learning allow us to make sense of the raw signals, from determining fundamental measurements to extracting actionable insights and long term patterns. Finally, wearable design, from the embedded system development and hardware to the final fit and finish, allows us to combine all of this into an ergonomic, wearable package.
