Mobile Health Informatics
Vision: Smartphones and wearables, constituting an array of sensors are becoming a part of everyday life. The seamless embedding of these devices in daily lives helps track and monitor an array of activities and behaviors. Such tracking and monitoring is central to applications that are intended for health monitoring. We utilize the sensing capabilities of these devices for detecting activities that can be used for understanding the health outcomes of diverse populations, which include but are not limited to children on the autism spectrum, college students, among others. Eventually the goal is to work towards building systems that scale for real-world environments and deployments and can be used as a part of everyday.
Stakeholders: This work is mostly transdisciplinary in nature, which involves collaborators from various domains experts like clinical,psychology and computer science experts. The aim of such projects is to identify an intended use-case that can be solved using wearable technology for an identified population. Data collection is then conducted in conjunction with professional care providers. At CBA, we utilize signal processing and machine learning as tools to solve real-world problems that can directly be beneficial to targeted populations.
At CBA, we develop tools grounded in machine learning that can be used to solve real-world problems, which the eventual focus on deployment of such systems. These automated assessment systems are verified to be performing as well as gold standard clinical practices and in turn hopefully assist in clinical decision making.