Computer Science 690R - Computing/Human Mvmt Analysis

Computer science has played a pivotal role in developing innovative technologies to monitor patients' behaviors and behavioral phenotypes beyond the traditional laboratory or clinical environments. A profound understanding of patient behaviors has the potential to unlock a myriad of applications, including the implementation of targeted behavioral interventions to drive substantial improvements in health-related outcomes, monitoring the progress of individuals undergoing rehabilitation, and assessing the efficacy of emerging therapeutic interventions. In this course, we will delve into the application of machine learning and mobile technologies in the analysis of human movement and behavior. More specifically, the course curriculum will encompass the fundamentals of human movement analysis, mobile and wearable sensing technologies to support remote human movement monitoring, fundamentals of signal processing techniques, and state-of-the-art machine learning techniques, all with the overarching goal of improving our understanding of human behaviors and behavioral phenotypes. In addition, we will cover essential topics such as human subject study design (e.g., randomized controlled trials) and hypothesis testing (e.g., t-test, ANOVA, correlation test, etc.). These skills are crucial for their application within the realm of clinical sciences, especially when it comes to assessing the effectiveness of emerging healthcare and wellness technologies. This course contains lectures, assignments, a final project, paper presentations, and critical discussions.

Open to graduate students in COMPSCI, M&I-ENG, E&C-ENG, BMED-ENG, and KIN THERE ARE NO FORMAL PREREQUISITES FOR GRADUATE STUDENTS, BUT INFORMALLY, STUDENTS SHOULD BE FAMILIAR WITH STATISTICS AND MACHINE LEARNING. KNOWLEDGE OF HEALTH DATA OR MEDICINE IS NOT A PREREQUISITE; THIS COURSE IS DESIGNED TO INTRODUCE THE CONCEPTS OF HEALTH AND MEDICAL DATA. SEATS SAVED FOR INCOMING GRADUATE STUDENT REGISTRATION. STUDENTS NEEDING SPECIAL PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM: https://www.cics.umass.edu/overrides.