SUMMER RESEARCH 2023 Part 2

“Explainability in Multivariate Time Series Classification Machine Learning Models” by Emanuel Sanchez

We conducted a study that seeks to classify posture adopted by students using data
collected while they performed patient handling tasks. It seeks ultimately to
investigate the mechanics of task performance to better understand the cause of
early onset of musculoskeletal injuries (particularly low back pain) in nursing
professionals, and prescribe guidelines for good posture to help mitigate the risk of injury in nurses.

“Classifying Patient Handling Techniques to Reduce Risk of Musculoskeletal Injury in Nursing Students” by Giovanni Battaglia

We will present a study is that used OpenCap, a video software which
captures whole-body kinematics data, in tandem with multivariate time series
classifiers to accurately predict patient handling tasks and quality
of posture during these tasks. We expect that these findings will facilitate prevention of future injuries to nurses.

“Interactive Art with Algorithms” by Justin Fay and Jack Rutherford

We employed the Unity software application to build an immersive environment that
seamlessly integrates interactive art. This project serves as a proficiencies demonstration
of the remarkable competencies achievable within a concise span of time through our Computer Science curriculum at Hope.