therapyTrak

Our project was inspired by our personal experiences with physical therapy and the lack of motivation patients possess throughout their treatment. According to Heidi Jannenga, over 20% of physical therapy patients drop out of their treatment within the first 3 visits, and 70% fail to complete their full course of care. We aim to make physical therapy more engaging and approachable to those in need. Our project, TherapyTrak, evaluates a patient’s physical therapy exercises and stretches throughout the week. Our technology counts their reps, how good their form is, and their heart rate throughout their therapeutic workout and sends it to their therapist to monitor and track. In addition, we have statistics and records to help therapists visualize and absorb their patients’ progress over their weeks of treatment. Patients can record and browse through our IOS App while the therapists are able to manage patients and plans through our Web App. We built our IOS App fully integrated with our Web App using Swift, Swift UI, Machine Learning (Vision Human Body Pose Detection), Firebase, HealthKit, HTML/SCSS/CSS, and JavaScript. Some challenges we ran into include horizontal scalability and database structuring. We also found difficulty in tracking nearly 20 joints on the body to create an accurate machine learning model. We are proud of our execution of making an IOS App and Web App that are both connected to a Firebase Database, from which we can transfer and store data. We are also pleased with our ability to make 2 different platforms in a short time span, both of which have complex functionality and engaging User Interfaces. Over the span of this past weekend, we learned to make a full stack application that is both maintainable and scalable. Coming up next for TherapyTrak is to scale the app for more stretches in order to help treat a variety of patients. We also want to expand our project to more mobile platforms such as Android, in order to make it more accessible to patients across the world.