CAPSTONE DESIGN PARTICIPANTS
Avery Ryoo, Ben Huggard, Jathushan Kaetheeswaran, Leon Wang, Srikar Saradhi
CorticoChair
16
Recent advances in brain-computer interface (BCI) technology have allowed for medical breakthroughs in autonomous mobility, particularly for individuals who have lost motor function but are cognitively-able. However, the extended operation of these devices can induce cognitive fatigue, which negatively affects the classification performance of the signals captured by the BCI. To address this, CorticoChair uses the Steady-State Visual Evoked Potential (SSVEP) paradigm and machine learning to mitigate these detrimental effects, allowing for a BCI wheelchair control system that maintains consistent performance through prolonged usage.
Abby Tien
Nick Butt
Matthew Lee
Paul (Teng Hung) Chang
Sore No More
17
Sore No More is a pressure alert system intended to help patients with trans-tibial amputations reduce their risk of developing pressure ulcers. The system uses pressure data from a soft-robotic balloon sensor and calculates risk using pressure threshold and activity recognition algorithms. Our developed mobile application then alerts patients of high-pressure ulcer risk. This system is designed to be integrated into prosthetic development workflow to maximize user adoption. The user will also be able to visualize pressure data and send it to their healthcare teams.
Leeam Ng Tang Fui, John Quinto, Kendra Wang, Yue chen (Cindy) Yu
Lumbly
18
Lumbly is a mobile app that monitors physiotherapy patients with lower back pain as they perform their prescribed home exercises. The app uses pose estimation on videos of the patient performing their prescribed exercises to provide feedback on exercise form, promoting adherence and improving the rehabilitation process. Common mistakes in exercise form are identified and reported to the patient to reduce the risk of injury, increase confidence in their exercise form, and inform their physiotherapy treatment.