E17 : Sarco Analyst
| Students | Eshaan Akude
Rayan Al Tabarani |
| School | HDSB - W. H. Morden Public School - Oakville |
| Level | Junior 7/8 - Grade 8 |
| Group | Group 9 - Health Sciences II |
| Abstract | This project aimed to develop and evaluate a low-cost wearable IMU-based system that applies unsupervised machine learning to quantify neuromuscular inefficiency from functional movement data. By integrating gait, balance, fatigue, reaction, sit-to-stand, and asymmetry metrics into a composite index, the study investigates whether subtle pre-clinical motor changes can be objectively detected earlier than traditional strength- or questionnaire-based assessments. |