There currently exist a variety of methods for evaluating movement in patients suffering from neuromuscular diseases (NMD). These tests are primarily performed in the clinical setting and evaluated by highly trained individuals, rather than evaluating patient in their natural environments (i.e., home or school). Currently available automated motion capture modalities offer a highly accurate means of assessing general motion, but are also limited to a highly controlled setting. Recent advances in MEMS technology have introduced the possibility of robust motion capture in uncontrolled environments, while minimizing user interference with self-initiated motion, especially in weaker subjects. The goal of this study is to design and evaluate a MEMS-sensor-based system for motion capture in the NMD patient population. The highly interdisciplinary effort has led to significant progress toward the implementation of a new device, which is accurate, clinically relevant, and highly affordable.
