科研之友
微信
新浪微博
Facebook
分享链接
摘要
Muscle activity and human motion are useful parameters to map the diagnosis, treatment, and rehabilitation of neurological and movement disorders. In laboratory and clinical environments, electromyography and motion capture systems enable the collection of accurate, high-resolution data on human movement and corresponding muscle activity. However, controlled surroundings limit both the length of time and the breadth of activities that can be measured. Features of movement, critical to understanding patient progress, can change during the course of a day and daily activities may not correlate to the limited motions examined in a laboratory. We introduce a system to measure motion and muscle activity simultaneously over the course of a day in an uncontrolled environment with minimal preparation time and ease of implementation that enables daily usage. Our system combines a bespoke inertial measurement unit (IMU) and mechanomyography sensor, which measures the mechanical signal of muscular activity. The IMU can collect data continuously, and transmit wirelessly, for up to 10 h. We describe the hardware design and validation, and outline the data analysis (including data processing and activity classification algorithms) for the sensing system. Furthermore, we present two pilot studies to demonstrate utility of the system, including activity identification in six able-bodied subjects with an accuracy of 98%, and monitoring motion/muscle changes in a subject with cerebral palsy and of a single leg amputee over extended periods (similar to 5 h). We believe these results provide a foundation for mapping human muscle activity and corresponding motion changes over time, providing a basis for a range of novel rehabilitation therapies.
- 出版日期2017-10
- 单位东北大学
