hMC2
Human Motion, Categorization and Characterization
| HMC2 | |
| Project start: | |
|---|---|
| 1 January 2012 | |
| Project end: | |
| 31 December 2015 | |
| More info (PDF): | |
| Contact: | |
| Nicholas Wickström | |
| Application Area: | |
| Health Technology | |
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Abstract
The objective is to design wearable instruments/devices that can characterize and classify human motion. The devices shall be small and “non-intrusive”, similar to a step counter. We are looking at two sensor modalities: inertial sensors (e.g. accelerometers and gyros) and electrical sensors for detecting, e.g., electromyography (EMG) signals.
Background and Motivation
Moderate physical activity can improve health substantially over an individual’s lifetime. Even physically active people can improve their health status by increasing their activity. Physical activity helps to control diseases; adopting healthy behaviors, including physical activity, decrease and control the effects of diseases like, e.g., diabetes, heart disease, depressions and dementia. There are two important aspects in the problem of increasing the level of physical activity for an individual. One is the matter of having a portable method/device for measuring an individual’s level of physical activity. The other is the ability to motivate the individual by providing suitable feedback on his/her level of activity. It is important to develop simple and wearable devices that can measure the daily physical activity of an individual. Such devices can be used both to monitor physical activity, e.g. in a treatment scenario or to gauge the levels of physical activity in a cohort, and to motivate physical activity. A simple example of such a device is the step counter. However, the step counter gives a very coarse measurement and it only measures the activity during walking or running. If a portable device (preferably wearable) would be available that could “ubiquitously” measure different sorts of physical activity and estimate the intensity level, then it would open up new frontiers promoting treatments and pro-active approaches to better health. Muscle fatigue may occur during cycling. It occurs locally and is characterized by the declining ability to perform muscle contractions and force exertions. A person experiencing muscle fatigue will generally feel pain in those muscles. High levels of muscle fatigue can cause serious injuries. Objective assessment of muscle fatigue would help athletes, trainers, and hobby cyclists to assess fitness and prevent muscle injuries. Analysis of electromyographic (EMG) signals can be applied to evaluate local muscle fatigue. Stationary equipment is usually used to record EMG signals.
