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Wireless Device Helps Athletes Get the Most out of Exercise

Feb. 16, 2011 — New research at the University of Essex could help athletes train to their maximum potential without putting undue pressure on their muscles.


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A special wireless device -- called the iSense -- has been devised which is capable of predicting and detecting the status of muscles during training and can be adapted to any sport.

"It is all about being able to train safely and smartly," explained PhD student Mohamed Al-Mulla who has devised the iSense.

Until now, athletes have to rely on their own perception of muscle fatigue when training. However, the iSense helps optimise performance by building the bridge between what the brain is telling the athlete and what the muscles are actually doing.

The iSense device is attached by sensors and takes signals from the muscles based on the tiny electrical signals they produce when contracting. Mr Al-Mulla is now hoping to attract investment to make the isense device a commercial product.

Whilst muscle fatigue can be beneficial to body-builders wanting to push their bodies to the extreme to promote muscle growth, it can cause serious injury when the level of fatigue is high. When muscle fatigue is not detected soon enough, it can often lead to pain and injuries. The system will guide the user during training to act as a warning device, to avoid unnecessary strain on the muscle and avoiding injury.

The device can not only benefit sports enthusiasts but the elderly and disabled who can often suffer muscle fatigue by sitting in the same position for too long. It can also be used for preventing muscle fatigue in work-related settings.

The research, published in the journal Sensors, is already moving towards an improved device which is smaller, more portable and can be connected to an iPhone.

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The above story is reprinted from materials provided by University of Essex.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.


Journal Reference:

  1. Mohamed R. Al-Mulla, Francisco Sepulveda, Martin Colley. An Autonomous Wearable System for Predicting and Detecting Localised Muscle Fatigue. Sensors, 2011; 11 (2): 1542 DOI: 10.3390/s110201542
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