Inspiration

Intelligent Leggings Measure Muscle Fatigue in Runners

Posted February 29th 2016

musce-fatigue

Wearable devices are changing the way people think about their lives and lifestyles. Smart watches are changing how we interact with each other, activity trackers are changing how we exercise, and wearable cameras are changing the nature of memory. So what can we expect from the next generation of wearable electronic devices?

Muscle fatigue has always been difficult to measure for a number of reasons. For a start, the most sensitive method involves inserting a fine wire into the muscle to measure the electrical stimulation of the nerves and determine the force the muscle can exert. As the muscle tires, this force drops, as does the electrical signal.

Now researchers at King’s College London have developed a significantly cheaper and more flexible alternative. Their idea is to embroider an ordinary pair runners leggings with electrodes and circuitry that connect to a portable Arduino microprocessor. This then collects and analyses the electrical stimulation data. The team has put the leggings through their paces by asking two runners to wear them while jogging around five-kilometer routes across three different surfaces—an asphalt track, an athletics track, and a sand track. The leggings recorded the muscle activity throughout.

The results make for interesting reading. The data clearly shows how the runner’s leg muscles begin to work harder, tire quickly after a minute or two and then get their second wind before tiring again. However, this tiring occurs quickly on sand, less quickly on asphalt, and least quickly on an athletics track.

Every runner hopes to compete without injury, but muscle fatigues makes this much more likely. So a way to measure and reveal fatigue in real time could have a major impact on training methods and running techniques. What’s more, a better understanding of how muscles exert force could help in the design of better biomechanical prosthesis and in understanding power demands for bipedal robots.

via MIT Technology Review