Wristband monitors your rock-climbing prowess

Are you an expert climber or a trembling novice? A sensor-equipped wristband will find out how well climbers negotiate rock faces by analysing the way they move.

Cassim Ladha and colleagues at the University of Newcastle have developed ClimbAx, a plastic wristband which contains 3D motion, orientation and altitude sensors to collect key data during climbs. Afterwards, climbers download the data via a USB port. A machine learning algorithm then identifies their individual moves and makes an assessment of their skill level.

The system automatically replicates some of the ways professional coaching, which is too expensive for most people, assesses the skills of elite climbers. Two factors that coaches look for are the climbers’ overall control – their ability to make smooth transitions between holds – and their stability, which is a measure of their ability to maintain a hold and remain composed while doing so.

“This is where poorer climbers can tend to struggle. Improving control or stability could drastically improve a climbers’ chances of survival,” Ladha told delegates at Ubicomp, a wearable computing conference in Zurich, Switzerland, last week.

What the software seeks in particular are nervy “microvibrations” in holds and moves that suggest a lack of composure and stability, says Ladha. In tests on six volunteer climbers who each took the device on a roped climb, the system scored the climbers’ skills at levels close to what they had achieved in competition climbing.

Encouraged by these results, the team is now working out the best way for ClimbAx to present the data in a friendly fashion to novice users &ndash and how to advise them to improve. “We want it to be able to help people make less silly decisions by recommending exercises they can do,” says Ladha.

If they perfect the gadget and its software, it could aid video analysis of climbs, says Iwona Kulczynska-Evans, a coach at the Castle Climbing Centre in north London. “This definitely sounds interesting. If it works, it might complement video analysis by helping people read their climbing sequences better.”