A prototype technology could make lifting weights a lighter task.

Sensor technology keeps track of your progress in the gym and puts you in touch with other gym-goers

Sensor gives weightlifters a boost

A prototype technology could make lifting weights a lighter task.

Working out with free weights is an excellent way to build strength and burn off fat.

But keeping track of the sets and reps can be tedious. It's easy to accidentally skip steps, miscount a sequence or forget your progress.

The new technique uses sensor-embedded gloves and a waistband designed to recognise what type of exercise a person is doing and how many repetitions have been completed.

The system is tied with an online community of exercisers and could lead to a new kind of digital personal trainer that gives real-time tips or warnings on form and posture.

It would also connect people with others to help achieve their goals.

"People can use this to share their progress with others. They can share their secret and how they do their exercise," says Keng-hao Chang, a graduate student of computer science at the University of California, Berkeley.

Workout gloves are fixed with wireless sensors called accelerometers, which track motion in three directions: side to side, up and down, and front and back.

The data collected is sent via a wireless connection to a computer, where custom software analyses the information to distinguish a bicep curl from a tricep curl.

Eventually the data could be sent to a mobile phone or PDA.

Another accelerometer on the belt also tracks motions in three axes to distinguish whether the exerciser is standing or lying on a bench.

That information is helpful because the motion of some exercises - for example a bench press, which works the chest, and the movement of an overhead dumbbell press, which works the shoulders - are quite similar.


Initial tests
In initial tests, the sensors were 85-95% accurate in recognising the exercise being performed. And out of 100 repetitions, the system miscounted by fewer than five.

Chang and his team think that the system could be further enhanced by attaching radio-frequency tags to the weights themselves.

That information could be picked up by the sensors to determine how much weight is being lifted. In this way, the exerciser need only focus on the workout instead of its progress.

"The application itself is very interesting," says Dr Jamie Ward, a researcher of human activity recognition at the UK's Lancaster University.

"I believe you could make a product out of it," he says. "[But] there are a number challenges to overcome first."


Challenges ahead
For example, the sensors need battery power.

"It would be nice if the devices could be powered just from the movements themselves," says Ward.

"Wristwatches can do that but they use a very small amount of power, and accelerometers use more power."

There is also the issue of privacy.

"If the environment is smart so that the objects are monitoring you, it obviously raises some privacy issues," says Ward, adding that it will be important to keep the information localised