Robots Will Quickly Recognize and Respond to Human Gestures, With New AlgorithmsNew intelligent algorithms could help robots to quickly recognize and respond to human gestures. Researchers at A*STAR Institute for Infocomm Research in Singapore have created a computer program which recognizes human gestures quickly and accurately, and requires very little training.

New intelligent algorithms could help robots to quickly recognize and respond to human gestures. Researchers at A*STAR Institute for Infocomm Research in Singapore have created a computer program which recognizes human gestures quickly and accurately, and requires very little training.

New intelligent algorithms could help robots to quickly recognize and respond to human gestures. 

 

 

 

 

Many works of science fiction have imagined robots that could interact directly with people to provide entertainment, services or even health care. Robotics is now at a stage where some of these ideas can be realized, but it remains difficult to make robots easy to operate.
One option is to train robots to recognize and respond to human gestures. In practice, however, this is difficult because a simple gesture such as waving a hand may appear very different between different people. Designers must develop intelligent computer algorithms that can be 'trained' to identify general patterns of motion and relate them correctly to individual commands.
Now, Rui Yan and co-workers at the A*STAR Institute for Infocomm Research in Singapore have adapted a cognitive memory model called a localist attractor network (LAN) to develop a new system that recognize gestures quickly and accurately, and requires very little training.
"Since many social robots will be operated by non-expert users, it is essential for them to be equipped with natural interfaces for interaction with humans," says Yan. "Gestures are an obvious, natural means of human communication. Our LAN gesture recognition system only requires a small amount of training data, and avoids tedious training processes."
Yan and co-workers tested their software by integrating it with ShapeTape, a special jacket that uses fibre optics and inertial sensors to monitor the bending and twisting of hands and arms. They programmed the ShapeTape to provide data 80 times per second on the three-dimensional orientation of shoulders, elbows and wrists, and applied velocity thresholds to detect when gestures were starting.
In tests, five different users wore the ShapeTape jacket and used it to control a virtual robot through simple arm motions that represented commands such as forward, backwards, faster or slower. The researchers found that 99.15% of gestures were correctly translated by their system. It is also easy to add new commands, by demonstrating a new control gesture just a few times.
The next step in improving the gesture recognition system is to allow humans to control robots without the need to wear any special devices. Yan and co-workers are tackling this problem by replacing the ShapeTape jacket with motion-sensitive cameras.
"Currently we are building a new gesture recognition system by incorporating our method with a Microsoft Kinect camera," says Yan. "We will implement the proposed system on an autonomous robot to test its usability in the context of a realistic service task, such as cleaning!"

Dark Chocolate Could Prevent Heart Problems in High-Risk People

Daily consumption of dark chocolate can reduce cardiovascular events, such as heart attacks and strokes, in people with metabolic syndrome (a cluster of factors that increases the risk of developing heart disease and diabetes), finds a study published in the British Medical Journal.

Daily consumption of dark chocolate can reduce cardiovascular events, such as heart attacks and strokes, in people with metabolic syndrome (a cluster of factors that increases the risk of developing heart disease and diabetes), finds a new study.

Cardiovascular disease is the leading cause of death worldwide. Dark chocolate (containing at least 60% cocoa solids) is rich in flavonoids -- known to have heart protecting effects -- but this has only been examined in short term studies.
So a team of researchers from Melbourne, Australia used a mathematical model to predict the long-term health effects and cost effectiveness of daily dark chocolate consumption in 2,013 people already at high risk of heart disease.
All participants had high blood pressure and met the criteria for metabolic syndrome, but had no history of heart disease or diabetes and were not on blood pressure lowering therapy.
With 100% compliance (best case scenario), the researchers show that daily dark chocolate consumption could potentially avert 70 non-fatal and 15 fatal cardiovascular events per 10,000 people treated over 10 years.
Even when compliance levels were reduced to 80%, the number of non-fatal and fatal events potentially averted was 55 and 10 per 10,000 people treated over 10 years, and could still be considered an effective intervention strategy.
The model also suggested that $A40 (£25; €31; $42) could be cost effectively spent per person per year on dark chocolate prevention strategies and could be used for advertising, educational campaigns, or subsidizing dark chocolate in this high risk population, they add.
The authors stress that only non-fatal stroke and non-fatal heart attack were assessed in their analysis, and that the potential effects on other cardiovascular events, such as heart failure, are yet to be tested.
Also important, they say, is that these protective effects have only been shown for dark chocolate (at least 60-70% cocoa), rather than for milk or white chocolate, probably due to the higher levels of flavonoids found in dark chocolate.
Nevertheless, they conclude that the blood pressure and cholesterol lowering effects of plain dark chocolate "could represent an effective and cost effective strategy for people with metabolic syndrome (and no diabetes)."