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Disney Research shows smart watch that can recognize touched objects
The research department of Disney has partnered with Carnegie Mellon University created a proof-of-concept of a smart watch that can recognize touched objects. The EM-sense does that by analyzing electromagnetic signals.
Many objects emit electromagnetic signals; as soon as one touches an object, the signals enter the body. The wearable prototype of Disney Research and Carnegie Mellon University captures these signals and, according to the researchers then determine what object or object touches the wearer of the smart watch. The researchers made their findings in a paper published and show a proof-of-concept video how the technique in practice could be applied.
In the paper, the researchers describe that they have a cheap software-defined radio receiver, converted to a sensor that can detect electromagnetic signals. In the prototype, this radio-receiver mounted on the underside of the smart watch. The wearable itself is very similar to the Samsung Galaxy Gear smart watch. Making the adjustments would have cost the researchers less than 10 dollars.
The signals that receives the radio receiver are analyzed and using machine learning, the EM-sense determine what object or device touches the wearer of the wearable. All objects that are electrically or electro-magnetically, could be classified. In addition, even large metal objects such things as doors, furniture and frames are recognized according to the researchers. They claim that in their tests an accuracy of 96.1% was achieved.
By recognizing which object the wearer of the EM-sense touch, the smart watch can make a good estimate where the user is doing and respond with another action. For example, it automatically set a timer when the user grasps a toothbrush. The EM-sense can tell the wearer what agreements he has when he opens the door of his office.
Whether and when the technique of EM-sense actually on the market is to come is not yet known. Disney Research is an international network of research labs. Rather they presented an algorithm for creating panorama videos using images from multiple cameras.
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