Virtual reality is becoming more of a thing, now that we have high quality headsets and the computing power to generate attractive environments. Many VR systems use controllers held in mid air, or camera-based systems that track limbs and hands for interaction. However, productivity scenarios often require prolonged interactions over a long period of time, which typically necessitates working at surfaces that allow the body to rest intermittently. To help facilitate this, a group of researchers at ETH Zurich developed TapID, including a preprint paper (PDF) that will be presented at IEEE VR 2021 later this month.
TapID consists of a wristband that carries two motion sensors, with one worn on each wrist. This allows TapID to detect taps from each of the user’s fingers individually, thanks to a machine learning algorithm that analyses the unique vibrations through your skeletal system. This is demonstrated as being useful for VR environments, where the user can type into a virtual keyboard, or interact with virtual objects on a surface, using their fingers as they would in the real world. This is a sensor fusion with the features of modern VR headsets that include hand tracking. The TapID wristbands deliver granularity and detection of small motions that is not nearly as accurate through headset-mounted senors and camera-based detection.
Test hardware includes 4 accelerometers. Two on flexible PCBs are the sensing hardware used by the system, the other two on the rigid PCB are used as a baseline during testing but do not co ..
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