2020 · 12 citations · 10 references
EngineeringComputer SystemsAssistive TechnologyComputer VisionSensorsCapacitive SensingMotion CaptureMotion SensorsTracking SystemsCapacitive Motion SensingCapacitive Proximity SensingCapacitive SensorsHand TrackingLeave-one-out Cross-validationLong Short-term Memory NetworksMean Absolute ErrorMean Absolute Error Analysis
We present a ring-shaped interaction device, called PeriSense, utilizing capacitive sensing in order to enable finger tracking. The finger angles and its adjacent fingers are sensed by measuring capacitive proximity between electrodes and human skin. To map the capacitive measurements to the finger angles, we use long short-term memory (LSTM). By wearing the ring on the middle finger, the angles of the index, middle and ring finger can be determined from the capacitive measurements. We collected sample data from 17 users using a Leap Motion camera, which provided the reference data. In a leave-one-user-out cross-validation test, we revealed a mean absolute error of 13.02 degrees over all finger angles. The motion of the little finger and the thumb are out of the capacitive measurement range or covered by the index and ring finger, respectively. With natural finger movements, the LSTM estimates the angles of the little finger and thumb based on the movement pattern of the other fingers.
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