Adaptive Speed and Sensitivity Configuration with Parallel Health Status Validation Via a Gesture-Based Controller - Robotic Arm Interface

Elderly people usually adverse new technologies, especially robotic system solutions, due to interrelated difficulties concerning their setup, control and operation. An intuitive gesture control algorithm for the Jaco Robotic Arm has been developed, via the Leap Motion Controller gestured based sensor. Instead of just to instruct the Jaco Robotic Arm by the Leap Motion controller, this new interface is used to measure and validate as well as the user gesture patterns in the proposed paper. Even though the implementation mainly focuses on elderly persons, e.g. Parkinson's disease is often met on individuals of this particular target group, tremor can also be detected on healthy individuals, when muscle fatigue is present. by analysing the frequency of the acquired rotational and translational user palm data retrieved by a gesture driven sensor like the Leap Motion Controller, the proposed human-machine interface is able to efficiently analyse the tremor frequency and strength, which helps the user to distinguish between a physiological and pathological tremor pattern. Because the accuracy of the measurements are suffering, while working with gestures, the calibration process of the gesture sensor has two advantages: First the arm is adjusted to a useable accuracy, and secondly the tremor and bradykinesia algorithm can work undisturbed at the same time. Due to the proposed approach, an unobtrusive user health validation has been realized, which is analysing and validating the gestures, while the user controls a robotic arm.