Unobtrusive Tremor Detection While Gesture Controlling a Robotic Arm
Jörg Güttler, Dany Bassily, Christos Georgoulas, Thomas Linner, and Thomas Bock
Chair of Building Realization and Robotics, Technische Universität München, Germany
Received:July 1, 2014Accepted:September 9, 2014Published:February 20, 2015
Keywords:Fourier analysis, tremor detection, leap motion controller, ageing diseases
A light weight robotic arm (Jaco) has been interfaced with a novel gesture detection sensor (Leap Motion Controller), substituting complicated conventional input devices, i.e., joysticks and pads. Due to the enhanced precision and high throughput capabilities of the Leap Motion Controller, the unobtrusive measurement of physiological tremor can be extracted. An algorithm was developed to constantly detect and indicate potential user hand tremor patterns in real-time. Additionally a calibration algorithm was developed to allow an optimum mapping between the user hand movement, tracked by the Leap Motion Controller, and the Jaco arm, by filtering unwanted oscillations, allowing for a more natural human-computer interaction.
Cite this article as:J. Güttler, D. Bassily, C. Georgoulas, T. Linner, and T. Bock, “Unobtrusive Tremor Detection While Gesture Controlling a Robotic Arm,” J. Robot. Mechatron., Vol.27 No.1, pp. 103-104, 2015.Data files:
Gesture based validation
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