JRM Vol.27 No.1 pp. 103-104
doi: 10.20965/jrm.2015.p0103

Development Report:

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

July 1, 2014
September 9, 2014
February 20, 2015
Fourier analysis, tremor detection, leap motion controller, ageing diseases
Gesture based validation

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:
  1. [1] F. Weichert, D. Bachmann, B. Rudak, and D. Fisseler, “Analysis of the accuracy and robustness of the leap motion controller,” Sensors, Vol.13, No.5, pp. 6380-6393, 2013.
  2. [2] D. Bassily, C. Georgoulas, J. Guettler, T. Linner, and T. Bock, “Intuitive and Adaptive Robotic Arm Manipulation using the Leap Motion Controller,” Proc. of the 45th Int. Symposium on Robotics (ISR 2014) and the 8th German Conf. on Robotics (ROBOTIK 2014), Munich, Germany, June 2-3, pp. 78-84, 2014.

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Last updated on Nov. 15, 2018