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Sensors 2010, 10(3), 2129-2149; doi:10.3390/s100302129
Article

Real-Time Estimation of Pathological Tremor Parameters from Gyroscope Data

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Bioengineering Group, Consejo Superior de Investigaciones Científicas, CSIC, Ctra. Campo Real, km 0.2 La Poveda, 28500, Arganda del Rey, Spain
* Author to whom correspondence should be addressed.
Received: 25 January 2010 / Revised: 26 February 2010 / Accepted: 1 March 2010 / Published: 16 March 2010
(This article belongs to the Special Issue Motion Detectors)
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Abstract

This paper presents a two stage algorithm for real-time estimation of instantaneous tremor parameters from gyroscope recordings. Gyroscopes possess the advantage of providing directly joint rotational speed, overcoming the limitations of traditional tremor recording based on accelerometers. The proposed algorithm first extracts tremor patterns from raw angular data, and afterwards estimates its instantaneous amplitude and frequency. Real-time separation of voluntary and tremorous motion relies on their different frequency contents, whereas tremor modelling is based on an adaptive LMS algorithm and a Kalman filter. Tremor parameters will be employed to drive a neuroprosthesis for tremor suppression based on biomechanical loading.
Keywords: tremor; inertial sensors; MEMS gyroscope; tremor modelling; voluntary movement estimation; adaptive signal processing; Kalman filter; real-time estimation; neuroprosthesis tremor; inertial sensors; MEMS gyroscope; tremor modelling; voluntary movement estimation; adaptive signal processing; Kalman filter; real-time estimation; neuroprosthesis
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Gallego, J.A.; Rocon, E.; Roa, J.O.; Moreno, J.C.; Pons, J.L. Real-Time Estimation of Pathological Tremor Parameters from Gyroscope Data. Sensors 2010, 10, 2129-2149.

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