Real-Time Estimation of Pathological Tremor Parameters from Gyroscope Data

Sensors

Juan A. Gallego¹  Eduardo Rocon²  Javier O. Roa²  Juan C. Moreno² 

[1] Bioengineering Group, Consejo Superior de Investigaciones Científicas, CSIC, Ctra. Campo Real, km 0.2 La Poveda, 28500, Arganda del Rey, Spain;

关键词: tremor;    inertial sensors;    MEMS gyroscope;    tremor modelling;    voluntary movement estimation;    adaptive signal processing;    Kalman filter;    real-time estimation;    neuroprosthesis;   

DOI  :  10.3390/s100302129

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.