Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/43660
Título : Real-Time estimation of pathological tremor parameters from gyroscope data
Autor : Gallego, Juan Álvaro, Rocón, Eduardo, Roa, Javier O., Moreno, Juan C., Pons Rovira, José Luis
Palabras clave : tremor
inertial sensors
MEMS gyroscope
tremor modelling
voluntary movement estimation
adaptive signal processing
Kalman filter
real-time estimation
neuroprosthesis
Fecha de publicación : 16-Mar-2010
Editor: Multidisciplinary Digital Publishing Institute
Citación : Sensors 10: 2129-2149
Resumen: This paper presents a two stage algorithm for real-time estimation of instanta- neous 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.
Versión del editor: http://dx.doi.org/10.3390/s100302129
Citación : Sensors 10: 2129-2149
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