DSpace

Digital.CSIC > Ciencia y Tecnologías Físicas > Centro de Automática y Robótica (CAR) > (CAR) Artículos >

Share

EndNote

Impact

Open Access item Real-Time estimation of pathological tremor parameters from gyroscope data

Authors:Gallego, Juan A.
Rocon, Eduardo
Roa, Javier O.
Moreno, Juan C.
Pons, José L.
Keywords:tremor, inertial sensors, MEMS gyroscope, tremor modelling, voluntary movement estimation, adaptive signal processing, Kalman filter, real-time estimation, neuroprosthesis
Issue Date:16-Mar-2010
Publisher:Multidisciplinary Digital Publishing Institute
Citation:Sensors 10: 2129-2149
Abstract: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.
Publisher version (URL):http://dx.doi.org/10.3390/s100302129
URI:http://hdl.handle.net/10261/43660
E-ISSNmetadata.dc.identifier.doi = DOI:1424-8220
Appears in Collections:(CAR) Artículos

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.