Authors:
E. Rocon
1
;
A. F. Ruiz
1
;
J. C. Moreno
1
;
J. L. Pons
1
;
J. A. Miranda
2
and
A. Barrientos
3
Affiliations:
1
Bioengineering group, IAI-CSIC, Spain
;
2
Technaid S. L., Spain
;
3
Grupo de Robótica y Cibernética, UPM, Spain
Keyword(s):
Tremor, Empirical mode decomposition, Inertial sensors, Timefrequency analysis, Real-Time estimation.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Cybernetics and User Interface Technologies
;
Data Manipulation
;
Devices
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Informatics in Control, Automation and Robotics
;
Information and Systems Security
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics
;
Real-Time Systems
;
Sensor Networks
;
Signal Processing, Sensors, Systems Modeling and Control
;
Soft Computing
;
Time and Frequency Response
;
Time-Frequency Analysis
Abstract:
This paper introduces the work developed by the authors in the study of tremor time series. First, it introduces
a novel technique for the study of tremor. The technique presented is a high-resolution technique that solves most of limitations of the Fourier Analysis (the standard technique to the study of tremor time series). This technique was used for the study of tremorous movement in joints of the upper limb. After, some conclusions about tremor behaviour in upper limb based on the technique introduces are presented. Furthermore, an algorithm able to estimated in real-time the voluntary and the tremorous movement was presented. This algorithm was validated in two contexts with successful results. Finally, some conclusions and future work are given.