Optimal digital filtering for tremor suppression

Remote manually operated tasks such as those found in teleoperation, virtual reality, or joystick-based computer access, require the generation of an intermediate electrical signal which is transmitted to the controlled subsystem (robot arm, virtual environment, or a cursor in a computer screen). Wh...

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Vydáno v:	IEEE transactions on biomedical engineering Ročník 47; číslo 5; s. 664 - 673
Hlavní autoři:	Gonzalez, J.G., Heredia, E.A., Rahman, T., Barner, K.E., Arce, G.R.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY IEEE 01.05.2000 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Autocorrelation Biological and medical sciences Computer Peripherals Correlation methods Criteria Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases Digital filters Distortion Equalizers Equipment Design Filtering Filtration Humans Man machine systems Matlab Medical sciences Neurology Neurophysiology Optimization Parkinson Disease - complications Parkinson Disease - physiopathology Robot control Robotics Signal distortion Signal generators Signal Processing, Computer-Assisted Tremor - etiology Tremor - physiopathology Tremors Vibration Virtual environment Virtual reality Human Nervous system diseases Optimal filter Man machine system Tremor Suppression Remote operation Parkinson disease Cerebral disorder Involuntary movement Manual task Biomedical data processing Digital filter Central nervous system disease Degenerative disease Neurological disorder Performance Signal analysis Extrapyramidal syndrome
ISSN:	0018-9294, 1558-2531
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Popis
Shrnutí:	Remote manually operated tasks such as those found in teleoperation, virtual reality, or joystick-based computer access, require the generation of an intermediate electrical signal which is transmitted to the controlled subsystem (robot arm, virtual environment, or a cursor in a computer screen). When human movements are distorted, for instance, by tremor, performance can be improved by digitally filtering the intermediate signal before it reaches the controlled device. This paper introduces a novel tremor filtering framework in which digital equalizers are optimally designed through pursuit tracking task experiments. Due to inherent properties of the man-machine system, the design of tremor suppression equalizers presents two serious problems: 1) performance criteria leading to optimizations that minimize mean-squared error are not efficient for tremor elimination and 2) movement signals show ill-conditioned autocorrelation matrices, which often result in useless or unstable solutions. To address these problems, a new performance indicator in the context of tremor is introduced, and the optimal equalizer according to this new criterion is developed, III-conditioning of the autocorrelation matrix is overcome using a novel method which we call pulled-optimization. Experiments performed with artificially induced vibrations and a subject with Parkinson's disease show significant improvement in performance. Additional results, along with MATLAB source code of the algorithms, and a customizable demo for PC joysticks, are available on the Internet at http://tremor-suppression.com.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 ObjectType-Article-2 ObjectType-Feature-1
ISSN:	0018-9294 1558-2531
DOI:	10.1109/10.841338