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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| Veröffentlicht in: | IEEE transactions on biomedical engineering Jg. 47; H. 5; S. 664 - 673 |
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| Sprache: | Englisch |
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New York, NY
IEEE
01.05.2000
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 0018-9294, 1558-2531 |
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| Abstract | 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. |
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| AbstractList | 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. Ill-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. 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). 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 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. Ill-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.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. Ill-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. 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. 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. Ill-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. |
| Author | Barner, K.E. Arce, G.R. Rahman, T. Gonzalez, J.G. Heredia, E.A. |
| Author_xml | – sequence: 1 givenname: J.G. surname: Gonzalez fullname: Gonzalez, J.G. organization: Dept. of Electr. & Comput. Eng., Delaware Univ., Newark, DE, USA – sequence: 2 givenname: E.A. surname: Heredia fullname: Heredia, E.A. – sequence: 3 givenname: T. surname: Rahman fullname: Rahman, T. – sequence: 4 givenname: K.E. surname: Barner fullname: Barner, K.E. email: barner@udel.edu – sequence: 5 givenname: G.R. surname: Arce fullname: Arce, G.R. |
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| Cites_doi | 10.1002/j.1538-7305.1982.tb03086.x 10.1109/TMMS.1969.299909 10.1152/jappl.1974.37.6.852 10.1109/TMMS.1968.300017 10.1136/jnnp.51.7.934 10.1016/S1050-6411(05)80001-X 10.1113/jphysiol.1974.sp010615 10.1007/BF02368522 10.1109/21.59975 10.1152/jn.1980.44.1.40 10.1109/TAC.1959.6429402 10.1016/0021-9290(85)90046-6 10.1109/21.59976 10.1109/THFE2.1961.4503299 10.1093/brain/95.3.579 10.1145/120782.120784 10.1109/TBME.1977.326216 10.1007/BF02368521 10.1109/TASSP.1981.1163568 |
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| Keywords | 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 |
| Language | English |
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| References_xml | – year: 1990 ident: ref14 publication-title: The Rehabilitation Specialists Handbook – volume: 16 start-page: 170 year: 1962 ident: ref9 article-title: a study of upper extremity control brace: self feeding with cerebral palsied athetoid adults publication-title: Amer J Occupat Therapy – volume: 61 start-page: 1817 year: 1982 ident: ref46 article-title: the tap-leakage algorithm: an algorithm for the stable operation of a digitally implemented, fractionally-spaced adaptive equalizer publication-title: Bell Syst Tech J doi: 10.1002/j.1538-7305.1982.tb03086.x – year: 1981 ident: ref31 publication-title: Peripheral mechanical loading and the mechanism of abnormal intention tremor – volume: dsc 12 bed 11 start-page: 17 year: 1988 ident: ref37 article-title: capacity of the human operator to move joints as control inputs to prosthesis publication-title: Model Contr Issues Biomech Syst - ASME – ident: ref35 doi: 10.1109/TMMS.1969.299909 – volume: 29 start-page: 341 year: 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physiological proprioception as a prosthesis-control technique publication-title: J Rehab Res Develop – ident: ref40 doi: 10.1109/21.59976 – ident: ref34 doi: 10.1109/THFE2.1961.4503299 – ident: ref13 doi: 10.1093/brain/95.3.579 – ident: ref24 doi: 10.1145/120782.120784 – ident: ref41 doi: 10.1109/TBME.1977.326216 – volume: 414 start-page: 17p year: 1989 ident: ref5 article-title: attenuation of wrist tremor with closed-loop electrical stimulation of muscles publication-title: J Physiol – ident: ref8 doi: 10.1007/BF02368521 – ident: ref45 doi: 10.1109/TASSP.1981.1163568 – volume: 8 start-page: 204 year: 1954 ident: ref11 article-title: an arm restrainer for the athetoid publication-title: Amer J Occupat Therapy – year: 1984 ident: ref29 publication-title: Engineering Psychology and Human Performance – volume: 25 start-page: 402 year: 1971 ident: ref12 article-title: upper extremity bracing of the severely athetoid mental retardate publication-title: Amer J Occupat Therapy – year: 1974 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| SubjectTerms | 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 |
| Title | Optimal digital filtering for tremor suppression |
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