The Experts below are selected from a list of 99267 Experts worldwide ranked by ideXlab platform
Philippe Lutz - One of the best experts on this subject based on the ideXlab platform.
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voltage frequency Proportional Control of stick slip micropositioning systems
IEEE Transactions on Control Systems and Technology, 2008Co-Authors: Micky Rakotondrabe, Yassine Haddab, Philippe LutzAbstract:A new Control type for stick-slip micropositioning systems is proposed in this brief: the voltage/frequency (U/f) Proportional Control. It gives more precise results relatively to the classical Control algorithm. It is also an assembling of two classical Controllers: the sign and the classical Proportional Controllers. A high stroke model of a stick-slip micropositioning system is first given. Then, we will theoretically analyze the performances of the closed-loop process with the U/f Controller. Finally, we will give some experimental results obtained with different values of the Proportional gains.
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Voltage/frequency Proportional Control of stick-slip micropositioning systems
IEEE Transactions on Control Systems Technology, 2008Co-Authors: Micky Rakotondrabe, Yassine Haddab, Philippe LutzAbstract:A new Control type for stick-slip micropositioning systems is proposed in this brief: the voltage/frequency (U/f) Proportional Control. It gives more precise results relatively to the classical Control algorithm. It is also an assembling of two classical Controllers: the sign and the classical Proportional Controllers. A high stroke model of a stick-slip micropositioning system is first given. Then, we will theoretically analyze the performances of the closed-loop process with the U/f Controller. Finally, we will give some experimental results obtained with different values of the Proportional gains.
Micky Rakotondrabe - One of the best experts on this subject based on the ideXlab platform.
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voltage frequency Proportional Control of stick slip micropositioning systems
IEEE Transactions on Control Systems and Technology, 2008Co-Authors: Micky Rakotondrabe, Yassine Haddab, Philippe LutzAbstract:A new Control type for stick-slip micropositioning systems is proposed in this brief: the voltage/frequency (U/f) Proportional Control. It gives more precise results relatively to the classical Control algorithm. It is also an assembling of two classical Controllers: the sign and the classical Proportional Controllers. A high stroke model of a stick-slip micropositioning system is first given. Then, we will theoretically analyze the performances of the closed-loop process with the U/f Controller. Finally, we will give some experimental results obtained with different values of the Proportional gains.
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Voltage/frequency Proportional Control of stick-slip micropositioning systems
IEEE Transactions on Control Systems Technology, 2008Co-Authors: Micky Rakotondrabe, Yassine Haddab, Philippe LutzAbstract:A new Control type for stick-slip micropositioning systems is proposed in this brief: the voltage/frequency (U/f) Proportional Control. It gives more precise results relatively to the classical Control algorithm. It is also an assembling of two classical Controllers: the sign and the classical Proportional Controllers. A high stroke model of a stick-slip micropositioning system is first given. Then, we will theoretically analyze the performances of the closed-loop process with the U/f Controller. Finally, we will give some experimental results obtained with different values of the Proportional gains.
Yassine Haddab - One of the best experts on this subject based on the ideXlab platform.
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voltage frequency Proportional Control of stick slip micropositioning systems
IEEE Transactions on Control Systems and Technology, 2008Co-Authors: Micky Rakotondrabe, Yassine Haddab, Philippe LutzAbstract:A new Control type for stick-slip micropositioning systems is proposed in this brief: the voltage/frequency (U/f) Proportional Control. It gives more precise results relatively to the classical Control algorithm. It is also an assembling of two classical Controllers: the sign and the classical Proportional Controllers. A high stroke model of a stick-slip micropositioning system is first given. Then, we will theoretically analyze the performances of the closed-loop process with the U/f Controller. Finally, we will give some experimental results obtained with different values of the Proportional gains.
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Voltage/frequency Proportional Control of stick-slip micropositioning systems
IEEE Transactions on Control Systems Technology, 2008Co-Authors: Micky Rakotondrabe, Yassine Haddab, Philippe LutzAbstract:A new Control type for stick-slip micropositioning systems is proposed in this brief: the voltage/frequency (U/f) Proportional Control. It gives more precise results relatively to the classical Control algorithm. It is also an assembling of two classical Controllers: the sign and the classical Proportional Controllers. A high stroke model of a stick-slip micropositioning system is first given. Then, we will theoretically analyze the performances of the closed-loop process with the U/f Controller. Finally, we will give some experimental results obtained with different values of the Proportional gains.
Kevin Englehart - One of the best experts on this subject based on the ideXlab platform.
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A Proportional Control scheme for high density force myography.
Journal of neural engineering, 2018Co-Authors: Alexander T Belyea, Kevin Englehart, Erik SchemeAbstract:OBJECTIVE Force myography (FMG) has been shown to be a potentially higher accuracy alternative to electromyography for pattern recognition based prosthetic Control. Classification accuracy, however, is just one factor that affects the usability of a Control system. Others, like the ability to start and stop, to coordinate dynamic movements, and to Control the velocity of the device through some Proportional Control scheme can be of equal importance. To impart effective fine Control using FMG-based pattern recognition, it is important that a method of Controlling the velocity of each motion be developed. METHODS In this work force myography data were collected from 14 able bodied participants and one amputee participant as they performed a set of wrist and hand motions. The offline Proportional Control performance of a standard mean signal amplitude approach and a proposed regression-based alternative was compared. The impact of providing feedback during training, as well as the use of constrained or unconstrained hand and wrist contractions, were also evaluated. RESULTS It is shown that the commonly used mean of rectified channel amplitudes approach commonly employed with electromyography does not translate to force myography. The proposed class-based regression Proportional Control approach is shown significantly outperform this standard approach (ρ
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motion normalized Proportional Control for improved pattern recognition based myoelectric Control
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2014Co-Authors: Erik Scheme, Levi J. Hargrove, Blair A Lock, Wendy Hill, Usha Kuruganti, Kevin EnglehartAbstract:This paper describes two novel Proportional Control algorithms for use with pattern recognition-based myoelectric Control. The systems were designed to provide automatic configuration of motion-specific gains and to normalize the Control space to the user's usable dynamic range. Class-specific normalization parameters were calculated using data collected during classifier training and require no additional user action or configuration. The new Control schemes were compared to the standard method of deriving Proportional Control using a one degree of freedom Fitts' law test for each of the wrist flexion/extension, wrist pronation/supination and hand close/open degrees of freedom. Performance was evaluated using the Fitts' law throughput value as well as more descriptive metrics including path efficiency, overshoot, stopping distance and completion rate. The proposed normalization methods significantly outperformed the incumbent method in every performance category for able bodied subjects and nearly every category for amputee subjects. Furthermore, one proposed method significantly outperformed both other methods in throughput , yielding 21% and 40% improvement over the incumbent method for amputee and able bodied subjects, respectively. The proposed Control schemes represent a computationally simple method of fundamentally improving myoelectric Control users' ability to elicit robust, and Controlled, Proportional velocity commands.
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training strategies for mitigating the effect of Proportional Control on classification in pattern recognition based myoelectric Control
Jpo Journal of Prosthetics and Orthotics, 2013Co-Authors: Erik Scheme, Kevin EnglehartAbstract:The performance of pattern recognition based myoelectric Control has seen significant interest in the research community for many years. Due to a recent surge in the development of dexterous prosthetic devices, determining the clinical viability of multifunction myoelectric Control has become paramount. Several factors contribute to differences between offline classification accuracy and clinical usability, but the overriding theme is that the variability of the elicited patterns increases greatly during functional use. Proportional Control has been shown to greatly improve the usability of conventional myoelectric Control systems. Typically, a measure of the amplitude of the electromyogram (a rectified and smoothed version) is used to dictate the velocity of Control of a device. The discriminatory power of myoelectric pattern classifiers, however, is also largely based on amplitude features of the electromyogram. This work presents an introductory look at the effect of contraction strength and Proportional Control on pattern recognition based Control. These effects are investigated using typical pattern recognition data collection methods as well as a real-time position tracking test. Training with dynamically force varying contractions and appropriate gain selection is shown to significantly improve (p<0.001) the classifier’s performance and tolerance to Proportional Control.
Erik Scheme - One of the best experts on this subject based on the ideXlab platform.
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A Proportional Control scheme for high density force myography.
Journal of neural engineering, 2018Co-Authors: Alexander T Belyea, Kevin Englehart, Erik SchemeAbstract:OBJECTIVE Force myography (FMG) has been shown to be a potentially higher accuracy alternative to electromyography for pattern recognition based prosthetic Control. Classification accuracy, however, is just one factor that affects the usability of a Control system. Others, like the ability to start and stop, to coordinate dynamic movements, and to Control the velocity of the device through some Proportional Control scheme can be of equal importance. To impart effective fine Control using FMG-based pattern recognition, it is important that a method of Controlling the velocity of each motion be developed. METHODS In this work force myography data were collected from 14 able bodied participants and one amputee participant as they performed a set of wrist and hand motions. The offline Proportional Control performance of a standard mean signal amplitude approach and a proposed regression-based alternative was compared. The impact of providing feedback during training, as well as the use of constrained or unconstrained hand and wrist contractions, were also evaluated. RESULTS It is shown that the commonly used mean of rectified channel amplitudes approach commonly employed with electromyography does not translate to force myography. The proposed class-based regression Proportional Control approach is shown significantly outperform this standard approach (ρ
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motion normalized Proportional Control for improved pattern recognition based myoelectric Control
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2014Co-Authors: Erik Scheme, Levi J. Hargrove, Blair A Lock, Wendy Hill, Usha Kuruganti, Kevin EnglehartAbstract:This paper describes two novel Proportional Control algorithms for use with pattern recognition-based myoelectric Control. The systems were designed to provide automatic configuration of motion-specific gains and to normalize the Control space to the user's usable dynamic range. Class-specific normalization parameters were calculated using data collected during classifier training and require no additional user action or configuration. The new Control schemes were compared to the standard method of deriving Proportional Control using a one degree of freedom Fitts' law test for each of the wrist flexion/extension, wrist pronation/supination and hand close/open degrees of freedom. Performance was evaluated using the Fitts' law throughput value as well as more descriptive metrics including path efficiency, overshoot, stopping distance and completion rate. The proposed normalization methods significantly outperformed the incumbent method in every performance category for able bodied subjects and nearly every category for amputee subjects. Furthermore, one proposed method significantly outperformed both other methods in throughput , yielding 21% and 40% improvement over the incumbent method for amputee and able bodied subjects, respectively. The proposed Control schemes represent a computationally simple method of fundamentally improving myoelectric Control users' ability to elicit robust, and Controlled, Proportional velocity commands.
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training strategies for mitigating the effect of Proportional Control on classification in pattern recognition based myoelectric Control
Jpo Journal of Prosthetics and Orthotics, 2013Co-Authors: Erik Scheme, Kevin EnglehartAbstract:The performance of pattern recognition based myoelectric Control has seen significant interest in the research community for many years. Due to a recent surge in the development of dexterous prosthetic devices, determining the clinical viability of multifunction myoelectric Control has become paramount. Several factors contribute to differences between offline classification accuracy and clinical usability, but the overriding theme is that the variability of the elicited patterns increases greatly during functional use. Proportional Control has been shown to greatly improve the usability of conventional myoelectric Control systems. Typically, a measure of the amplitude of the electromyogram (a rectified and smoothed version) is used to dictate the velocity of Control of a device. The discriminatory power of myoelectric pattern classifiers, however, is also largely based on amplitude features of the electromyogram. This work presents an introductory look at the effect of contraction strength and Proportional Control on pattern recognition based Control. These effects are investigated using typical pattern recognition data collection methods as well as a real-time position tracking test. Training with dynamically force varying contractions and appropriate gain selection is shown to significantly improve (p<0.001) the classifier’s performance and tolerance to Proportional Control.
