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A Decision-Based Velocity Ramp for Minimizing the Effect of Misclassifications During Real-Time Pattern Recognition Control

Published on Aug 1, 2011in IEEE Transactions on Biomedical Engineering4.491
· DOI :10.1109/TBME.2011.2155063
Ann M. Simon19
Estimated H-index: 19
(Rehabilitation Institute of Chicago),
Levi J. Hargrove35
Estimated H-index: 35
(Rehabilitation Institute of Chicago)
+ 1 AuthorsTodd A. Kuiken45
Estimated H-index: 45
(Rehabilitation Institute of Chicago)
Abstract
Real-time pattern recognition control is frequently affected by misclassifications. This study investigated the use of a decision-based velocity ramp that attenuated movement speed after a change in classifier decision. The goal was to improve prosthesis positioning by minimizing the effect of unintended movements. Nonamputee and amputee subjects controlled a prosthesis in real time using pattern recognition. While performing a target achievement test in a virtual environment, subjects had a significantly higher completion rate (p <; 0.05) and a more direct path (p <; 0.05) to the target with the velocity ramp than without it. Using a physical prosthesis, subjects stacked a greater average number of 1-in cubes (p <; 0.05) in 3 min with the velocity ramp than without it (76% more blocks for nonamputees; 89% more blocks for amputees). Real-time control using the velocity ramp also showed significant performance improvements above using majority vote. Eighty-three percent of subjects preferred to control the prosthesis using the velocity ramp. These results suggest that using a decision-based velocity ramp with pattern recognition may improve user performance. Since the velocity ramp is a postprocessing step, it has the potential to be used with a variety of classifiers for many applications.
  • References (30)
  • Citations (76)
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References30
Newest
#1Ann M. SimonH-Index: 19
#2Levi J. HargroveH-Index: 35
Last. Todd A. Kuiken (NU: Northwestern University)H-Index: 45
view all 4 authors...
Despite high classification accuracies (~95%) of myoelectric control systems based on pattern recognition, how well offline measures translate to real-time closed-loop control is unclear. Recently, a real-time virtual test analyzed how well subjects completed arm motions using a multiple-degree of freedom (DOF) classifier. Although this test provided real-time performance metrics, the required task was oversimplified: motion speeds were normalized and unintended movements were ignored. We includ...
106 CitationsSource
#1Lauren H. Smith (NU: Northwestern University)H-Index: 11
#2Levi J. Hargrove (Rehabilitation Institute of Chicago)H-Index: 35
Last. Todd A. Kuiken (Rehabilitation Institute of Chicago)H-Index: 45
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Pattern recognition-based control of myoelectric prostheses has shown great promise in research environments, but has not been optimized for use in a clinical setting. To explore the relationship between classification error, controller delay, and real-time controllability, 13 able-bodied subjects were trained to operate a virtual upper-limb prosthesis using pattern recognition of electromyogram (EMG) signals. Classification error and controller delay were varied by training different classifier...
174 CitationsSource
#1Levi J. Hargrove (UNB: University of New Brunswick)H-Index: 35
#2Erik Scheme (UNB: University of New Brunswick)H-Index: 20
Last. B. Hudgins (UNB: University of New Brunswick)H-Index: 19
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This paper describes a novel pattern recognition based myoelectric control system that uses parallel binary classification and class specific thresholds. The system was designed with an intuitive configuration interface, similar to existing conventional myoelectric control systems. The system was assessed quantitatively with a classification error metric and functionally with a clothespin test implemented in a virtual environment. For each case, the proposed system was compared to a state-of-the...
137 CitationsSource
#1Levi J. Hargrove (Rehabilitation Institute of Chicago)H-Index: 35
#2Ping Zhou (Rehabilitation Institute of Chicago)H-Index: 22
Last. Todd A. Kuiken (Rehabilitation Institute of Chicago)H-Index: 45
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Targeted muscle reinnervation has been introduced as an effective neural machine interface. In the case of a shoulder disarticulation patient, an effective site for a nerve transfer involves the pectoralis muscles, as these perform little useful function with a missing limb. Consequently, the myoelectric signals measured from the reinnervated muscles may be corrupted by a large amount of ECG interference. This paper investigates the effect of ECG upon the accuracy of a pattern-classification-bas...
35 CitationsSource
#1Todd A. Kuiken (NU: Northwestern University)H-Index: 45
#2Guanglin Li (NU: Northwestern University)H-Index: 26
Last. Kevin Englehart (UNB: University of New Brunswick)H-Index: 24
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Context Improving the function of prosthetic arms remains a challenge, because access to the neural-control information for the arm is lost during amputation. A surgical technique called targeted muscle reinnervation (TMR) transfers residual arm nerves to alternative muscle sites. After reinnervation, these target muscles produce electromyogram (EMG) signals on the surface of the skin that can be measured and used to control prosthetic arms. Objective To assess the performance of patients with u...
598 CitationsSource
#1Laura A. Miller (NU: Northwestern University)H-Index: 16
#2Robert D. Lipschutz (Rehabilitation Institute of Chicago)H-Index: 19
Last. Todd A. Kuiken (NU: Northwestern University)H-Index: 45
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Abstract Miller LA, Lipschutz RD, Stubblefield KA, Lock BA, Huang H, Williams III TW, Weir RF, Kuiken TA. Control of a six degree of freedom prosthetic arm after targeted muscle reinnervation surgery. Objectives To fit and evaluate the control of a complex prosthesis for a shoulder disarticulation-level amputee with targeted muscle reinnervation. Design One participant who had targeted muscle reinnervation surgery was fitted with an advanced prosthesis and his use of this device was compared wit...
63 CitationsSource
We investigated the performance of three user interfaces for restoration of cursor control in individuals with tetraplegia: head orientation, electromyography(EMG) from face and neck muscles, and a standard computer mouse (for comparison). Subjects engaged in a 2-D, center-out, Fitts' Law style task and performance was evaluated using several measures. Overall, head orientation commanded motion resembled mouse commanded cursor motion (smooth, accurate movements to all targets), although with som...
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#1He Huang (Rehabilitation Institute of Chicago)H-Index: 25
#2Ping Zhou (NU: Northwestern University)H-Index: 22
Last. Todd A. Kuiken (NU: Northwestern University)H-Index: 45
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Targeted muscle reinnervation (TMR) is a novel neural machine interface for improved myoelectric prosthesis control. Previous high-density (HD) surface electromyography (EMG) studies have indicated that tremendous neural control information can be extracted from the reinnervated muscles by EMG pattern recognition (PR). However, using a large number of EMG electrodes hinders clinical application of the TMR technique. This study investigated a reduced number of electrodes and the placement require...
125 CitationsSource
#1Todd R. FarrellH-Index: 8
#2Richard F. WeirH-Index: 20
prosthesis controllers analyze fixed segments of EMG data collected from the residual musculature in an attempt to discern the intended movement of the user. However, many researchers have designed controllers with little or no regard for the delay the controller will introduce when operated in real-time. If the delay is too large the prosthesis will feel sluggish and performance will suffer. Several attributes of the classifier affect the delay it will create. State-based pattern recognition cl...
11 Citations
#1Mohammadreza Asghari Oskoei (University of Essex)H-Index: 8
#2Huosheng Hu (University of Essex)H-Index: 42
Abstract The development of an advanced human–machine interface has always been an interesting research topic in the field of rehabilitation, in which biomedical signals, such as myoelectric signals, have a key role to play. Myoelectric control is an advanced technique concerned with the detection, processing, classification, and application of myoelectric signals to control human-assisting robots or rehabilitation devices. This paper reviews recent research and development in pattern recognitio...
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Abstract Myoelectric control systems (MCSs), which recognize motions through surface electromyograms (sEMGs), present potential applicability for clinical, recreational, and motion-assisting purposes. To increase the adoption of armband device-based MCSs, the performance of motion recognition algorithms should be determined over long periods and sensor placement shifts. We prepared an sEMG dataset to assess motion recognition algorithms for practical use over long periods with varying sensor pla...
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#1Joseph L. Betthauser (Johns Hopkins University)H-Index: 5
#2John T. Krall (Johns Hopkins University)H-Index: 1
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Prediction of movement intentions from electromyographic (EMG) signals is typically performed with a pattern recognition approach, wherein a short dataframe of raw EMG is compressed into an instantaneous feature-encoding that is meaningful for classification. However, EMG signals are time-varying, implying that a frame-wise approach may not sufficiently incorporate temporal context into predictions, leading to erratic and unstable prediction behavior. Goal: We demonstrate that sequential predict...
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#1Bin Yu (USTC: University of Science and Technology of China)H-Index: 1
#2Xu Zhang (USTC: University of Science and Technology of China)H-Index: 14
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Pattern-recognition-based myoelectric control systems are not yet widely available due to their limited robustness in real-life situations. Some postprocessing methods were introduced to improve the robustness in previous studies, but there is lack of investigation into movement transition phases. This article presents a novel postprocessing method based on movement pattern transition (MPT) detection. An image-based index is used to quantify the similarity of adjacent feature matrices from high-...
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Upper limb amputation is a condition that significantly restricts the amputees from performing their daily activities. The myoelectric prosthesis, using signals from residual stump muscles, is aimed at restoring the function of such lost limbs seamlessly. Unfortunately, the acquisition and use of such myosignals are cumbersome and complicated. Furthermore, once acquired, it usually requires heavy computational power to turn it into a user control signal. Its transition to a practical prosthesis ...
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Rejection of movements based on the confidence in the classification decision has previously been demonstrated to improve the usability of pattern recognition based myoelectric control. To this point, however, the optimal rejection threshold has been determined heuristically, and it is not known how different thresholds affect the tradeoff between error mitigation and false rejections in real-time closed-loop control. To answer this question, 24 able-bodied subjects completed a real-time Fitts’ ...
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OBJECTIVE: Hand amputation is a highly disabling event, which significantly affects quality of life. An effective hand replacement can be achieved if the user, in addition to motor functions, is provided with the sensations that are naturally perceived while grasping and moving. Intraneural peripheral electrodes have shown promising results toward the restoration of the sense of touch. However, the long-term usability and clinical relevance of intraneural sensory feedback have not yet been clear...
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We present an integrated, open-source platform for the control of assistive vehicles. The system is vehicle-agnostic and can be controlled using a myoelectric interface to translate muscle contractions into vehicular commands. A modular shared-control system was used to enhance safety and ease of use, and three collision avoidance systems were included and verified in both an included test platform and on a quadcopter operating in a simulated environment. Seven subjects performed the experiments...
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