Conference Paper

A comparison of direct and pattern recognition control for a two degree-of-freedom above elbow virtual prosthesis

DOI: 10.1109/EMBC.2012.6346925 Conference: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Source: PubMed


Individuals with a transhumeral amputation have a large functional deficit and require basic functions out of their prosthesis. Myoelectric prostheses have used amplitude control techniques for decades to restore one or two degrees of freedom to these patients. Pattern recognition control has also been investigated for transhumeral amputees, but in recent years, has been more focused on transradial amputees or high-level patients who have received targeted muscle reinnervation. This study seeks to use the most recent advances in pattern recognition control and investigate techniques that could be applied to the majority of the transhumeral amputee population that has not had the reinnervation surgery to determine if pattern recognition systems may provide them with improved control. In this study, able-bodied control subjects demonstrated that highly accurate two degree-of-freedom pattern recognition systems may be trained using four EMG channels. Such systems may be used to better control a prosthesis in real-time when compared to conventional amplitude control with mode switching.

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Available from: Cinthya Toledo, Dec 31, 2013
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    ABSTRACT: The four main functions that are available in current clinical prostheses (e.g. Otto Bock DMC Plus®) are power grasp, hand open, wrist pronation and wrist supination. Improving the control of these two DoFs is therefore of great clinical and commercial interest. This study investigates whether control performance can be improved by targeting wrist rotator muscles by means of intramuscular EMG. Nine able-bodied subjects were evaluated using offline metrics and during a real-time control task. Two intramuscular (targeted) and four surface EMG channels were recorded concurrently from the right forearm. The control was derived either from the four surface sources or by combining two surface channels combined with two intramuscular channels located in the pronator and supinator muscles (combined EMG). Five metrics (Throughput, Path Efficiency, Average Speed, Overshoot and Completion Rate) were used to quantify real-time performance. A significant improvement of 20% in Throughput was obtained with combined EMG (0.90 ± 0.12 bit/s) compared to surface EMG alone (0.75 ± 0.10 bit/s). Furthermore, combined EMG performed significantly better than the surface EMG in terms of Overshoot, Path Efficiency and offline classification error. No significant difference was found for Completion Rate and Average Speed. The results obtained in this study imply that targeting muscles that are involved in the rotation of the forearm could improve the performance of myoelectric control systems that include both wrist rotation and opening/closing of a terminal device.
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    ABSTRACT: Previous studies on intramuscular EMG based control used offline data analysis. The current study investigates the usability of intramuscular EMG in two degree-of-freedom using a Fitts’ Law approach by combining classification and proportional control to perform a task, with real time feedback of user performance. Nine able-bodied subjects participated in the study. Intramuscular and surface EMG signals were recorded concurrently from the right forearm. Five performance metrics (Throughput, Path efficiency, Average Speed, Overshoot and Completion Rate) were used for quantification of usability. Intramuscular EMG based control performed significantly better than surface EMG for Path Efficiency (80.5 ± 2.4% vs. 71.5 ± 3.8%, P = 0.004) and Overshoot (22.0 ± 3.0% vs. 45.1 ± 6.6%, P = 0.01). No difference was found between Throughput and Completion Rate. However the Average Speed was significantly higher for surface (51.8 ± 5.5%) than for intramuscular EMG (35.7 ± 2.7%). The results obtained in this study imply that intramuscular EMG has great potential as control source for advanced myoelectric prosthetic devices.
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