A real-time comparison between direct control, sequential pattern recognition control and simultaneous pattern recognition control using a Fitts' law style assessment procedure

Abstract

Background: Pattern recognition (PR) based strategies for the control of myoelectric upper limb prostheses are generally evaluated through offline classification accuracy, which is an admittedly useful metric, but insufficient to discuss functional performance in real time. Existing functional tests are extensive to set up and most fail to provide a challenging, objective framework to assess the strategy performance in real time.

Methods: Nine able-bodied and two amputee subjects gave informed consent and participated in the local Institutional Review Board approved study. We designed a two-dimensional target acquisition task, based on the principles of Fitts' law for human motor control. Subjects were prompted to steer a cursor from the screen center of into a series of subsequently appearing targets of different difficulties. Three cursor control systems were tested, corresponding to three electromyography-based prosthetic control strategies: 1) amplitude-based direct control (the clinical standard of care), 2) sequential PR control, and 3) simultaneous PR control, allowing for a concurrent activation of two degrees of freedom (DOF). We computed throughput (bits/second), path efficiency (%), reaction time (second), and overshoot (%)) and used general linear models to assess significant differences between the strategies for each metric.

Results: We validated the proposed methodology by achieving very high coefficients of determination for Fitts' law. Both PR strategies significantly outperformed direct control in two-DOF targets and were more intuitive to operate. In one-DOF targets, the simultaneous approach was the least precise. The direct control was efficient in one-DOF targets but cumbersome to operate in two-DOF targets through a switch-depended sequential cursor control.

Conclusions: We designed a test, capable of comprehensively describing prosthetic control strategies in real time. When implemented on control subjects, the test was able to capture statistically significant differences (p < 0.05) in control strategies when considering throughputs, path efficiencies and reaction times. Of particular note, we found statistically significant (p < 0.01) improvements in throughputs and path efficiencies with simultaneous PR when compared to direct control or sequential PR. Amputees could readily achieve the task; however a limited number of subjects was tested and a statistical analysis was not performed with that population.

Figures

Figure 1

Fitts’ target acquisition task (FTAT) test. (A) MATLAB (The MathWorks, Inc.)-based graphical user interface (GUI) for the Fitts’ target acquisition task (FTAT) test. Subjects were prompted to move the blue cursor from the center (blue circle) into the target (red circle) using one of three EMG-based control strategies (See Table 2). (B) Widths and locations of all possible targets.

Figure 2

Fitts’ linear relationship (eq. (1)) between movement time and index of difficulty for (A) able-bodied subjects and (B) amputee subjects. Data is presented for each task type (thin lines represent 1 DOF targets and thick lines represent 2 DOF targets), and each control strategy (DC, seqPR or simPR). (A) n = 9 able-bodied subjects. (B) n = 2 amputee subjects (S10 and S11).

Figure 3

Cursor trajectories with the three control strategies (DC in green, seqPR in yellow and simPR in red) for (A) one representative able-bodied subject (B) the TR subject (S10), and (C) the TH-TMR subject (S11). For (A), (B), and (C), the left column represents all cursor trajectories for 1 DOF targets (discrete motions) and the right column represents all cursor trajectories for 2 DOF targets (combined motions).

Figure 4

Performance metrics (Mean ± Std dev.) across able-bodied subjects. Data is presented for (A) throughput (bits/sec), (B) path efficiency (%), (C) reaction time (sec) and (D) overshoot (%) in each of the three control strategies: DC (green), seqPR (yellow) and simPR (red). n = 9 able-bodied subjects.

Figure 5

Reaction time (Mean ± Std err.) and overshoot (Mean ± Std err.) for amputee subjects S10 and S11. Data is presented for reaction time in (A) for the TR subject (S10) and in (B) for the TH-TMR subject (S11); for overshoot in (C) for the TR subject (S10) and in (D) for the TH-TMR subject (S11) in each of the three control strategies: DC (green), seqPR (yellow) and simPR (red).

Figure 6

Results of the three-part questionnaire with (A) part I, (B) part II, and part III. (A) Part I: evaluation (Mean ± Std dev.) of the study design and comprehension in 3 questions with rating (1–7) to (totally disagree - totally agree). (B) Part II: evaluation of each control strategy in 5 questions with rating (1–7) to (totally disagree - totally agree) unless otherwise indicated. (C) Part III: After completion of the total experiment, subjective evaluation of which strategy subjects preferred. (n = 11: 9 able-bodied subjects, S10, and S11).