Open AccessEvaluation of Computer-Based Target Achievement Tests for Myoelectric Control
Author(s) -
Jacob Gusman,
Enzo Mastinu,
Max Ortiz-Catalan
Publication year - 2017
Publication title -
ieee journal of translational engineering in health and medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.653
H-Index - 24
ISSN - 2168-2372
DOI - 10.1109/jtehm.2017.2776925
Subject(s) - bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , signal processing and analysis , robotics and control systems , general topics for engineers
Real-time evaluation of novel prosthetic control schemes is critical for translational research on artificial limbs. Recently, two computer-based, real-time evaluation tools, the target achievement control (TAC) test and the Fitts' law test (FLT), have been proposed to assess real-time controllability. Whereas TAC tests provides an anthropomorphic visual representation of the limb at the cost of confusing visual feedback, FLT clarifies the current and target locations by simplified non-anthropomorphic representations. Here, we investigated these two approaches and quantified differences in common performance metrics that can result from the chosen method of visual feedback. Ten able-bodied and one amputee subject performed target achievement tasks corresponding to the FLT and TAC test with equivalent indices of difficulty. Ablebodied subjects exhibited significantly (p <;0.05) better completion rate, path efficiency, and overshoot when performing the FLT, although no significant difference was seen in throughput performance. The amputee subject showed significantly better performance in overshoot at the FLT, but showed no significant difference in completion rate, path efficiency, and throughput. Results from the FLT showed a strong linear relationship between the movement time and the index of difficulty (R2 = 0.96), whereas TAC test results showed no apparent linear relationship (R2 = 0.19). These results suggest that in relatively similar conditions, the confusing location of virtual limb representation used in the TAC test contributed to poorer performance. Establishing an understanding of the biases of various evaluation protocols is critical to the translation of research into clinical practice.