Offline Evaluation Matters: Investigation of the Influence of Offline Performance of EMG-Based Neural-Machine Interfaces on User Adaptation, Cognitive Load, and Physical Efforts in a Real-Time Application.

There has been controversy about the value of offline evaluation of EMG-based neural-machine interfaces (NMIs) for their real-time application. Often, conclusions have been drawn after studying the correlation of the offline EMG decoding accuracy/error with the NMI user's real-time task performance without further considering other important human performance metrics such as adaptation rate, cognitive load, and physical effort. To fill this gap, this study aimed to investigate the relationship between the offline decoding accuracy of EMG-based NMIs and user adaptation, cognitive load, and physical effort in real-time NMI use. Twelve non-disabled subjects participated in this study. For each subject, we established three EMG decoders that yielded different offline accuracy (low, moderate, and high) in predicting continuous hand and wrist motions. The subject then used each EMG decoder to perform a virtual hand posture matching task in real time with and without a secondary task as the evaluation trials. Results showed that the high-level offline performance decoders yield the fastest adaptation rate and highest posture matching completion rate with the least muscle effort in users during online testing. A secondary task increased the cognitive load and reduced real-time virtual task competition rate for all the decoders; however, the decoder with high offline accuracy still produced the highest task completion rate. These results imply that the offline performance of EMG-based NMIs provide important insight to users' abilities to utilize them and should play an important role in research and development of novel NMI algorithms.

Toward Safe Wearer-Prosthesis Interaction: Evaluation of Gait Stability and Human Compensation Strategy Under Faults in Robotic Transfemoral Prostheses.

Although advanced wearable robots can assist human wearers, their internal faults (i.e., sensors or control errors) also pose a challenge. To ensure safe wearer-robot interactions, how internal errors by the prosthesis limb affect the stability of the user-prosthesis system, and how users react and compensate for the instability elicited by internal errors are imperative. The goals of this study were to 1) systematically investigate the biomechanics of a wearer-robot system reacting to internal errors induced by a powered knee prosthesis (PKP), and 2) quantify the error tolerable bound that does not affect the user's gait stability. Eight non-disabled participants and two unilateral transfemoral amputees walked on a pathway wearing a PKP, as the controller randomly switched the control parameters to disturbance parameters to mimic the errors caused by locomotion mode misrecognition. The size of prosthesis control errors was systematically varied to determine the error tolerable bound that disrupted gait stability. The effect of the error was quantified based on the 1) mechanical change described by the angular impulse applied by the PKP, and 2) overall gait instability quantified using human perception, angular momentum, and compensatory stepping. The results showed that the error tolerable bound is dependent on the gait phase and the direction of torque change. Two balance recovery strategies were also observed to allow participants to successful respond to the induced errors. The outcomes of this study may assist the future design of an auto-tuning algorithm, volitionally-controlled powered prosthetic legs, and training of gait stability.

Accuracy of the Scratch Collapse Test for Carpal Tunnel Syndrome in Comparison With Electrodiagnostic Studies.

Background: The scratch collapse test (SCT) is a clinical examination maneuver that has been previously reported as a reliable and reproducible test to diagnose carpal tunnel syndrome (CTS). The initial study by Cheng et al in 2008 showed a simple test with high sensitivity. However, subsequent attempts to reproduce those findings have resulted in lower accuracy. Our goal was to evaluate the use of the SCT for patients presenting with symptoms of pain, numbness, or weakness in an upper extremity. Methods: Forty patients were referred to the electrodiagnostic (EDX) lab for evaluation of an upper extremity. One blinded examiner who was familiar with the maneuver performed the SCT on all 40 patients. Another physician or technician performed the nerve conduction study and electromyography. Patient history and accompanying physical examination findings were not revealed to the SCT examiner. Results: The relationship between the SCT performed by a blinded examiner and the EDX performed by blinded examiners was nonsignificant (P = .676) and showed a sensitivity of 0.48, specificity of 0.59, positive predictive value of 0.61, and negative predictive value of 0.45. Conclusion: Based on this study and previous findings by other authors, we would advise against the use of the SCT in CTS for important patient-care decisions, such as surgical decision-making, until future research is done. It is possible that the SCT, in combination with other physical examination maneuvers, could increase diagnostic accuracy and enhance patient management.