Control Strategies and Performance Assessment of Upper-Limb TMR Prostheses: A Review.

The evolution of technological and surgical techniques has made it possible to obtain an even more intuitive control of multiple joints using advanced prosthetic systems. Targeted Muscle Reinnervation (TMR) is considered to be an innovative and relevant surgical technique for improving the prosthetic control for people with different amputation levels of the limb. Indeed, TMR surgery makes it possible to obtain reinnervated areas that act as biological amplifiers of the motor control. On the technological side, a great deal of research has been conducted in order to evaluate various types of myoelectric prosthetic control strategies, whether direct control or pattern recognition-based control. In the literature, different control performance metrics, which have been evaluated on TMR subjects, have been introduced, but no accepted reference standard defines the better strategy for evaluating the prosthetic control. Indeed, the presence of several evaluation tests that are based on different metrics makes it difficult the definition of standard guidelines for comprehending the potentiality of the proposed control systems. Additionally, there is a lack of evidence about the comparison of different evaluation approaches or the presence of guidelines on the most suitable test to proceed for a TMR patients case study. Thus, this review aims at identifying these limitations by examining the several studies in the literature on TMR subjects, with different amputation levels, and proposing a standard method for evaluating the control performance metrics.

A Sensory Feedback Neural Stimulator Prototype for Both Implantable and Wearable Applications.

The restoration of sensory feedback is one of the current challenges in the field of prosthetics. This work, following the analysis of the various types of sensory feedback, aims to present a prototype device that could be used both for implantable applications to perform PNS and for wearable applications, performing TENS, to restore sensory feedback. The two systems are composed of three electronic boards that are presented in detail, as well as the bench tests carried out. To the authors' best knowledge, this work presents the first device that can be used in a dual scenario for restoring sensory feedback. Both the implantable and wearable versions respected the expected values regarding the stimulation parameters. In its implantable version, the proposed system allows simultaneous and independent stimulation of 30 channels. Furthermore, the capacity of the wearable version to elicit somatic sensations was evaluated on healthy participants demonstrating performance comparable with commercial solutions.

Hierarchical strategy for sEMG classification of the hand/wrist gestures and forces of transradial amputees.

Introduction: The myoelectric control strategy, based on surface electromyographic signals, has long been used for controlling a prosthetic system with multiple degrees of freedom. Several methods classify gestures and force levels but the simultaneous real-time control of hand/wrist gestures and force levels did not yet reach a satisfactory level of effectiveness. Methods: In this work, the hierarchical classification approach, already validated on 31 healthy subjects, was adapted for the real-time control of a multi-DoFs prosthetic system on 15 trans-radial amputees. The effectiveness of the hierarchical classification approach was assessed by evaluating both offline and real-time performance using three algorithms: Logistic Regression (LR), Non-linear Logistic Regression (NLR), and Linear Discriminant Analysis (LDA). Results: The results of this study showed the offline performance of amputees was promising and comparable to healthy subjects, with mean F1 scores of over 90% for the "Hand/wrist gestures classifier" and 95% for the force classifiers, implemented with the three algorithms with features extraction (FE). Another significant finding of this study was the feasibility of using the hierarchical classification strategy for real-time applications, due to its ability to provide a response time of 100 ms while maintaining an average online accuracy of above 90%. Discussion: A possible solution for real-time control of both hand/wrist gestures and force levels is the combined use of the LR algorithm with FE for the "Hand/wrist gestures classifier", and the NLR with FE for the Spherical and Tip force classifiers.

Exploring the EMG transient: the muscular activation sequences used as novel time-domain features for hand gestures classification.

Introduction: Muscular activation sequences have been shown to be suitable time-domain features for classification of motion gestures. However, their clinical application in myoelectric prosthesis control was never investigated so far. The aim of the paper is to evaluate the robustness of these features extracted from the EMG signal in transient state, on the forearm, for classifying common hand tasks. Methods: The signal associated to four hand gestures and the rest condition were acquired from ten healthy people and two persons with trans-radial amputation. A feature extraction algorithm allowed for encoding the EMG signals into muscular activation sequences, which were used to train four commonly used classifiers, namely Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Non-linear Logistic Regression (NLR) and Artificial Neural Network (ANN). The offline performances were assessed with the entire sample of recruited people. The online performances were assessed with the amputee subjects. Moreover, a comparison of the proposed method with approaches based on the signal envelope in the transient state and in the steady state was conducted. Results: The highest performance were obtained with the NLR classifier. Using the sequences, the offline classification accuracy was higher than 93% for healthy and amputee subjects and always higher than the approach with the signal envelope in transient state. As regards the comparison with the steady state, the performances obtained with the proposed method are slightly lower (<4%), but the classification occurred at least 200 ms earlier. In the online application, the motion completion rate reached up to 85% of the total classification attempts, with a motion selection time that never exceeded 218 ms. Discussion: Muscular activation sequences are suitable alternatives to the time-domain features commonly used in classification problems belonging to the sole EMG transient state and could be potentially exploited in control strategies of myoelectric prosthesis hands.

Dynamic balance is impaired after a match in young elite soccer players.

PURPOSE: The aim of this study is to assess the effect of actual match effort on dynamic balance abilities in young elite soccer players. METHODS: Seventeen Under 15 male players who compete at national level participated in the study. Their dynamic balance was assessed by having them jump starting with both feet on the ground in a standing position and land on one foot only. Their vertical time to stabilization (vTTS) and postural sway were calculated before and after 35 min of an unofficial match. Postural sway was assessed on the basis of center-of-pressure (COP) trajectories. Parameters considered were sway area, COP displacements in the antero-posterior (AP) and medio-lateral (ML) directions and COP path length. RESULTS: After the match, a significant increase in vTTS (p = 0.007) COP path length (p = 0.001) and COP displacements in ML (p < 0.001) was observed. Such effects involve both non-dominant (vTTS, path length) and dominant limb (COP displacements). CONCLUSIONS: The physical effort associated with the match induces significant impairments of players' dynamic balance abilities. On the basis of such findings, coaches might consider integrating training sessions with specific balance exercises as well as performing injury-prevention routines even when players are fatigued, to better adapt them to match conditions.