An Algorithm for Choosing the Optimal Number of Muscle Synergies during Walking

In motor control studies, the 90% thresholding of variance accounted for (VAF) is the classical way of selecting the number of muscle synergies expressed during a motor task. However, the adoption of an arbitrary cut-off has evident drawbacks. The aim of this work is to describe and validate an algorithm for choosing the optimal number of muscle synergies (ChoOSyn), which can overcome the limitations of VAF-based methods. The proposed algorithm is built considering the following principles: (1) muscle synergies should be highly consistent during the various motor task epochs (i.e., remaining stable in time), (2) muscle synergies should constitute a base with low intra-level similarity (i.e., to obtain information-rich synergies, avoiding redundancy). The algorithm performances were evaluated against traditional approaches (threshold-VAF at 90% and 95%, elbow-VAF and plateau-VAF), using both a simulated dataset and a real dataset of 20 subjects. The performance evaluation was carried out by analyzing muscle synergies extracted from surface electromyographic (sEMG) signals collected during walking tasks lasting 5 min. On the simulated dataset, ChoOSyn showed comparable performances compared to VAF-based methods, while, in the real dataset, it clearly outperformed the other methods, in terms of the fraction of correct classifications, mean error (ME), and root mean square error (RMSE). The proposed approach may be beneficial to standardize the selection of the number of muscle synergies between different research laboratories, independent of arbitrary thresholds

Atypical Gait Cycles in Parkinson’s Disease

It is important to find objective biomarkers for evaluating gait in Parkinson’s Disease (PD), especially related to the foot and lower leg segments. Foot-switch signals, analyzed through Statistical Gait Analysis (SGA), allow the foot-floor contact sequence to be characterized during a walking session lasting five-minutes, which includes turnings. Gait parameters were compared between 20 PD patients and 20 age-matched controls. PDs showed similar straight-line speed, cadence, and double-support compared to controls, as well as typical gait-phase durations, except for a small decrease in the flat-foot contact duration (−4% of the gait cycle, p = 0.04). However, they showed a significant increase in atypical gait cycles (+42%, p = 0.006), during both walking straight and turning. A forefoot strike, instead of a “normal” heel strike, characterized the large majority of PD’s atypical cycles, whose total percentage was 25.4% on the most-affected and 15.5% on the least-affected side. Moreover, we found a strong correlation between the atypical cycles and the motor clinical score UPDRS-III (r = 0.91, p = 0.002), in the subset of PD patients showing an abnormal number of atypical cycles, while we found a moderate correlation (r = 0.60, p = 0.005), considering the whole PD population. Atypical cycles have proved to be a valid biomarker to quantify subtle gait dysfunctions in PD patients

Surface Electromyography Applied to Gait Analysis: How to Improve Its Impact in Clinics?

Surface electromyography (sEMG) is the main non-invasive tool used to record the electrical activity of muscles during dynamic tasks. In clinical gait analysis, a number of techniques have been developed to obtain and interpret the muscle activation patterns of patients showing altered locomotion. However, the body of knowledge described in these studies is very seldom translated into routine clinical practice. The aim of this work is to analyze critically the key factors limiting the extensive use of these powerful techniques among clinicians. A thorough understanding of these limiting factors will provide an important opportunity to overcome limitations through specific actions, and advance toward an evidence-based approach to rehabilitation based on objective findings and measurements

Muscle synergies in Parkinson's disease before and after the deep brain stimulation of the bilateral subthalamic nucleus

The aim of this study is to quantitatively assess motor control changes in Parkinson's disease (PD) patients after bilateral deep brain stimulation of the subthalamic nucleus (STN-DBS), based on a novel muscle synergy evaluation approach. A group of 20 PD patients evaluated at baseline (before surgery, T0), at 3 months (T1), and at 12 months (T2) after STN-DBS surgery, as well as a group of 20 age-matched healthy control subjects, underwent an instrumented gait analysis, including surface electromyography recordings from 12 muscles. A smaller number of muscle synergies was found in PD patients (4 muscle synergies, at each time point) compared to control subjects (5 muscle synergies). The neuromuscular robustness of PD patients-that at T0 was smaller with respect to controls (PD T0: 69.3 ± 2.2% vs. Controls: 77.6 ± 1.8%, p = 0.004)-increased at T1 (75.8 ± 1.8%), becoming not different from that of controls at T2 (77.5 ± 1.9%). The muscle synergies analysis may offer clinicians new knowledge on the neuromuscular structure underlying PD motor types of behavior and how they can improve after electroceutical STN-DBS therapy

Automatic Identification of the Best Auscultation Area for the Estimation of the Time of Closure of Heart Valves through Multi-Source Phonocardiography

In the latest years, multi-source phonocardiography (PCG) is gaining interest in relation to the home monitoring of cardiovascular diseases. An application of interest regards the monitoring of the time of closure of the four cardiac valves, which would enable the follow-up of at-risk patients for heart failure. In this work, we propose a hybrid system based on hierarchical clustering and Multi-Criteria Decision Analysis (MCDA) for automatically selecting the best auscultation area for the mentioned application through multi-source PCG. We simultaneously recorded 48 PCG signals from the subject's chest and divided them into morphologically homogenous groups using agglomerative hierarchical clustering, based on their correlation. Then, we explored three different approaches to select the best auscultation area, based respectively on the minimum latency, on the maximum signal-to-noise ratio, and on multiple criteria using ELECTRE III. The results obtained on the follow-up of a healthy subject over consecutive days show that a) the selection of the auscultation area using MCDA overcomes the limits of single-criteria approaches, b) the estimate of the time of closure of the heart valves using the proposed system is more robust than what obtained through the state-of-the-art single-source methodology

Influence of Gait Cycle Normalization on Principal Activations

The Clustering for Identification of Muscle Activation Pattern (CIMAP) algorithm has been recently proposed to cope with the high intra-subject variability of muscle activation patterns and to allow the extraction of principal activations (PAs), defined as those muscle activation intervals that are strictly necessary to perform a specific task. To assess differences between different PAs, gait cycle normalization techniques are needed to handle between- and within-subject variability. The aim of this contribution is to assess the effect of two different time-normalization techniques (Linear Length Normalization and Piecewise Linear Length Normalization) on PA extraction, in terms of inter-subject similarity. Results demonstrated no statistically significant differences in the inter-subject similarity between the two tested approaches, revealing, on the average, inter-subject similarity values higher than 0.64. Moreover, a statistically significant difference in the inter-subject similarity among muscles was assessed, revealing a higher similarity of PAs extracted considering the distal lower limb muscles. In conclusion, our results demonstrated that PAs extracted from healthy subjects during a walking task at comfortable walking speed are not affected by the time-normalization approach implemented

Muscle activations during functional tasks in individuals with chronic ankle instability: a systematic review of electromyographical studies

Background: It has been reported that individuals with chronic ankle instability (CAI) show motor control ab-normalities. The study of muscle activations by means of surface electromyography (sEMG) plays a key role in understanding some of the features of movement abnormalities. Research question: Do common sEMG activation abnormalities and strategies exists across different functional movements? Methods: Literature review was conducted on PubMed, Web-of-Science and Cochrane databases. Studies pub-lished between 2000 and 2020 that assessed muscle activations by means of sEMG during any type of functional task in individuals with CAI, and used healthy individuals as controls, were included. Methodological quality was assessed using the modified Downs&Black checklist. Since the methodologies of different studies were hetero-geneous, no meta-analysis was conducted. Results: A total of 63 articles investigating muscle activations during gait, running, responses to perturbations, landing and hopping, cutting and turning; single-limb stance, star excursion balance task, forward lunges, ball- kicking, y-balance test and single-limb squatting were considered. Individuals with CAI showed a delayed activation of the peroneus longus in response to sudden inversion perturbations, in transitions between double- and single-limb stance, and in landing on unstable surfaces. Apparently, while walking on ground there are no differences between CAI and controls, walking on a treadmill increases the variability of muscles activations, probably as a “safety strategy” to avoid ankle inversion. An abnormal activation of the tibialis anterior was observed during a number of tasks. Finally, hip/spine muscles were activated before ankle muscles in CAI compared to controls. Conclusion: Though the methodology of the studies herein considered is heterogeneous, this review shows that the peroneal and tibialis anterior muscles have an abnormal activation in CAI individuals. These individuals also show a proximal muscle activation strategy during the performance of balance challenging tasks. Future studies should investigate whole-body muscle activation abnormalities in CAI individuals

Evaluation of Muscle Function by Means of a Muscle-Specific and a Global Index

Gait analysis applications in clinics are still uncommon, for three main reasons: (1) the considerable time needed to prepare the subject for the examination; (2) the lack of user-independent tools; (3) the large variability of muscle activation patterns observed in healthy and pathological subjects. Numerical indices quantifying the muscle coordination of a subject could enable clinicians to identify patterns that deviate from those of a reference population and to follow the progress of the subject after surgery or completing a rehabilitation program. In this work, we present two user-independent indices. First, a muscle-specific index (MFI) that quantifies the similarity of the activation pattern of a muscle of a specific subject with that of a reference population. Second, a global index (GFI) that provides a score of the overall activation of a muscle set. These two indices were tested on two groups of healthy and pathological children with encouraging results. Hence, the two indices will allow clinicians to assess the muscle activation, identifying muscles showing an abnormal activation pattern, and associate a functional score to every single muscle as well as to the entire muscle set. These opportunities could contribute to facilitating the diffusion of surface EMG analysis in clinics

Wearable Inertial Sensors to Assess Standing Balance: A Systematic Review

Wearable sensors are de facto revolutionizing the assessment of standing balance. The aim of this work is to review the state-of-the-art literature that adopts this new posturographic paradigm, i.e., to analyse human postural sway through inertial sensors directly worn on the subject body. After a systematic search on PubMed and Scopus databases, two raters evaluated the quality of 73 full-text articles, selecting 47 high-quality contributions. A good inter-rater reliability was obtained (Cohen’s kappa = 0.79). This selection of papers was used to summarize the available knowledge on the types of sensors used and their positioning, the data acquisition protocols and the main applications in this field (e.g., “active aging”, biofeedback-based rehabilitation for fall prevention, and the management of Parkinson’s disease and other balance-related pathologies), as well as the most adopted outcome measures. A critical discussion on the validation of wearable systems against gold standards is also presented