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.
In the last years, several studies have been focused on understanding how the central nervous system controls muscles to perform a specific motor task. Although it still remains an open question, muscle synergies have come to be an appealing theory to explain the modular organization of the central nervous system. Even though the neural encoding of muscle synergies remains controversial, a large number of papers demonstrated that muscle synergies are robust across different tested conditions, which are within a day, between days, within a single subject, and between subjects that have similar demographic characteristics. Thus, muscle synergy theory has been largely used in several research fields, such as clinics, robotics, and sports. The present systematical review aims at providing an overview on the applications of muscle synergy theory in clinics, robotics, and sports; in particular, the review is focused on the papers that provide tangible information for (i) diagnosis or pathology assessment in clinics, (ii) robot-control design in robotics, and (iii) athletes' performance assessment or training guidelines in sports.
The muscle synergy theory has been widely used to assess the modular organization of the central nervous system (CNS) during human locomotion. The pre-processing approach applied to the surface electromyographic (sEMG) signals influences the extraction of muscle synergies. The aim of this contribution is to assess the improvements in muscle synergy extraction obtained by using an innovative pre-processing approach. We evaluate the improvement in terms of the possible variation in the number of muscle synergies, of the intra-subject consistency, of the robustness, and of the interpretability of the results. The pre-processing approach presented in this paper is based on the extraction of the muscle principal activations (muscle activations strictly necessary to accomplish a specific biomechanical task) from the original sEMG signals, to then obtain muscle synergies using principal activations only. The results herein presented show that the application of this novel approach for the extraction of the muscle synergies provides a more robust and easily interpretable description of the modular organization of the CNS with respect to the standard preprocessing approach. Figure 4. Average (± SE) values of the three parameters computed to compare the standard approach (Standard) and the novel approach (PAs): (A) represents the values of the intra-subject consistency of the weight vectors and the activation coefficients across different subgroup of 10-gait-cycles, (B) shows the vaules of the muscle synergy robustness and (C) the values of the muscle synergy interpretability.This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.The final version of record is available at http://dx.
Minimal residual disease (MRD) analysis is a known predictive tool in mantle cell lymphoma (MCL). We describe MRD results from the Fondazione Italiana Linfomi phase III MCL0208 prospective clinical trial assessing lenalidomide maintenance vs observation after autologous transplantation (ASCT), in the first prospective comprehensive analysis of different techniques, molecular markers, and tissues (peripheral blood, PB, and bone marrow, BM), taken at well-defined timepoints. Among the 300 patients enrolled, a molecular marker was identified in 250 (83%), allowing us to analyze 234 patients and 4351 analytical findings from 10 timepoints. ASCT induced high rates of molecular remission (91% in PB and 83% in BM, by quantitative real-time PCR [RQ-PCR]). Nevertheless, the number of patients with persistent clinical and molecular remission decreased over time in both arms (up to 30% after 36 months). MRD predicted early progression and long-term outcome, particularly from 6 months after ASCT (6-month TTP HR 3.83, p<0.001). In single-timepoint analysis, BM outperformed PB, and RQ-PCR was more reliable, while nested PCR appeared applicable to a larger number of patients (234 vs 176). To improve MRD performance we developed a time-varying kinetic model, based on regularly updated MRD results and the Mantle Cell Lymphoma International Prognostic Index, showing an area under the ROC curve (AUROC) of up to 0.87 using BM. Most notably, PB reached an AUROC of up to 0.81: with kinetic analysis it was comparable to BM in performance. MRD is a powerful predictor over the entire natural history of MCL and suitable for models with continuous adaptation of patient risk. Study can be found in EudraCT N. 2009-012807-25 https://eudract.ema.europa.eu/
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