The pandemic of COVID-19 is continuously spreading, becoming a worldwide emergency. Early and fast identification of subjects with a current or past infection must be achieved to slow down the epidemiological widening. Here we report a Raman-based approach for the analysis of saliva, able to significantly discriminate the signal of patients with a current infection by COVID-19 from healthy subjects and/or subjects with a past infection. Our results demonstrated the differences in saliva biochemical composition of the three experimental groups, with modifications grouped in specific attributable spectral regions. The Raman-based classification model was able to discriminate the signal collected from COVID-19 patients with accuracy, precision, sensitivity and specificity of more than 95%. In order to translate this discrimination from the signal-level to the patient-level, we developed a Deep Learning model obtaining accuracy in the range 89–92%. These findings have implications for the creation of a potential Raman-based diagnostic tool, using saliva as minimal invasive and highly informative biofluid, demonstrating the efficacy of the classification model.

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Background The aim of this study was to synthesize evidence from systematic reviews, to summarise the effects of rehabilitation interventions for improving balance in stroke survivors. Methods We conducted an overview of systematic reviews (SRs). We included Cochrane Systematic Reviews and non-Cochrane Systematic Reviews of randomized-controlled clinical trials and not-randomized clinical trials, in all types of stroke, comparing the effects of interventions, control interventions and no interventions on balance-related outcomes. We conducted a comprehensive search of electronic databases, from inception to December 2017. Data extracted included: number and type of participants, type of intervention, control intervention, method of assessing risk of bias of primary studies, balance outcome measures and results of statistical meta-analyses. Methodological quality of included reviews was assessed using AMSTAR 2. A narrative description of the characteristics of the SRs was provided and results of meta-analyses summarised with reference to their methodological quality. Results 51 SRs (248 primary studies and 10,638 participants) met the inclusion criteria and were included in the overview. All participants were adults with stroke. A wide variety of different balance and postural control outcomes were included. 61% of SRs focussed on the effectiveness of physical therapy, 20% virtual reality, 6% electromechanical devices, 4% Tai-Chi, whole body vibration and circuit training intervention, and 2% cognitive rehabilitation. The methodology of 54% of SRs were judged to be of a “low or critically low” quality, 23% “moderate” quality and 22% “high” quality. Conclusions There are 51 SRs of evidence relating to the effectiveness of interventions to improve balance in people with stroke, but the majority of these are of poor methodological quality, limiting our ability to draw clear implications. Only 22% of these SRs were judged to be of high quality, highlighting the need to address important methodological issues within rehabilitation research.

Wearable devices are used in rehabilitation to provide biofeedback about biomechanical or physiological body parameters to improve outcomes in people with neurological diseases. This is a promising approach that influences motor learning and patients’ engagement. Nevertheless, it is not yet clear what the most commonly used sensor configurations are, and it is also not clear which biofeedback components are used for which pathology. To explore these aspects and estimate the effectiveness of wearable device biofeedback rehabilitation on balance and gait, we conducted a systematic review by electronic search on MEDLINE, PubMed, Web of Science, PEDro, and the Cochrane CENTRAL from inception to January 2020. Nineteen randomized controlled trials were included (Parkinson’s n = 6; stroke n = 13; mild cognitive impairment n = 1). Wearable devices mostly provided real-time biofeedback during exercise, using biomechanical sensors and a positive reinforcement feedback strategy through auditory or visual modes. Some notable points that could be improved were identified in the included studies; these were helpful in providing practical design rules to maximize the prospective of wearable device biofeedback rehabilitation. Due to the current quality of the literature, it was not possible to achieve firm conclusions about the effectiveness of wearable device biofeedback rehabilitation. However, wearable device biofeedback rehabilitation seems to provide positive effects on dynamic balance and gait for PwND, but higher-quality RCTs with larger sample sizes are needed for stronger conclusions.

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BACKGROUND: The term "rehabilitation" is heterogeneously used in the health context. Different interpretations can lead to disagreements, misunderstandings and different interpretations of what rehabilitation is between who provides it, who receives it and who studies it. The aim of this study was to conduct a terminological analysis of the different rehabilitation definitions used by different audiences: consumers, rehabilitation stakeholders and researchers. METHODS: We performed a terminological analysis with comparison of three different collections of rehabilitation definitions in English language. We performed: systematic reviews of databases representing consumers and lay persons (Google) and researchers (Cochrane Systematic Reviews [CSRs]), and a survey of rehabilitation stakeholders (Cochrane Rehabilitation Advisory Board). To aggregate words that had the same underlying concepts, their roots were extracted, and their occurrences counted. The 30 most frequent roots of each search were included. The 3 obtained collections were compared and similarities calculated. An overall collection of the most important 30 roots was obtained weighting those obtained in each single collection. All analyses have been performed using Excel. RESULTS: One hundred and eighty-seven rehabilitation definitions were identified: 23 from CSRs, 36 from the survey and 128 from Google. The most frequent roots were "function*" (92%), followed by "proces*" (69‰), "health*" (59‰), "disab*" (53‰), and "person*" (50‰). The most common relevant roots related to rehabilitation concept were "proces*" (73‰) in Google, "function*" (109‰) in the survey and "disab*" (41‰) in CSRs. The noun "function" prevailed in Google and "functioning" in the survey. CONCLUSIONS: According to our findings, any definition of rehabilitation for research purposes should include the identified terms, focusing on the concept of process and considering the main elements of functioning (and function), disability, person, health, optimization and environment.

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