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BACKGROUND: Diabetic neuropathy is one of the most common complications of diabetes mellitus. The aim of this study is to evaluate the Moveo device, a novel device that uses a machine learning (ML) algorithm to detect and track diabetic neuropathy. The Moveo device comprises 4 sensors positioned on the back of the hands and feet accompanied by a mobile application that gathers data and ML algorithms that are hosted on a cloud platform. The sensors measure movement signals, which are then transferred to the cloud through the mobile application. The cloud triggers a pipeline for feature extraction and subsequently feeds the ML model with these extracted features. METHODS: The pilot study included 23 participants. Eleven patients with diabetes and suspected diabetic neuropathy were included in the experimental group. In the control group, 8 patients had suspected radiculopathy, and 4 participants were healthy. All participants underwent an electrodiagnostic examination (EDx) and a Moveo examination, which consists of sensors placed on the feet and back of the participant's hands and use of the mobile application. The participant performs six tests that are part of a standard neurological examination, and a ML algorithm calculates the probability of diabetic neuropathy. A user experience questionnaire was used to compare participant experiences with regard to both methods. RESULTS: The total accuracy of the algorithm is 82.1%, with 78% sensitivity and 87% specificity. A high linear correlation up to 0.722 was observed between Moveo and EDx features, which underpins the model's adequacy. The user experience questionnaire revealed that the majority of patients preferred the less painful method. CONCLUSIONS: Moveo represents an accurate, easy-to-use device suitable for home environments, showing promising results and potential for future usage.

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Objectives: This study aimed to investigate the efficacy of glucosamine-sulfate (GS), nonanimal chondroitin-sulfate (naCS), and S-adenosylmethionine (SAMe) combination on ultrasound findings, inflammation, pain, and functionality in knee osteoarthritis. Patients and methods: In the prospective, randomized, double-blind, placebo-controlled pilot study conducted between August 2019 and November 2019, 120 participants (28 males, 92 females; mean age: 66.4±7.9 years; range, 42.4 to 74.5 years) were randomized at a 1:1:1 ratio to the placebo group, the first experimental group (a combination of GS, naCS, and SAMe was administered to the experimental groups. The first experimental group received 375 mg of GS, 300 mg of naCS, and 100 mg of SAMe, whereas the second experimental group received 750 mg of GS, 600 mg of naCS, and 200 mg of SAMe). Laboratory (erythrocyte sedimentation rate, C-reactive protein, tumor necrosis factor alpha, interleukin [IL]-1ß, IL-6, IL-17), clinical (Visual Analog Scale [VAS], short form health survey [SF-36], the Western Ontario and McMaster Universities Arthritis Index [WOMAC], and the Tegner Lysholm Knee Scoring Scale [TLKS]), and musculoskeletal ultrasound (MSUS) assessments were performed at baseline and after three and six months. Results: A minor increase was observed in the second experimental group after six months using ultrasonography to evaluate articular cartilage thickness (p<0.05). The investigational product's superiority in reducing osteoarthritis ultrasonographic findings was not proven. A moderately negative association was found between cartilage thickness and VAS scores at baseline (ρ=-0.36, p<0.01), while the presence of massive osteophytes on MSUS showed a low to moderate association with all clinical outcomes. There was no difference in the delta changes between groups for the VAS, TLKS, WOMAC, and SF-36. The only serum inflammatory marker outside the reference range was IL-1ß, but no significant changes were observed after six months. Conclusion: According to the results of our investigation, treatment for knee osteoarthritis should be evaluated using more objective outcomes. The most important conclusion of our study is that IP may result in a slight increase in articular cartilage thickness, which was associated with a decrease in pain intensity at baseline. Clarification of the potential influence of this combination on radiographic progression and laboratory markers of inflammation requires further exploration.

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BACKGROUND: The aim of the study was to assess gait pattern of patients diagnosed with fibromyalgia (FM) while performing demanding motor and/or cognitive dual tasks while walking. Further, idea was to explore possible correlations of dual task gait pattern alterations to patients' functional status and presence or absence of clinical symptoms associated with FM. METHODS: Twenty-four female FM patients and 24 healthy female subjects performed a basic walking task, a dual motor, a dual mental (cognitive) and a combined, dual motor and cognitive task simultaneously. Quantitative spatial (stride length) and temporal (cycle time, swing time and double support time) gait parameters were measured using GAITRite walkway system and their variability was assessed. Patients underwent clinical examination including assessment of functional status, pain and fatigue level, psychiatric and cognitive manifestations. RESULTS: The motor, cognitive and combined dual tasks affect gait performance in FM patients. Difference in tasks between FM and healthy subjects was found as double support time prolongation. Comparison of tasks showing that cycle time in FM was longer than controls and stride length was shorter in patients for all conditions, while no changes were found in any of the gait parameters variability. Further, mental/cognitive dual tasks had a larger effect than motor tasks. Correlations were also found between depression and functional status of the patients and the gait parameters. CONCLUSIONS: Gait is affected in FM patients while dual task walking. No changes in stride-to-stride variability point that patients preserve stability in complex walking situations. Analysis of gait may provide additional information for the FM identification based on presence of clinical features and cognitive status. Correlation of dual task gait alterations with occurrence of clinical symptoms and influence of cognitive changes on gait pattern could additionally define FM subgroups.

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