Background: The use of telemedicine has increased to address the ongoing healthcare needs of patients with movement disorders.Objective: We aimed to describe the technical and basic security features of the most popular telemedicine videoconferencing software.Methods: We conducted a systematic review of articles/websites about “Telemedicine,” “Cybersecurity,” and “Videoconferencing software.” Technical capabilities and basic security features were determined for each videoconferencing software.Results: Twenty-six videoconferencing software programs were reviewed, 13 (50.0%) were specifically designed for general healthcare, and 6/26 (23.0%) were compliant with European and US regulations. Overall technical and security information were found in 5/26 software (19.2%), including Microsoft Teams, Google Hangout, Coviu, Doxy.me, and Thera platforms.Conclusions: Detailed information about technical capabilities and data security of videoconferencing tools is not easily and openly retrievable. Our data serves as a guide for practitioners seeking to understand what features should be examined when choosing software and what options are available.

Background Gait abnormalities are a hallmark of Parkinson's disease and contribute to falling risk. As disease symptoms progress, assistive devices are often prescribed. However, there are no guidelines for choosing appropriate ambulatory devices for gait impairment. Objective To review the scientific evidence on assistive devices for gait impairment in Parkinson's disease. Methods We performed a systematic literature review for articles relating to parkinsonian gait impairment and assistive devices. We assessed the studies’ methodological quality and risk of bias using the PEDro scale. Results Seventeen articles were reviewed. Four articles (23.53%) showed that canes and standard and two‐wheeled walkers without visual cues decreased gait speed and stride length, with no significant effects on freezing of gait or falls. Instead, improvements were observed with the use of visual [seven articles (41.18%)] and auditory cues [three articles (17.65%)], including decreased number of freezing episodes and increased stride length. Conclusions Although assistive devices seem to improve confidence, there is still limited information about the efficacy of assistive devices on gait parameters and functional disability in Parkinson's disease. Further, longitudinal, multicenter, randomized, blinded, and controlled studies using assistive devices in a free‐living context are required to provide the best scientific evidence

Background Skeletal muscle loss has been associated with declining physical performance and a negative prognostic effect on falls, disability, and mortality risk in Parkinson's disease. Objectives We aimed to analyze the clinical correlates associated with skeletal muscle wasting in Parkinson's disease. Methods This was a cross‐sectional, case–control, observational study. We collected information on dietary intake with a 24‐hour recall questionnaire, body composition with bioelectrical impedance, motor severity with the Unified Parkinson's disease Rating Scale, and physical activity with the Global Physical Activity Questionnaire. We used multivariate linear regression analysis to analyze the sociodemographic and clinical correlates associated with skeletal muscle loss after adjusting for confounding variables. Results Forty‐three patients with Parkinson's disease and 21 matched family members were included. Patients and family members had similar body composition, anthropometrics, and nutritional parameters. Advanced patients had similar nutrient intakes compared to patients with mild‐to‐moderate Parkinson's disease. In the multivariate linear regression analysis, female patients with low physical activity and low energy intake were more likely to have skeletal muscle loss. Conclusions Skeletal muscle wasting is a complex multifactorial problem. Dietary strategies and physical exercise should be recommended, especially to females with Parkinson's disease, to prevent significant skeletal muscle wasting.

Background Approximately 40–70% of people with Parkinson’s disease (PD) fall each year, causing decreased activity levels and quality of life. Current fall-prevention strategies include the use of pharmacological and non-pharmacological therapies. To increase the accessibility of this vulnerable population, we developed a multidisciplinary telemedicine program using an Information and Communication Technology (ICT) platform. We hypothesized that the risk for falling in PD would decrease among participants receiving a multidisciplinary telemedicine intervention program added to standard office-based neurological care. Objective To determine the feasibility and cost-effectiveness of a multidisciplinary telemedicine intervention to decrease the incidence of falls in patients with PD. Methods Ongoing, longitudinal, randomized, single-blinded, case-control, clinical trial. We will include 76 non-demented patients with idiopathic PD with a high risk of falling and limited access to multidisciplinary care. The intervention group (n = 38) will receive multidisciplinary remote care in addition to standard medical care, and the control group (n = 38) standard medical care only. Nutrition, sarcopenia and frailty status, motor, non-motor symptoms, health-related quality of life, caregiver burden, falls, balance and gait disturbances, direct and non-medical costs will be assessed using validated rating scales. Results This study will provide a cost-effectiveness assessment of multidisciplinary telemedicine intervention for fall reduction in PD, in addition to standard neurological medical care. Conclusion In this challenging initiative, we will determine whether a multidisciplinary telemedicine intervention program can reduce falls, as an alternative intervention option for PD patients with restricted access to multidisciplinary care. Trial registration ClinicalTrials.gov Identifier: NCT04694443.

Background The Movement Disorder Society‐sponsored Non‐motor Rating Scale (MDS‐NMS) assess the severity and disability caused by non‐motor symptoms (NMS) in Parkinson's disease (PD). Objective This article encapsulates the formal process for completing this program and the data on the first officially approved non‐English version of the MDS‐NMS (Spanish). Methods The MDS‐NMS translation program involves four steps: translation and back‐translation; cognitive pre‐testing to ensure that raters and patients understand the scale and are comfortable with its content; field testing of the finalized version; analysis of the factor structure of the tested version against the original English language version for the nine domains that could be analyzed in a confirmatory factor analysis. To be designated an “Official MDS translation,” the confirmatory factor analysis Comparative Fit Index had to be ≥0.90. Results The Spanish MDS‐NMS was tested in 364 native‐Spanish‐speaking patients with PD from seven countries. For all subjects with fully computable data with all domains of the MDS‐NMS (n = 349), the Comparative Fit Index was ≥0.90 for the nine eligible domains. Missing data were negligible and moderate floor effect (42.90%) was found for the Non‐Motor Fluctuations subscale. Item homogeneity coefficient was adequate, and the correlation of the MDS‐NMS domains with other measures for related constructs was acceptable (rs ≥ 0.50). Conclusions The Spanish version of the MDS‐NMS followed the IPMDS Translation Program protocol, reached the criterion to be designated as an Official Translation, and is now available on the MDS website.

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Introduction: Huntington’s disease (HD) is an autosomal dominant neurodegenerative disorder characterized by motor dysfunction, cognitive impairment, and psychiatric disorders. These symptoms cause functional limitations in occupational performance. This study aimed to describe the difficulties in self-care, productivity, and leisure activities and to analyze the patients’ own perception and satisfaction and the association with sex, age, disability, HD severity, and quality of life. Method: We conducted an observational, retrospective study in 38 patients with HD without cognitive impairment at the Burgos University Hospital. We assessed occupational performance, quality of life, and HD severity with the Canadian Occupational Performance Measure, Short-Form Health Survey 12, Unified Huntington’s Disease Rating Scale, Total Functional Capacity, and the Problems Behavior Assessment. Results: One hundred sixty-five occupations (median 4, range 2–7) were categorized as self-care (50.90%), leisure (30.30%), and productivity (18.79%). Patients reported a higher degree of satisfaction with the activities prioritized than with the degree of performance. Elderly HD patients reported more satisfaction in leisure and women in self-care. Self-ratings of satisfaction in productivity were associated with higher levels of mental wellbeing. Conclusions: HD patients have problems with their daily life occupations, particularly with self-care. This underlines the need for assessment tools that capture the complexity of occupations.

The consolidation of telerehabilitation for the treatment of many diseases over the last decades is a consequence of its cost-effective results and its ability to offer access to rehabilitation in remote areas. Telerehabilitation operates over a distance, so vulnerable patients are never exposed to unnecessary risks. Despite its low cost, the need for a professional to assess therapeutic exercises and proper corporal movements online should also be mentioned. The focus of this paper is on a telerehabilitation system for patients suffering from Parkinson’s disease in remote villages and other less accessible locations. A full-stack is presented using big data frameworks that facilitate communication between the patient and the occupational therapist, the recording of each session, and real-time skeleton identification using artificial intelligence techniques. Big data technologies are used to process the numerous videos that are generated during the course of treating simultaneous patients. Moreover, the skeleton of each patient can be estimated using deep neural networks for automated evaluation of corporal exercises, which is of immense help to the therapists in charge of the treatment programs.