Dizziness can be a debilitating condition with various causes, with at least one episode reported in 17% to 30% of the international adult population. Given the effectiveness of rehabilitation in treating dizziness and the recent advancements in telerehabilitation, this systematic review aims to investigate the effectiveness of telerehabilitation in the treatment of this disorder. The search, conducted across Medline, Cochrane Central Register of Controlled Trials, and PEDro databases, included randomized controlled trials assessing the efficacy of telerehabilitation interventions, delivered synchronously, asynchronously, or via tele-support/monitoring. Primary outcomes focused on dizziness frequency/severity and disability, with secondary outcomes assessing anxiety and depression measures. Seven articles met the eligibility criteria, whereas five articles contributed to the meta-analysis. Significant findings were observed regarding the frequency and severity of dizziness (mean difference of 3.01, p < 0.001), disability (mean difference of −4.25, p < 0.001), and anxiety (standardized mean difference of −0.16, p = 0.02), favoring telerehabilitation. Telerehabilitation shows promise as a treatment for dizziness, aligning with the positive outcomes seen in traditional rehabilitation studies. However, the effectiveness of different telerehabilitation approaches requires further investigation, given the moderate methodological quality and the varied nature of existing methods and programs.

Background and Objectives: Driven by the rising demand for telerehabilitation (TR) services and digital transformations in the healthcare management of people with facial palsy (FP), studies on TR programs in this specific population are steadily increasing. Our scoping review aimed to provide an overview of the current state of knowledge on TR for people with FP by addressing three subquestions regarding the types of studies conducted, the technologies used, and the potential existing technologies that could be adapted for TR in this context. Study Design and Methods: We followed the Joanna Briggs Institute methodology for scoping reviews. Between January and February 2024, two authors performed a literature search on Medline, Cochrane, PEDro, and Scopus databases, while two additional authors conducted a gray literature search using the “Grey Matters” tool, repositories, and Google. Results: A total of 10,804 reports were initially considered in this scoping review. After the screening process, we included and analyzed 39 results. We found 18 studies with 11 different study designs or types related to TR in FP, 14 technologies projected or already used for TR purposes with a variety of delivery methods or rehabilitative treatments, and 18 additional digital instruments suitable for different TR stages. Conclusions: Our findings indicate a growing interest in and development of TR instruments, aligning with the broader expansion of telemedicine services across healthcare. We have identified a diverse range of delivery methods, rehabilitative treatments, and digital tools utilized in TR for FP. Additionally, our comprehensive overview provides healthcare providers with practical insights to improve their approach to managing patients with FP in TR contexts.

Motor recovery after stroke is highly variable and closely linked to the extent of corticospinal tract (CST) damage. Neurophysiological biomarkers, such as motor evoked potentials (MEPs) and structural imaging markers, including CST lesion load and fractional anisotropy (FA), show promise for predicting motor outcomes. This scoping review evaluated the prognostic value of these biomarkers and the utility of multimodal models for individualized rehabilitation. A systematic search (April 2024) in PubMed, the Cochrane Library, and Scopus identified empirical studies examining biomarkers predictive of post-stroke motor recovery. Biomarkers were primarily derived from magnetic resonance imaging (resting-state functional connectivity and diffusion-weighted imaging) and transcranial magnetic stimulation. Nineteen studies (1219 patients) met the inclusion criteria. Structural biomarkers, particularly lower CST FA and higher weighted lesion load, were generally associated with poorer motor recovery. Combining neurophysiological measures, such as MEP status, with functional imaging and artificial intelligence-based analyses may improve prognostic precision. Multimodal approaches appeared promising in some studies, but evidence remains limited and heterogeneous. Integrating diverse biomarkers into multimodal prognostic models may enhance the prediction of motor recovery and support personalized rehabilitation after stroke, although heterogeneity in study design and outcome assessment highlights the need for standardized, large-scale longitudinal studies to enable clinical implementation.