This study explores the use of machine learning models to assess the severity of Parkinson’s disease symptoms based on data from wearable and smartphone sensors. It presents models to predict the severities of individual symptoms—tremor, bradykinesia, stiffness, and dyskinesia—as well as the overall state of patients, using both clinician and patient self-assessments as labels. The dataset, although limited and imbalanced, enabled the identification of key trends. The best performance was achieved when combining data from both the MYO armband and smartphone, and when using patient self-assessments as targets. Tremor was the most predictable symptom, while others proved more challenging—especially at higher severity levels, which were poorly represented in the dataset. These results highlight the value of multimodal data and the importance of patient input in symptom monitoring. However, they also point to the need for more balanced and extensive datasets to improve prediction accuracy across all severity levels and symptoms.

Dystonia-myoclonus syndrome is a rare neurological condition characterized by involuntary muscle contractions and myoclonic jerks, significantly impairing daily functioning. Pharmacological management is often ineffective, prompting consideration of alternative therapeutic interventions such as deep brain stimulation (DBS). This report describes a novel clinical case involving a 38-year-old female with severe dystonic and myoclonic symptoms associated with a pathogenic mutation in the KCNN2 gene (DYT34). Bilateral DBS targeting the internal segment of the globus pallidus (GPi) resulted in marked and sustained symptom improvement, notably reducing dystonic posturing and myoclonic movements over the 24-month follow-up period. Neuropsychological and neurologopedic assessments revealed no adverse effects on cognition or speech. This represents the first sufficient effect of GPi-DBS in a patient with a genetically confirmed KCNN2 mutation, highlighting its potential efficacy and underscoring the need for genetic testing in patients presenting with dystonia-myoclonus syndromes.

BackgroundAutism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by deficits in social communication and restricted, repetitive behaviors. Its growing prevalence and functional burden have increased interest in non-pharmacological interventions, particularly physical activity and sport-based programs, as potential strategies to improve physical and neurobehavioral outcomes in pediatric populations. AimThis narrative review aimed to summarize current evidence on the effects of physical activity and exercise interventions on motor, cognitive, behavioral, and psychosocial outcomes in children and adolescents with ASD. Material and methodsA narrative literature review was conducted using peer-reviewed studies on exercise-based interventions in pediatric ASD populations. Included were systematic reviews, meta-analyses, randomized controlled trials, and experimental studies assessing outcomes such as motor skills, executive functioning, social interaction, sleep, and behavioral regulation. ResultsEvidence indicates that structured physical activity may positively affect multiple domains in children with ASD. Exercise interventions were associated with improvements in motor skills, executive functions, and social abilities, along with reductions in behavioral problems and anxiety. Some studies also reported improved sleep and overall well-being. However, significant heterogeneity in intervention types, duration, and outcome measures was noted. ConclusionsPhysical activity is a valuable complementary element of multidisciplinary ASD management, supporting both physical health and neurobehavioral functioning. Further well-designed studies with standardized protocols and long-term follow-up are needed to determine optimal intervention strategies and their sustained effects.

Background/Objectives: MR-guided focused ultrasound (MRgFUS) Vim thalamotomy targets medication-refractory tremor in essential tremor (ET) and tremor-dominant Parkinson’s disease (PD). We examined longitudinal patient-reported outcomes alongside early motor changes. Methods: This retrospective cohort included 30 patients (12 ET, 18 PD). PDQ-39, PDQ-8, and EQ-VAS were analyzed using random-intercept mixed models. Multiplicity correction covered 16 visit contrasts, including four contrasts for a secondary. A sensitivity analysis included 11 participants with confirmed pretreatment W1 dates and numeric patient-reported data. Results: The paired motor analysis showed a median 12-point TRS reduction and median individual tremor improvement of 64.7% (n = 23; p < 0.001). Median original UPDRS Part III reductions in PD were 5 points OFF (p = 0.010) and 9 points ON medication (p = 0.004). Patient-reported outcomes were available for 25, 21, and 10 participants at W1, W2, and W3. No categorical-visit contrast met the corrected significance threshold in either the full-cohort or restricted analysis. Conclusions: MRgFUS was followed by substantial early tremor reduction and PD motor-score reductions compatible with clinically meaningful improvement against external benchmarks. This post hoc interpretation provides clinical context for motor change; the patient-reported analyses did not establish a consistent or durable quality-of-life benefit. Safety outcomes were not evaluated in this study.