Search Results (646)

The efficacy of botulinum toxin A (BoNT) in alleviating motor symptoms of cervical dystonia (CD) has been well established, and it is the treatment of choice in this disease. Lately, the effect of BoNT on non-motor symptoms (NMS) such as cognitive function, depression, anxiety, pain, and sleep disturbance has been observed in patients with CD. A comprehensive clinical and functional assessment of motor (dystonia severity, gait) and non-motor symptoms (cognitive functions, depression, anxiety, sleep, and pain) has been performed in a total of 34 adult patients with cervical dystonia before and after BoNT treatment. Results have also been compared to a control group. Significant improvements in the scales assessing dystonia severity have been observed, which is in line with previous studies on the effect of BoNT on motor symptoms in dystonia. Interestingly, the results also clearly indicate that BoNT has a positive effect on NMS. Among the studied non-motor domains, depression and cognitive functions improved the most after the treatment procedure. The study highlights the potential of BoNT to positively influence non-motor symptoms in patients with cervical dystonia, although its effect on various NMS is not equal. Full article

Shaken Baby Syndrome (SBS) is one of the primary causes of fatal head trauma in infants and young children, occurring in about 33 per 100,000 infants annually in the U.S., with mortality rates being between 15% and 38%. Survivors frequently endure long-term disabilities, such as cognitive deficits, visual impairments, and motor dysfunction. Diagnosing SBS remains difficult due to the lack of visible injuries and delayed symptom onset. Existing detection methods—such as neuroimaging, biomechanical modeling, and infant monitoring systems—cannot perform real-time detection and face ethical, technical, and accuracy limitations. This study proposes an inertial measurement unit (IMU)-based detection system enhanced with machine learning to identify aggressive shaking patterns. Findings indicate that wearable-based motion analysis is a promising method for recognizing high-risk shaking, offering a non-invasive, real-time solution that could minimize infant harm and support timely intervention. Full article

Ulcerative colitis is a chronic intestinal disorder that belongs to the category of inflammatory bowel diseases, and is usually characterized by the presence of bloody diarrhea and abdominal pain, due to an accelerated transit and intestinal sensibilization following inflammation of the colonic mucosa. However, the literature reports that ulcerative colitis may sometimes feature fecal stasis with constipation. This apparent paradox may be partially explained by the motor abnormalities of the large bowel following inflammation, damage to the enteric innervation, and the onset of parietal fibrosis over time. Moreover, some anorectal abnormalities such pelvic floor dyssynergia may explain the symptoms of constipation reported in subsets of patients. Since these abnormalities may be responsible for diagnostic delays and non- or partial responses to therapy, it is important to recognize them as early as possible to avoid incorrect clinical and therapeutic approaches to these patients. Full article

Background/Objectives: Dystonia, traditionally regarded as a purely motor disorder, is now increasingly recognized as involving clinically significant non-motor symptoms (NMSs) that can adversely affect patients’ health-related quality of life (HRQoL). This study aimed to assess HRQoL in Romanian patients with isolated dystonia and to evaluate the impact of two key NMSs, depression and cognitive impairment, on their HRQoL. We hypothesized that depression would have a greater adverse effect on HRQoL than cognitive impairment. Methods: A cross-sectional study was conducted involving 65 adult Romanian patients with isolated dystonia. HRQoL was measured using the Short Form-36 Health Survey (SF-36), including the physical component summary (PCS) and mental component summary (MCS). Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), and cognitive impairment was assessed using the Montreal Cognitive Assessment (MoCA). Descriptive statistics, correlation analysis, and parametric and non-parametric tests were used. Multiple regression analysis was employed to evaluate associations between NMS and HRQoL. Results: The mean (SD) age was 56.6 (14.3) years, and 80% of participants were female. Depression and cognitive function were significantly associated with PCS (0.33 and −0.51, respectively) and MCS (0.26 and −0.78, respectively). Multiple regression analysis showed that the two NMS explained 38% of the variance in PCS and 58% of the variance in MCS. Depression had a greater impact on PCS and MCS than cognitive impairment (−0.47 vs. 0.33 and −0.72 vs. 0.16, respectively). Cognitive impairment (MoCA < 26) was present in 35.4% of patients, while 46.2% had at least mild depressive symptoms (PHQ-9 ≥ 5); 23.1% met criteria for moderate-to-severe depression (PHQ-9 ≥ 10). Depressive symptoms showed strong negative correlations with all SF-36 domains, while cognitive performance correlated modestly. Conclusions: Both depression and cognitive impairment have a significant negative impact on HRQoL in dystonia, with depression having a stronger effect, as we hypothesized. Routine screening for non-motor symptoms is essential to support better clinical outcomes and enhance patients’ quality of life. Full article

Background/Objectives: Parkinson’s disease (PD) is a neurodegenerative disorder that impairs mobility. Treadmill training (TT) is a common rehabilitation strategy for improving gait parameters in individuals with PD. This systematic review evaluated the effectiveness of TT in improving motor function, walking ability, and overall functional mobility in PD patients. Methods: We compared TT to other forms of gait and motor rehabilitation, including conventional and robotic gait training. Trials that compared a treadmill training group with a non-intervention group were excluded from this review. We searched multiple databases for RCTs involving Parkinson’s patients until January 2025. The primary outcomes were motor function (UPDRS-III) and walking ability (6 MWT and TUG test). Results: We identified 285 articles; 199 were excluded after screening. We assessed the full text of 86 articles for eligibility, and 13 RCTs met the inclusion criteria. Some of them were included in the meta-analysis. The TT group showed a significant improvement in UPDRS-III scores [mean difference (MD): −1.36 (95% CI: −2.60 to −0.11)] and greater improvement in TUG performance [MD, −1.75 (95% CI: −2.69 to −0.81)]. No significant difference in walking capacity as assessed through the 6 MWT was observed [MD: 26.03 (95% CI: −6.72 to 58.77). Conclusions: The current study suggests that TT is effective in improving the motor symptoms and functional mobility associated with PD. Further studies are needed to develop protocols that consider the patients’ clinical characteristics, disease stage, exercise tolerance, and respiratory function. Full article

Background: Epidemiological studies have reported an inverse association between smoking and Parkinson’s disease (PD) risk, prompting interest in nicotine as a potential therapeutic agent. The present meta-analysis evaluated the efficacy of nicotine therapy in improving motor symptoms and activities of daily living in patients with PD. Methods: PubMed, Embase, and Cochrane Library were systematically searched to identify randomized controlled trials (RCTs) assessing nicotine therapy in PD. Clinical RCTs administering interventions extending beyond 1 week and reporting motor or nonmotor outcomes were included. Random-effects models were used to analyze short-term (<6 months) and long-term (≥6 months) outcomes by using standardized mean differences (SMDs). Results: This meta-analysis included five RCTs (346 participants). Nicotine therapy led to no significant improvement in motor outcomes in the short term (pooled SMD: −0.452, 95% confidence interval: −1.612 to 0.708) or long term (pooled SMD: 0.174, 95% confidence interval: −0.438 to 0.787). Considerable interstudy heterogeneity was noted. Furthermore, short-term nicotine therapy resulted in no significant improvement in daily functioning, cognition, or quality of life. Conclusions: This meta-analysis revealed a lack of compelling evidence suggesting that nicotine-based therapies improve motor or nonmotor outcomes in PD. The findings highlight a disconnect between epidemiological associations and clinical efficacy. Given the prodromal nature of PD pathology and the challenges of early diagnosis, future preventive strategies should be implemented before symptom onset in high-risk individuals identified using advanced biomarker panels. Full article

Parkinson’s disease (PD) is a progressive neurological disorder with motor and non-motor symptoms that are inadequately addressed by current pharmacological and surgical therapies. Brain–computer interfaces (BCIs), particularly those based on electroencephalography (eBCIs), provide a promising, non-invasive approach to personalized neurorehabilitation. This narrative review explores the clinical potential of BCIs in PD, discussing signal acquisition, processing, and control paradigms. eBCIs are well-suited for PD due to their portability, safety, and real-time feedback capabilities. Emerging neurophysiological biomarkers—such as beta-band synchrony, phase–amplitude coupling, and altered alpha-band activity—may support adaptive therapies, including adaptive deep brain stimulation (aDBS), as well as motor and cognitive interventions. BCIs may also aid in diagnosis and personalized treatment by detecting these cortical and subcortical patterns associated with motor and cognitive dysfunction in PD. A structured search identified 11 studies involving 64 patients with PD who used BCIs for aDBS, neurofeedback, and cognitive rehabilitation, showing improvements in motor function, cognition, and engagement. Clinical translation requires attention to electrode design and user-centered interfaces. Ethical issues, including data privacy and equitable access, remain critical challenges. As wearable technologies and artificial intelligence evolve, BCIs could shift PD care from intermittent interventions to continuous, brain-responsive therapy, potentially improving patients’ quality of life and autonomy. This review highlights BCIs as a transformative tool in PD management, although more robust clinical evidence is needed. Full article

In the wide range of human diseases, Parkinson’s disease (PD) has a high incidence, according to a recent survey by the World Health Organization (WHO). According to WHO records, this chronic disease has affected approximately 10 million people worldwide. Patients who do not receive an early diagnosis may develop an incurable neurological disorder. PD is a degenerative disorder of the brain, characterized by the impairment of the nigrostriatal system. A wide range of symptoms of motor and non-motor impairment accompanies this disorder. By using new technology, the PD is detected through speech signals of the PD victims by using the reduced instruction set computing 5th version (RISC-V) processor. The RISC-V microcontroller unit (MCU) was designed for the voice-controlled human-machine interface (HMI). With the help of signal processing and feature extraction methods, the digital signal is impaired by the impairment of the nigrostriatal system. These speech signals can be classified through classifier modules. A wide range of classifier modules are used to classify the speech signals as normal or abnormal to identify PD. We use Matrix Laboratory (MATLAB R2021a_v9.10.0.1602886) to analyze the data, develop algorithms, create modules, and develop the RISC-V processor for embedded implementation. Machine learning (ML) techniques are also used to extract features such as pitch, tremor, and Mel-frequency cepstral coefficients (MFCCs). Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the selective loss of dopaminergic neurons in the substantia nigra, resulting in motor symptoms such as bradykinesia, tremor, rigidity, and postural instability, as well as a wide variety of non-motor manifestations. Branched-chain amino acids (BCAAs)—leucine, isoleucine, and valine—are essential nutrients involved in neurotransmitter synthesis, energy metabolism, and cellular signaling. Emerging evidence suggests that BCAA metabolism is intricately linked to the pathophysiology of PD. Dysregulation of BCAA levels has been associated with energy metabolism, mitochondrial dysfunction, oxidative stress, neuroinflammation, and altered neurotransmission. Furthermore, the branched-chain ketoacid dehydrogenase kinase (BCKDK), a key regulator of BCAA catabolism, has been implicated in PD through its role in modulating neuronal energetics and redox homeostasis. In this review, we synthesize current molecular, genetic, microbiome, and clinical evidence on BCAA dysregulation in PD to provide an integrative perspective on the BCAA–PD axis and highlight directions for future translational research. We explored the dualistic role of BCAAs as both potential neuroprotective agents and metabolic stressors, and critically examined the therapeutic prospects and limitations of BCAA supplementation and BCKDK targeting. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that impairs motor function, including the fine motor control required for handwriting. Traditional diagnostic methods often lack sensitivity and objectivity in the early stages, limiting opportunities for timely intervention. There is a growing need for non-invasive, accessible tools capable of capturing subtle motor changes that precede overt clinical symptoms. Among early PD manifestations, handwriting impairments such as micrographia have shown potential as digital biomarkers. However, conventional handwriting analysis remains subjective and limited in scope. Recent advances in artificial intelligence (AI) and machine learning (ML) enable automated analysis of handwriting dynamics, such as pressure, velocity, and fluency, collected via digital tablets and smartpens. These tools support the detection of early-stage PD, monitoring of disease progression, and assessment of therapeutic response. This paper highlights how AI-enhanced handwriting analysis provides a scalable, non-invasive method to support diagnosis, enable remote symptom tracking, and personalize treatment strategies in PD. This approach integrates clinical neurology with computer science and rehabilitation, offering practical applications in telemedicine, digital health, and personalized medicine. By capturing dynamic features often missed by traditional assessments, AI-based handwriting analysis contributes to a paradigm shift in the early detection and long-term management of PD, with broad relevance across neurology, digital diagnostics, and public health innovation. Full article

Parkinson’s disease (PD) is the second most common neurodegenerative disorder in the world. PD is characterized by motor and non-motor symptoms, but the diagnosis primarily relies on the clinical assessment of postural and movement abnormalities, supported by imaging and genetic testing. It is widely accepted that the disease process begins decades before the onset of overt symptoms. Emerging evidence suggests that neuroinflammation plays a central role in the pathogenesis of PD, particularly during the pre-clinical phase. Activated microglia, increased levels of pro-inflammatory cytokines, and persistent oxidative stress have all been associated with the gradual loss of dopaminergic neurons. Although earlier detection and diagnosis remain elusive, achieving these goals is crucial for advancing prevention and disease-modifying strategies. Clinical studies are ongoing. To fill the gap, research models that recapitulate the chronic disease progression of PD are crucial to test preventive and disease-modifying strategies. This review briefly summarizes clinical knowledge on PD as a starting point for improving research models. Furthermore, we will critically evaluate how the existing models have been utilized and highlight opportunities to overcome their limitations and enhance the translational relevance to clinical application. Full article

Parkinson’s Disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor symptoms, including cognitive decline, mood disturbances, and sensory deficits. While dopaminergic treatments remain the gold standard, they present long-term side effects and limited impact on non-motor symptoms. Transcranial Pulse Stimulation (TPS) has emerged as a promising adjunct therapy in neurological and psychiatric conditions, but its effects in PD remain underexplored. This open-label, single-arm trial protocol involves 14 PD participants and outlines a personalized 12-session treatment approach combined with a homogeneously distributed TPS intervention among patients with PD. The approach addresses the subject’s most prominent symptoms, as identified through validated clinical assessments, encompassing domains related to both motor and non-motor symptoms. Over 2.5 months, besides the intervention sessions, the 14 participants will undergo an MRI brain scan, a baseline assessment, a post-treatment assessment, and a 1-month follow-up assessment. The study aims to determine whether personalized TPS is a feasible and safe intervention and whether it improves PD symptoms across multiple functional domains. This study represents the first structured attempt to evaluate a multimodal, personalized TPS intervention in patients with PD. It addresses gaps in current treatment approaches and may support the development of future strategies for integrated, symptom-targeted neuromodulation. Full article

Background: A growing body of evidence suggests that diet can modify Parkinson’s disease (PD) outcomes, although there is disagreement about what should be included and excluded in such a diet. Existing evidence suggests that adherence to the MIND and Mediterranean (MEDI) diets are associated with reduced PD symptoms, but only a few variables from the adherence scales are responsible for the statistically observed improvement. Objectives: The goal was to use patient-reported outcomes in a large cohort to identify the foods and dietary patterns (PRO diet) most strongly associated with the fewest PD symptoms over time, and to develop a composite adherence scale to enable comparisons between MEDI, MIND, and PRO. Methods: Data were obtained from the prospective longitudinal natural history study and from Modifiable Variables in Parkinsonism (MVP)—a study designed to identify behaviors associated with patient-reported outcomes (PRO-PD). Upon the completion of the binary and food frequency data collection, using various predictive models and considering congruence with historical data, the PRO diet was created via an iterative process. Our goal was to create a new scale and compare its performance to the existing MIND and MEDI scores. The comparison was made at baseline, using the regression models for PRO-PD and the different scales as the predictors. The models were compared via the Akaike Information Criterion (AIC). To examine whether baseline adherence levels predicted subsequent symptom trajectories, the baseline PRO diet adherence and subsequent slope of progression were evaluated. Results: Data from 2290 individuals with PD were available for this analysis. The Mediterranean and MIND diets showed almost identical effects. For both the diets, the effect they had on non-motor symptoms was about twice the effect on motor symptoms. The slopes for the total PRO-PD for MEDI, MIND, and PRO-21 were −64.20467, −64.04220, and −28.61995, respectively. The AIC value differences were substantial (>2), indicating meaningful improvements in the model fit for total PRO-PD, as follows: MEDI: 28,897.24, MIND: 28,793.08, and PRO-21: 27,500.71. The subset of individuals who were most adherent to the PRO-21 diet at baseline had the slowest subsequent progression, as measured by a 43% reduced PRO-PD slope, compared to the less adherent groups. Conclusions: The PRO-21 outperformed the MIND and MEDI diets in the model fit, overcoming the ceiling effects and showing orders of magnitude and superior explanatory power for variance in PD outcomes, despite the smaller per-unit effect sizes. However, its rigorous demands may introduce barriers related to cost, feasibility, and sustainability, underscoring the need for future intervention trials to assess real-world feasibility, adherence, side effects, and clinical impact. Full article

Background: Parkinson’s disease (PD) presents a significant challenge due to its wide range of motor, non-motor, and treatment-related symptoms. Non-invasive interventions like transcranial magnetic stimulation (TMS) are being explored for potential therapeutic benefits. This study aimed to assess if a high-frequency repetitive TMS protocol (HF-rTMS) consisting of 10 trains of 100 pulses of rTMS at 25 Hz over the motor cortex (M1) at 80% of the resting motor threshold could be effective in treating motor or non-motor symptoms in patients with PD with levodopa-induced dyskinesias. Methods: A randomized, single-blinded, placebo-controlled pilot trial was conducted with eleven PD patients. Nine patients received HF-rTMS, while two received sham stimulation. Patients were exhaustively evaluated using validated clinical scales to assess motor and non-motor symptoms. The study followed a rigorous protocol to avoid bias, with assessments conducted by a neurologist specialized in single-blinded movement disorder. Results: The HF-rTMS group experienced a statistically significant slight worsening in both motor and non-motor symptoms, particularly in the mood/cognition and gastrointestinal domains. However, positive effects were observed in some non-motor symptoms, specifically reduced excessive sweating and weight. No adverse effects were reported. Conclusions: Although HF-rTMS did not produce significant motor improvements, its potential benefit on specific non-motor symptoms, such as autonomic regulation, warrants further investigation. Full article

(1) Background: Biofeedback and neurofeedback are gaining attention as non-invasive rehabilitation strategies in Parkinson’s disease (PD) treatment, aiming to modulate motor and non-motor symptoms through the self-regulation of physiological signals. (2) Objective: This review explores the application of biofeedback techniques, electromyographic (EMG) biofeedback, heart rate variability (HRV) biofeedback, and electroencephalographic (EEG) neurofeedback in PD rehabilitation, analyzing their impacts on motor control, autonomic function, and cognitive performance. (3) Methods: This review critically examined 15 studies investigating the efficacy of electromyographic (EMG), heart rate variability (HRV), and electroencephalographic (EEG) feedback interventions in PD. Studies were selected through a systematic search of peer-reviewed literature and analyzed in terms of design, sample characteristics, feedback modality, outcomes, and clinical feasibility. (4) Results: EMG biofeedback demonstrated improvements in muscle activation, gait, postural stability, and dysphagia management. HRV biofeedback showed positive effects on autonomic regulation, emotional control, and cardiovascular stability. EEG neurofeedback targeted abnormal cortical oscillations, such as beta-band overactivity and reduced frontal theta, and was associated with improvements in motor initiation, executive functioning, and cognitive flexibility. However, the reviewed studies were heterogeneous in design and outcome measures, limiting generalizability. Subgroup trends suggested modality-specific benefits across motor, autonomic, and cognitive domains. (5) Conclusions: While EMG and HRV systems are more accessible for clinical or home-based use, EEG neurofeedback remains technically demanding. Standardization of protocols and further randomized controlled trials are needed. Future directions include AI-driven personalization, wearable technologies, and multimodal integration to enhance accessibility and long-term adherence. Biofeedback presents a promising adjunct to conventional PD therapies, supporting personalized, patient-centered rehabilitation models. Full article