Search Results (1,857)

Background: About half of all Major Depressive Disorder (MDD) patients have anxiety disorder. There is a neurologic basis for the comorbidity of balance (vestibular) disorders and anxiety. To detect comorbid anxiety disorder in MDD patients and, importantly, to investigate its relationship with depressive severity, we use Electrovestibulography (EVestG), which is predominantly a measure of vestibular response. Methods: In a population of 42 (26 with anxiety disorder) MDD patients, EVestG signals were measured. Fourteen (eight with anxiety disorder) were not on any anti-depressants, anti-psychotics or mood stabilizers. Using standard questionnaires, participants were depression-wise labelled as reduced symptomatic (MADRS ≤ 19, R) or symptomatic (MADRS > 19, S) as well as with or without anxiety disorder. Analyses were conducted on the whole data set, matched (age/gender/MADRS) subsets and compared with medication free subsets. Low-frequency EVestG firing pattern modulation was measured. Results: The main differences between MDD populations with and without anxiety disorder populations, regardless of being medicated or not, were (1) the presence of an increased 10.8 Hz component in the dynamic movement phase recordings, (2) the presence of asymmetric right versus left 7.6–8.9 Hz and 12.1–13.8 Hz frequency bands in the no motion (static) phase recordings, and (3) these differences were dependent on depressive severity. Conclusions: The EVestG measures are capable of quantifying anxiety in MDD patients. These measures are functions of depressive severity and are hypothesized to be linked to Hippocampal Theta (~4–12 Hz). Full article

Objectives: The aim of this study was to evaluate the impact of four working heights on lumbar biomechanics during wall construction tasks, focusing on work-related musculoskeletal disorders (WMSDs). Methods: Fifteen young male participants performed simulated mortar-spreading and bricklaying tasks while actual body movements were recorded using Inertial Measurement Unit (IMU) sensors. Muscle activities of the lumbar erector spinae (ES), quadratus lumborum (QL), multifidus (MF), gluteus maximus (GM), and iliopsoas (IL) were estimated using a 3D musculoskeletal (MSK) model and measured via surface electromyography (sEMG). The analysis of variance (ANOVA) test was conducted to identify the significant differences in muscle activities across four working heights (i.e., foot, knee, waist, and shoulder). Results: Findings showed that working at foot-level height resulted in the highest muscle activity (7.6% to 40.6% increase), particularly in the ES and QL muscles, indicating an increased risk of WMSDs. The activities of the ES, MF, and GM muscles were statistically significant across both tasks and all working heights (p < 0.01). Conclusions: Both MSK and sEMG analyses indicated significantly lower muscle activities at knee and waist heights, suggesting these as the best working positions (47 cm to 107 cm) for minimizing the risk of WMSDs. Conversely, working at foot and shoulder heights was identified as a significant risk factor for WMSDs. Additionally, the similar trends observed between MSK simulations and sEMG data suggest that MSK modeling can effectively substitute for sEMG in future studies. These findings provide valuable insights into ergonomic work positioning to reduce WMSD risks among wall construction workers. Full article

There is limited published guidance available to help less experienced practitioners assess and manage shoulder conditions, including spasticity, after acquired central nervous system (CNS) lesions. To address this gap, 11 spasticity and dystonia experts convened in a 2023 meeting to build on existing guidance, provide consensus on best treatment practice, and develop expert recommendations to guide the diagnosis and treatment of complications of shoulder conditions following CNS lesions. Presentations by each expert on diagnosis and management were followed by discussion; consensus on assessment and treatment practices was identified and recommendations developed. The expert panel recommended an assessment approach structured using the following components: patient history, including interpretation of reported symptoms; observation of postures and pain responses; clinical examination with targeted tests for specific signs; diagnostic tests; and assessment of upper limb impairment, activity limitations, and participation restrictions. This assessment process and the recommended measures recognize the importance of identifying shoulder involvement in upper limb spasticity as part of the diagnostic process in shoulder conditions following CNS lesions. These recommendations provide a practical approach to diagnosis and treatment for clinicians who are less experienced in evaluating and treating such conditions, simplifying otherwise complicated clinical scenarios. Full article

Background/Objectives: Huntington’s disease (HD) is a neurodegenerative disorder involving the basal ganglia and is characterized by psychiatric, cognitive, and movement dysfunction, including gait and balance impairment. Given the limited efficacy of pharmacological treatments for HD motor symptoms, nonpharmacological approaches like rhythmic auditory stimulation are being explored. This study aims to describe walking performance in people with HD during rhythmic auditory stimulation using external musical cues and internal singing cues. Methods: Individuals in the manifest stage of HD performed walking in four conditions: (1) comfortable pace, (2) cognitive dual task, (3) musical cue (music was played aloud), and (4) singing cue (participants sang aloud). Sensors measured cadence, velocity, stride length, and variability. Relationships between change in cadence and motor and cognitive measures were explored. Results: While no direct measurements of synchronization were performed, limiting our interpretation, neither the external musical cue nor the singing cue significantly improved walking performance. Both cues increased variability, similar to what was observed during the dual task. Greater subjective balance confidence and better cognitive performance were associated with positive cadence change during cueing. Conclusions: Musical cues may be too cognitively demanding for individuals with Huntington’s disease as they worsen gait variability without increasing gait speed, cadence, or stride length. Although global cognition and perceived balance confidence were related to the ability to increase cadence, very few people were able to increase their cadence during either cue. Therefore, the results do not support the use of musical cues to improve gait for individuals with Huntington’s disease. Full article

Continuous monitoring of respiratory patterns is essential for disease diagnosis and daily health care. Contact medical devices enable reliable respiratory monitoring, but can cause discomfort and are limited in some settings. Radar offers a noncontact respiration measurement method for continuous, real-time, high-precision monitoring. However, it is difficult for a single radar to characterize the coordination of chest and abdominal movements during measured breathing. Moreover, motion interference during prolonged measurements can seriously affect accuracy. This study proposes a dual radar system with customized narrow-beam antennas and signals to measure the chest and abdomen separately, and an adaptive dynamic time warping (DTW) algorithm is used to effectively suppress motion interference. The system is capable of reconstructing respiratory waveforms of the chest and abdomen, and robustly extracting various respiratory parameters via motion interference. Experiments on 35 healthy subjects, 2 patients with chronic obstructive pulmonary disease (COPD), and 1 patient with heart failure showed a high correlation between radar and respiratory belt signals, with correlation coefficients of 0.92 for both the chest and abdomen, a root mean square error of 0.80 bpm for the respiratory rate, and a mean absolute error of 3.4° for the thoracoabdominal phase angle. This system provides a noncontact method for prolonged respiratory monitoring, measurement of chest and abdominal asynchrony and apnea detection, showing promise for applications in respiratory disorder detection and home monitoring. Full article

Background: Tremor is a common but diagnostically challenging movement disorder due to its clinical heterogeneity and overlapping aetiologies. The 2018 consensus introduced a two-axis classification system that redefined tremor syndromes by distinguishing between clinical phenomenology and underlying causes, and introduced new diagnostic categories, such as essential tremor plus. Methods: This review synthesises recent advances in the epidemiology, classification, pathophysiology, and treatment of tremor syndromes, aiming to provide an integrated and clinically relevant framework that aligns with emerging diagnostic and therapeutic paradigms. Results: We discuss how electrophysiology, neuroimaging, wearable sensors, and artificial intelligence are reshaping diagnostic precision. Syndromes such as essential tremor, parkinsonian tremor, dystonic tremor, task-specific tremor, orthostatic tremor, and functional tremor are examined through syndromic, aetiological, and mechanistic lenses. The limitations of current rating scales and the promise of emerging biomarkers are critically assessed. Conclusions: As therapeutic approaches evolve toward neuromodulation and precision medicine, the need for pathophysiologically grounded diagnostic criteria becomes more urgent. Integrating network-based frameworks, digital diagnostics, and individualised treatment holds promise for advancing tremor care. Full article

Background: Very preterm infants are at increased risk of impairment. The objective was to explore the effect of immediate parent–infant skin-to-skin contact at very preterm birth on cognition, motor, social, and language development during the two first years. Methods: The Immediate Parent-Infant Skin-To-Skin Study (IPISTOSS) was a clinical trial with inclusions between April 2018 to June 2021, in three Scandinavian neonatal intensive care units. Infants were randomised at gestational age 28 + 0 to 32 + 6 weeks plus days, to immediate and continuous skin-to-skin contact at birth or conventional care, during the first six hours of life. Results: At three months, 42 infants underwent a General Movement Assessment. At four and 12 months, 69 and 62 infants, respectively, were assessed with the Alberta Motor Infant Scale. At 24 months, language and cognition were tested in 62 infants with the Bayley Scales of Infant and Toddler Development, third edition. Parents completed the Modified Checklist for Autism in Toddlers for 57 infants. There were no significant differences in motor development, cognition, or autism spectrum disorders. A significant difference in language scores in favour of immediate skin-to-skin contact, was found, when adjusted for fathers’ education, mothers’ education, and infants’ sex, Beta (95% CI): 32.00 (7.57, 56.43) p = 0.01, 11.51 (8.94, 55.06) p = 0.007, and 32.00 (7.85, 56.15) p = 0.01, respectively. Conclusions: Skin-to-skin contact immediately at birth did not enhance cognition, motor, or social development during the first two years of life but may have been important for language skills. Our findings support the World Health Organisation guidelines recommending iSSC for preterm born infants in all settings. Full article

Background: Some neonates are assessed for the risk of atypical psychomotor development at birth and are referred for reflex locomotion therapy using the Vojta method. Aim: The aim of this study was to analyze the relationships between spontaneous motor activity (SMA), ideal movement patterns (IMPs), central coordination disorders (CCDs), vital signs at birth, involuntary reflexes, and postural asymmetry in infants. Methods: This study involved 90 female and 107 male subjects in the age interval of 1–16 months (4.15 ± 2.18). Their psychomotor development was assessed using the Vojta method. Age-appropriate involuntary reflexes were evaluated, and both parameters were correlated with perinatal risk factors. Results: Males scored significantly higher than females (difference of −0.7, p = 0.022) in the SMA test. In both genders, SMA (p < 0.001 in both genders) and IMP scores improved significantly with age. In male infants, higher CCD scores were associated with significantly lower SMA and IMP scores (p = 0.017 and p < 0.001, respectively). Significantly higher CCD scores were noted in female subjects with the Moro reflex and postural asymmetry (p = 0.003 and p = 0.002, respectively). In males, the Moro reflex was significantly correlated with the Vojta reaction (p = 0.012) and the Collis vertical suspension reflex (p < 0.001). Conclusions: Vital signs at birth, including birth weight, Apgar score, and type of delivery, can predict motor development disorders but do not clearly differentiate infants that require neurodevelopmental therapy. Full article

In recent decades, information technology has grown. Computers have become a daily activity, facilitating access to information, faster communication and faster work. If used responsibly, it has many advantages. Objectives: To explore the potential link between prolonged use of computer input devices—such as keyboards and mice—and the development of compressive neuropathies, including carpal tunnel syndrome (CTS) and cubital tunnel syndrome (CuTS), in individuals whose daily routines are heavily reliant on computer-based activities. Methods: A comprehensive review of the literature was undertaken to assess the correlation between the use of computer input devices and the incidence of compressive neuropathies in the upper limbs, with particular attention to repetitive strain, ergonomic posture deviations, and personal risk factors. Results: Current evidence indicates a potential association between prolonged computer use and the development of upper limb compressive neuropathies; however, a definitive consensus within the scientific literature remains elusive. Repetitive movements and non-neutral postures appear to be significant contributing factors, particularly among individuals with predisposing risk factors. Despite increasing awareness of this issue, standardized, evidence-based clinical guidelines for the evaluation and management of work-related nerve disorders remain lacking. Conclusions: While the relationship between computer use and compressive neuropathies remains debated, healthcare professionals should be aware of the risks, particularly in individuals exposed to repetitive strain and ergonomic stress. Further research and the development of clinical guidelines are needed to better understand and manage these work-related conditions. Full article

(1) Background: Children with attention-deficit hyperactivity disorder (ADHD) engage in significantly less physical activity than their peers. While ample research has shown the beneficial effect of physical activity on ADHD management, we have little to no knowledge of how children with ADHD experience physical activity, which may ultimately undermine the utility of prescribed physical activity programming. This study compared experiences and perspectives of physical activity in school and non-school settings, between children with and without ADHD. (2) Methods: In this study, 23 children with ADHD and 24 children without ADHD participated in semi-structured interviews, sharing their views on physical activity in school and non-school settings. (3) Results: Inductive content analysis revealed that, compared to children without ADHD, children with ADHD reported lower physical activity levels, more often emphasized the benefits of movement for improving mood and focus during learning, viewed classroom-based desk cycling as a helpful tool to focus their attention, and expressed a desire to use desk cycling during classroom learning. (4) Conclusions: This study emphasizes key differences in the physical activity experiences and preferences between children with and without ADHD; it also offers insight into how classroom learning may be enhanced by offering optional physical activity outlets for children who identify as benefiting from movement during learning. Full article

Eye movements (EMs) offer valuable insights into cognitive and perceptual processes, serving as potential biomarkers for disordered thinking. This study explores the relationship between EM indices and perception and thinking problems in the Rorschach Performance Assessment System (R-PAS). Sixty non-clinical participants underwent eye-tracking while completing the Rorschach test, focusing on variables from the Perception and Thinking Problems Domain (e.g., WSumCog, SevCog, FQo%). The results reveal that increased cognitive disturbances were associated with greater exploratory activity but reduced processing efficiency. Regression analyses highlighted the strong predictive role of cognitive variables (e.g., WSumCog) over perceptual ones (e.g., FQo%). Minimal overlap was observed between performance-based (R-PAS) and self-report measures (BSI), underscoring the need for multi-method approaches. The findings suggest that EM patterns could serve as biomarkers for early detection and intervention, offering a foundation for future research on psychotic-spectrum processes in clinical and non-clinical populations. Full article

Mitochondrial Membrane Protein-Associated Neurodegeneration is a rare monogenic form of neurodegeneration characterized by iron accumulation in the brain. It is due to variants in the orphan gene C19orf12. Since its definition in 2011, many scientific groups have investigated the clinical features and molecular underpinnings of the disorder. In this review, we summarize the main points of progress in this field, trying to highlight the issues that need further attention and efforts to speed up the diagnostic path, improve the existing treatment options, and define targeted therapies. Full article

Gait analysis is a valuable tool for aiding in the diagnosis of neurological diseases, providing objective measurements of human gait kinematics and kinetics. These data enable the quantitative estimation of movement abnormalities, which helps to diagnose disorders and assess their severity. In this regard, machine learning techniques and explainability methods offer an opportunity to enhance anomaly detection in gait measurements and support a more objective assessment of neurodegenerative disease, providing insights into the most relevant gait parameters used for disease identification. This study employs several classifiers and explainability methods to analyze gait data from a public dataset composed of patients affected by degenerative neurological diseases and healthy controls. The work investigates the relevance of spatial, temporal, and kinematic gait parameters in distinguishing such diseases. The findings are consistent among the classifiers employed and in agreement with known clinical findings about the major gait impairments for each disease. This work promotes the use of data-driven assessments in clinical settings, helping reduce subjectivity in gait evaluation and enabling broader deployment in healthcare environments. 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

Background/Objectives: Deep brain stimulation (DBS) is an effective surgical treatment for Parkinson’s Disease (PD) and other movement disorders. Despite its benefits, DBS explantation occurs in 5.6% of cases, with costs exceeding USD 22,000 per implant. Traditional statistical methods have struggled to identify reliable risk factors for explantation. We hypothesized that supervised machine learning would more effectively capture complex interactions among perioperative factors, enabling the identification of novel risk factors. Methods: The Medical Informatics Operating Room Vitals and Events Repository was queried for patients with DBS, adequate clinical data, and at least two years of follow-up (n = 38). Fisher’s exact test assessed demographic and medical history variables. Data were analyzed using Anaconda Version 2.3.1. with pandas, numpy, sklearn, sklearn-extra, matplotlin. pyplot, and seaborn. Recursive feature elimination with cross-validation (RFECV) optimized factor selection was used. A multivariate logistic regression model was trained and evaluated using precision, recall, F1-score, and area under the curve (AUC). Results: Fisher’s exact test identified chronic pain (p = 0.0108) and tobacco use (p = 0.0026) as risk factors. RFECV selected 24 optimal features. The logistic regression model demonstrated strong performance (precision: 0.89, recall: 0.86, F1-score: 0.86, AUC: 1.0). Significant risk factors included tobacco use (OR: 3.64; CI: 3.60–3.68), primary PD (OR: 2.01; CI: 1.99–2.02), ASA score (OR: 1.91; CI: 1.90–1.92), chronic pain (OR: 1.82; CI: 1.80–1.85), and diabetes (OR: 1.63; CI: 1.62–1.65). Conclusions: Our study suggests that supervised machine learning can identify risk factors for early DBS explantation. Larger studies are needed to validate our findings. Full article