Search Results (41)

Background: Recreational motorized vehicles, including all-terrain vehicles (ATVs), dirt and motor bikes, snowmobiles, and e-scooters, are an increasingly recognized source of severe trauma among children. Adult provincial data from Alberta demonstrate high morbidity, mortality, and more than $6 million in acute care costs from ATV-related injuries over a decade; however, pediatric injury patterns remain under-characterized despite rising exposure. Methods: We conducted a retrospective cohort study of pediatric patients presenting with major trauma (Injury Severity Score > 12) to the Stollery Children’s Hospital between December 2019 and June 2023. Recreational motorized vehicle-related cases were analyzed for demographics, injury mechanisms, injury severity, hospital resource utilization, and clinical outcomes. Available Abbreviated Injury Scale data were reviewed descriptively for a subset of ATV-related injuries. Results: Of 345 pediatric major trauma cases, 55 (16%) involved recreational motorized vehicles, accounting for 17% of major blunt trauma presentations. ATVs were the most common mechanism (58%), followed by dirt/motor bikes (23.6%), snowmobiles (14.5%), and e-scooters (3.6%). Patients were predominantly male (72.7%) with a mean age of 13.1 years. Operative intervention was required in 58.2% of cases, 30.9% required pediatric intensive care unit admission, and mortality was 5.5%. Helmet status was incompletely documented; only 36.4% of patients were recorded as wearing helmets. Children from rural regions accounted for 43.6% of injuries. In the ATV subset with available AIS data, head, facial, and extremity injuries were most common, and all patients sustained at least one serious injury (AIS ≥ 3). Conclusions: Recreational motorized vehicles represent a substantial and preventable cause of severe pediatric trauma in Alberta. When contextualized with adult provincial data demonstrating significant mortality and healthcare costs, these findings support strengthened injury-prevention strategies, improved safety enforcement, and evidence-informed policy approaches. Full article

Background: Understanding the temporal relationship between neurological and functional recovery after cervical spinal cord injury (SCI) is crucial for optimizing rehabilitation timing and clinical interpretation. This prospective longitudinal study aimed to investigate the temporal dynamics of clinically meaningful neurological and functional recovery in individuals with subacute SCI during inpatient rehabilitation. Methods: We enrolled 21 individuals with incomplete cSCI (AIS C and D). Evaluations were performed every 15 days, from admission up to 120 days. Recovery was defined using the Time to First Improvement based on thresholds exceeding the Minimal Detectable Change or Minimal Important Difference) for neurological scales (Upper Extremities Motor Score—UEMS, Graded Redefined Assessment of Strength, Sensation and Prehension—GRASSP subtests for Strength and Sensation) and the Minimal Clinically Important Difference for functional scales (Spinal Cord Independence Measure, GRASSP Ability and Prehension Performance). Survival analysis (Kaplan–Meier) and pairwise comparisons were used to analyze the temporal sequence of recovery. Results: Neurological and functional recovery showed a parallel macro-evolution. However, granular analysis revealed that motor strength improved significantly earlier than sensory recovery and fine motor dexterity. No significant differences were found between dominant and non-dominant limbs. Conclusions: Upper limb recovery follows a phase-specific evolution where motor strength provides the substrate for functional gains supporting a phase-specific approach to rehabilitation. Full article

Background/Objectives: Chronic traumatic spinal cord injury (SCI) causes persistent neurological deficits for which no clinically effective regenerative therapy is currently available. Mesenchymal stromal/stem cells (MSCs), particularly Wharton’s jelly-derived MSCs (WJ-MSCs), demonstrate immunomodulatory and neurotrophic potential. This phase I/II study evaluated the safety and efficacy of intrathecal allogeneic WJ-MSC administration in individuals with chronic incomplete cervical SCI. Methods: In this multicentre, randomised, double-blind, placebo-controlled trial (NCT05054803, EudraCT 2021-000346-18), 18 participants with chronic (1–5 years post-injury) incomplete cervical SCI (AIS B–D) received two intrathecal injections of WJ-MSCs (0.7–1.3 × 10⁶ viable cells/kg) or a placebo at baseline and 3 months. Seventeen participants completed the 12-month follow-up. Primary outcomes assessed safety, and secondary endpoints included International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) motor and sensory scores, spasticity, neuropathic pain, functional independence, neurophysiological measures, and quality of life. Results: Intrathecal WJ-MSC administration was safe and well tolerated. Eighty adverse events occurred (placebo: 26; WJ-MSC: 54), predominantly mild or moderate; four severe events were unrelated to treatment. Both groups demonstrated significant within-group improvements in total motor scores at 12 months, with no between-group difference. No treatment effects were observed for sensory scores, electrophysiological measures, functional independence, spasticity, pain, or patient-reported outcomes. Conclusions: In this first randomised, placebo-controlled trial evaluating intrathecal WJ-MSCs in chronic incomplete cervical SCI, WJ-MSC administration demonstrated a favourable safety profile; however, no significant between-group differences were detected relative to the placebo. Given the limited sample size and early-phase design, the efficacy findings should be interpreted cautiously. Future research should explore enhanced cell products, intensified dosing schedules, optimised delivery strategies, early intervention, and multimodal therapeutic combinations. Full article

Background: Spinal cord injury (SCI) is a leading cause of chronic disability. Loss of upper extremity (U.E.) function is central to limitations, in mobility, postural control, transfers, and self-care. The aim of this exploratory pilot study was to investigate whether self-reported UE function is associated with independence in activities of daily living (ADLs) in people with motor-incomplete tetraplegia. Methods: Eleven (n = 11) individuals with motor-incomplete tetraplegia (AIS C–D; neurological levels C4–T1; injury duration ≥ 1 year), recruited through convenience sampling from five specialist rehabilitation centres, participated in an exploratory cross-sectional pilot study designed to generate hypotheses rather than test them. U.E. function was assessed using the Patient-Rated Tennis Elbow Evaluation (PRTEE) questionnaire, selected for its ability to capture pain and task-related functional difficulty in the elbow, wrist, and hand; its application in this neurological population is considered exploratory. Independence in ADLs was evaluated using the Spinal Cord Independence Measure III (SCIM III). Given the small sample, all analyses were primarily descriptive and along with bivariate associations (Spearman correlations). Regression findings are reported strictly for exploratory purposes. Results: The median age was 50 years (interquartile range [IQR] 43–55). A strong negative correlation was observed between PRTEE total score and SCIM III (r_s = −0.76). In an exploratory univariate analysis, each 1-point increase in PRTEE total score was associated with a 1.3-point lower SCIM III score (β = −1.3, 95% CI −2.34 to −0.26, p = 0.02). Age also showed a positive association (β = 1.31, 95% CI 0.04 to 2.58, p = 0.05) with SCIM III; however, this finding is highly likely to reflect a statistical artefact of the small and unrepresentative sample. Multivariable regression was not conducted as a primary analysis due to insufficient statistical power. All findings should be treated as strictly exploratory and hypothesis-generating. Conclusions: Self-reported U.E. function appears to be associated with ADL independence in motor-incomplete tetraplegia. U.E. capacity may contribute to functional tasks requiring postural stability and mobility-related activities, but no predictive inferences can be made from this underpowered, convenience sample. Future studies with larger cohorts and performance-based measures are needed to confirm these preliminary observations and clarify the role of U.E. function in rehabilitation planning. Full article

Background/Objectives: The optimal transport strategy for patients with traumatic brain injury (TBI) remains debated, particularly in trauma systems where inter-hospital transfer is common. Whether secondary transfer independently influences mortality after risk adjustment is unclear. This study aimed to evaluate the association between admission route and in-hospital mortality among patients with TBI at a major trauma center (MTC). Methods: This retrospective observational study included 417 patients with TBI and an Abbreviated Injury Scale (AIS) head score ≥ 3 (direct admission: 245; inter-hospital transfer: 172). Severe TBI was defined as a total Glasgow Coma Scale (GCS) score ≤ 8 or the need for advanced airway management. Multivariable logistic regression was performed to assess whether admission route was independently associated with in-hospital mortality after adjustment for age, physiological status at MTC arrival, and injury severity. Subgroup analysis was conducted in patients with severe TBI. Results: Crude mortality was higher in the direct admission group than in the transfer group (40.8% vs. 26.7%; p = 0.003), despite significantly longer injury-to-trauma center arrival times in transferred patients (219.0 vs. 44.0 min). In multivariable analysis, admission route was not independently associated with mortality in the overall cohort (adjusted odds ratio [aOR] 0.75; 95% CI 0.44–1.28; p = 0.298) or in the severe TBI subgroup (n = 233; aOR 0.88; 95% CI 0.47–1.67; p = 0.705). Increasing age and lower GCS motor scores were consistently associated with higher mortality in both analyses. Conclusions: Inter-hospital transfer was not independently associated with increased in-hospital mortality among patients with TBI. After consideration of patient age and neurological severity, initial stabilization at a nearby hospital followed by transfer may be an acceptable transport strategy for patients who present with physiological instability requiring immediate resuscitative interventions. Full article

Objectives: This longitudinal single-case series evaluated an AI-based routine-learning system as assistive technology (AT) for elite Boccia athletes with severe Cerebral Palsy (CP). The study aimed to provide an innovative outcome measurement approach for individualized monitoring by integrating performance scores and longitudinal kinematic variability indicators. Methods: Three national-level players performed 694 throws over eight weeks. To ensure technical credibility, trials were rated through a consensus-based assessment by a panel of two experts, serving as ground truth for AI modeling. The system utilized a Bidirectional Long Short-Term Memory (Bi-LSTM) architecture to extract 29 kinematic features and perform regression-based scoring, providing real-time augmented feedback. Results: High-baseline tasks maintained stable scores (7–9), while intermediate tasks showed significant score increases, reflecting motor learning transitions. The model achieved a Mean Squared Error of 1.14 and a Mean Absolute Error of 1.13, demonstrating high alignment with expert standards. Training demonstrated stable convergence, with loss reducing from 7.45 to 1.19. Notably, for the most severely impaired athlete, the AI system detected a 4.69% reduction in kinematic variability despite stagnant performance scores. This provides empirical evidence of movement stabilization within the cognitive stage that traditional observation might overlook. Conclusions: The Bi-LSTM system enabled accurate tracking of performance and motor variability, revealing distinct learning curves based on task difficulty. These findings demonstrate the feasibility of AI-enabled motion analysis as an AT for outcome measurement, supporting data-driven coaching where conventional evaluation is constrained by the rarity and severity of disabilities. Full article

Background/Objectives: Muscle wasting is often observed in the acute phase after spinal cord injury (SCI). We aim to investigate the factors determining rectus femoris muscle thickness and echo intensity on discharge for patients who had acute incomplete spinal cord injury undergoing inpatient rehabilitation. Methods: This is a prospective exploratory observational cohort study, conducted in a standalone inpatient multi-specialty tertiary rehabilitation center in Singapore. Forty-five patients with incomplete SCI, defined as American Spinal Injury Association Impairment Scale (AIS) B–D were recruited from January 2020 to October 2021. Variables including clinico-demographic data, lower limb spasticity, Lower Extremity Muscle Score (LEMS), Functional Independence Measure (FIM) motor score on admission were collected. Muscle ultrasound of the rectus femoris thickness and echo intensity were obtained at 6 weeks after acute SCI via standardized protocols. Stepwise multiple regression analyses were performed to identify the factors that were significant for rectus femoris muscle thickness and echo intensity on discharge. Results: The mean age of participants was 59.6 ± 16.6 years, with patients having AIS of B (11.1%), C (28.9%) or D (60.0%). Rectus femoris muscle thickness on discharge had a significant association with body mass index (B = 4.62; CI = 1.77, 7.47; p = 0.002) and onset of mobilization (B = −4.97; CI = −9.46, −0.484; p = 0.031). The significant variables associated with rectus femoris echo intensity on discharge were age (B = 0.546; CI = 0.126, 0.967; p = 0.012) and onset of mobilization (B = 2.49; CI = 0.439, 4.53; p = 0.019). Conclusions: Our findings suggest that age, body mass index and a delayed onset of mobilization may have significant impact on muscle ultrasound parameters. Patients with incomplete SCI may benefit from early mobilization and nutritional assessment for improved muscle strength and function. Full article

Viticulture is facing growing economic and environmental pressures that demand a transition toward intelligent and autonomous crop management systems. Phytopathologies remain one of the most critical threats, causing substantial yield losses and reducing grape quality, while regulatory restrictions on agrochemicals and sustainability goals are driving the development of precision agriculture solutions. In this context, early disease detection is crucial; however, current visual inspection methods are hindered by subjectivity, cost, and delayed symptom recognition. This study presents a fully autonomous robotic platform developed within the Agrimet project, enabling continuous, high-frequency monitoring in vineyard environments. The system integrates a tracked mobility base, multimodal sensing using RGB-D and thermal cameras, an AI-based perception framework for leaf localisation, and a compliant six-axis manipulator for biological sampling. A custom control architecture bridges standard autopilot PWM signals with industrial CANopen motor drivers, achieving seamless coordination among all subsystems. Field validation in a Sicilian vineyard demonstrated the platform’s capability to navigate autonomously, acquire multimodal data, and perform precise georeferenced sampling under unstructured conditions. The results confirm the feasibility of holistic robotic systems as a key enabler for sustainable, data-driven viticulture and early disease management. The YOLOv10s detection model achieved good precision and F1-score for leaf detection, while the integrated Kalman filtering visual servoing system demonstrated low spatial tolerance under field conditions despite foliage sway and vibrations. Full article

Background/Objectives: The GCS is widely used to assess a patient’s level of consciousness after trauma. Although not a diagnostic tool for traumatic brain injury (TBI), prehospital clinicians frequently rely on GCS findings—along with pupil exam, mechanism of injury, and clinical presentation, to estimate the likelihood that TBI may be present before imaging is available. However, the GCS has known limitations and fails to identify a significant proportion of TBI patients. This study aimed to evaluate the association between GCS scores and the presence of TBI, and whether additional clinical variables improve its discriminatory value. Methods: This retrospective cohort study analyzed data from trauma patients registered in the TraumaRegister DGU^® between 2015 and 2017. TBI was defined as a head injury with an Abbreviated Injury Scale (AISHead) score of ≥2. Inclusion criteria consisted of trauma team activations with a maximum AIS ≥ 3 and/or the need for intensive care. Prognostic values were assessed using multivariable logistic regression analysis. Results: 40,216 patients were included of which 17,205 (42.8%) were diagnosed with TBI and 23,011 (57.2%) were non-TBI patients. In the TBI group, 36.4% (n = 6216) presented with an initial GCS of 15 prehospitally. 17.8% (n = 3059) of TBI patients had anisocoric or bilaterally dilated pupils, 22.1% (n = 3799) had sluggish or fixed light reactivity and 17% (n = 2934) had no motoric response in Eppendorf-Cologne Scale (ECS) motor component. GCS score by itself showed better TBI prediction value than pupil size or reactivity or motor component alone. Nevertheless, substantial misclassification was observed when using GCS alone: 25.7% of patients with a normal GCS (15) had TBI (AIS Head ≥ 2), while 19.1% of patients with GCS 3 had no TBI. In the non-TBI group, 2.7% (n = 622) had a GCS of 3, 2.9% (n = 685) had anisocoric or bilaterally dilated pupils, 4.2% (n = 960) had sluggish or fixed light reactivity and 3.3% (n = 751) had no motoric response. Even at the lowest GCS score of 3, 19.1% of patients did not have TBI, while a normal GCS of 15 still included 25.7% of patients with TBI. Conclusions: The expanded model combining GCS with pupillary assessment and the ECS motor component demonstrated superior performance in prehospital TBI detection compared with the GCS alone. Implementing an extended GCS incorporating pupillary and ECS assessment may facilitate earlier recognition of TBI and support timely triage decisions; however, potential effects on patient outcomes require confirmation in prospective studies. Full article

Background and Objectives: Spinal cord lesion is a severe disorder of the central nervous system, leading to partial or complete interruption of nerve impulse transmission between the brain and the periphery and causing severe neurological and functional deficits. Conventional rehabilitation offers limited outcomes, while robotic gait training (Lokomat^®) and Vojta Therapy have shown benefits individually. Evidence on their combined effect remains scarce. To evaluate the combined effect of Vojta Therapy and Lokomat-assisted gait training on motor recovery, functional independence, and quality of life in SCL patients. Materials and Methods: A retrospective clinical study was conducted on 205 patients with traumatic and non-traumatic SCL. Patients were allocated to four groups: (F)—conventional rehabilitation; (V)—conventional + Vojta; (L)—conventional + Lokomat; (VL)—conventional + Vojta + Lokomat. Assessments included the ASIA Impairment Scale (AIS), ASIA motor/sensory scores, spasticity (Modified Ashworth Scale, MAS), functional independence (Functional Independence Measure, FIM), and health-related quality of life (EQ-5D), performed at admission and discharge. Statistical analyses comprised paired t-tests, Wilcoxon signed-rank tests, chi-square tests, Kruskal–Wallis with Dunn’s post hoc corrections, and linear regression. Results: The most frequent lesion levels were C7 (21%) and L1 (20%). All groups showed improvement in FIM scores, with the greatest gains in the VL group (from 79.25 to 84.79, p < 0.05). Post hoc analysis confirmed significantly higher FIM outcomes in VL compared with L. Regression analysis identified the ASIA motor score as the strongest predictor of functional independence (β = 0.76, p < 0.001), with VL group membership adding +10.3 points (p = 0.004). EQ-5D indicated persistent deficits in mobility and self-care, especially in VL patients, consistent with higher lesion severity. Conclusions: Combining Vojta Therapy with Lokomat training provides additional functional benefits compared with Lokomat or Vojta alone. Multimodal individualized rehabilitation appears promising for patients with spinal cord lesions. Prospective randomized controlled trials with long-term follow-up are warranted. Full article

This paper presents a mathematics-focused AI iterative prediction framework that combines Extreme Gradient Boosting (XGBoost) for nonlinear function approximation with nonlinear autoregressive model with exogenous inputs (NARXs) for time-series modeling, applied to analyzing the Remaining Useful Life (RUL) and availability of Unmanned Aerial Vehicle (UAV) Brushless DC (BLDC) motors. The framework integrates nonlinear regression, temporal recursion, and survival analysis into a unified system. The dataset includes five UAV motor types, each recorded for 10 min at 20 Hz, totaling approximately 12,000 records per motor for validation across these five motor types. Using grouped K-fold cross-validation by motor ID, the framework achieved mean absolute error (MAE) of 4.01 h and root mean square error (RMSE) of 4.51 h in RUL prediction. Feature importance and SHapley Additive exPlanation (SHAP) analysis identified temperature, vibration, and HI as key predictors, aligning with degradation mechanisms. For availability assessment, survival metrics showed strong performance, with a C-index of 1.00 indicating perfect risk ranking and a Brier score at 300 s of 0.159 reflecting good calibration. Additionally, Conformalized Quantile Regression (CQR) enhanced interval coverage under diverse operating conditions, providing mathematically guaranteed uncertainty bounds. The results demonstrate that this framework improves both accuracy and interpretability, offering a reliable and adaptable solution for UAV motor prognostics and maintenance planning. Full article

Advances in brain–computer interface (BCI) research have explored various strategies for acquiring and processing electroencephalographic (EEG) signals to detect motor imagery (MI) activities. However, the complexity of multichannel clinical systems and processing techniques can limit their accessibility outside specialized centers, where complex setups are not feasible. This paper presents a proof-of-concept prototype of a single-channel EEG acquisition and processing system designed to identify lower-limb motor imagery. The proposed proof-of-concept prototype enables the wireless acquisition of raw EEG values, signal processing using digital filters, and the detection of MI patterns using machine learning algorithms. Experimental validation in a controlled laboratory with participants performing resting, MI, and movement tasks showed that the best performance was obtained by combining Savitzky–Golay filtering with a Random Forest classifier, reaching 87.36% ± 4% accuracy and an F1-score of 87.18% ± 3.8% under five-fold cross-validation. These findings confirm that, despite limited spatial resolution, MI patterns can be detected using appropriate AI-based filtering and classification. The novelty of this work lies in demonstrating that a single-channel, portable EEG prototype can be effectively used for lower-limb MI recognition. The portability and noise resilience achieved with the prototype highlight its potential for research, clinical rehabilitation, and assistive device control in non-specialized environments. Full article

(1) Background: Technological advancements provide new opportunities to objectively assess motor deficits in people with Multiple Sclerosis (PwMS). This pilot study aimed to evaluate the performance and usability of iFeel, a novel wearable system which integrates inertial sensors, instrumented shoes, and an AI-based algorithm. (2) Methods: Sixteen adult PwMS (Expanded Disability Status Scale—EDSS ≤ 6) performed motor tests (Timed 25-Foot Walk—T25FW; Timed Up and Go—TUG) both with and without the iFeel suit. Patient-reported outcomes (PROs) were also collected to assess perceived fatigue, dual-task impact, and walking difficulties. System Usability Scale (SUS) and ad hoc questionnaires have been further administered to test usability. (3) Results: No significant differences were found between the clinician and system-based scores for both T25FW (p = 0.383) and TUG (p = 0.447). Reliability analyses showed good agreement for T25FW (Intraclass Correlation Coefficient—ICC = 0.83) and excellent agreement for TUG (ICC = 0.92). Sensor-derived measures correlated strongly with PROs on fatigue, dual-task interference, and mobility. Usability was rated high (SUS: 78.6 ± 16.1), with participants reporting minimal discomfort and positive perceptions of iFeel usefulness for rehabilitation, health monitoring, and daily activities. (4) Conclusions: This pilot study provides preliminary yet promising evidence on the feasibility, usability, and perceived usefulness of the iFeel technology for motor assessment in PwMS. The findings support its further development and potential integration into clinical practice, particularly for remote or continuous motor monitoring. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that impairs motor function, often causing tremors and difficulty with movement control. A promising diagnostic method involves analyzing hand-drawn patterns, such as spirals and waves, which show characteristic distortions in individuals with PD. This study compares three computational approaches for classifying individuals as Parkinsonian or healthy based on drawing-derived features: (1) Large Language Models (LLMs), (2) traditional machine learning (ML) algorithms, and (3) a fuzzy ontology-based method using fuzzy sets and Fuzzy-OWL2. Each method offers unique strengths: LLMs leverage pre-trained knowledge for subtle pattern detection, ML algorithms excel in feature extraction and predictive accuracy, and fuzzy ontologies provide interpretable, logic-based reasoning under uncertainty. Using three structured handwriting datasets of varying complexity, we assessed performance in terms of accuracy, interpretability, and generalization. Among the approaches, the fuzzy ontology-based method showed the strongest performance on complex tasks, achieving a high F1-score, while ML models demonstrated strong generalization and LLMs offered a reliable, interpretable baseline. These findings suggest that combining symbolic and statistical AI may improve drawing-based PD diagnosis. Full article

Objectives: Despite the implementation of additional safety measures, motor vehicle collisions (MVCs) still result in significant injuries and fatalities. This study aims to explore the severity of these injuries and the length of hospital stays (LOS) following MVCs. Furthermore, this study will assess how helmet use and alcohol influence trauma outcomes. Methods: This retrospective study from a single center includes 604 patients from 1 January 2016, to 31 December 2024. Patients were identified based on the Abbreviated Injury Scale (AIS) body regions. Descriptive statistics and ANOVA were performed on helmet use and blood alcohol concentration, with significance set at p < 0.01. Results: Mean LOS at the hospital (H) was 13 days, 10.53 h in the ED, and 113.32 h in the ICU. In total, 74.5% of patients were male and 25.5% were female. The mean injury severity score (ISS) was 22.58, with 99.83% representing blunt trauma. The majority of patients (94.21%) arrived with signs of life, with 50.99% patients discharged to home or self-care (routine discharge). A noticeable trend following 2020 showed an increase in ED discharges, and thus ED admissions, compared to years before 2020. Helmet use showed a non-significant trend toward reduced ISS and length of stay. ETOH level and primary payor source were not significantly associated with outcome variables in regression models, though patterns suggest a potential relationship between payor source and ED discharge disposition. Conclusions: This study identifies important clinical trends that merit further investigation. Helmet use may be associated with reduced injury severity and shorter hospital stays, while differences in primary payor source suggest disparities in ED discharge outcomes. These findings underscore the need for further research on payor disposition, helmet use, and ETOH level in MVCs. Full article