Search Results (10)

Continuous monitoring of sitting posture is crucial for ergonomic assessment and fatigue prevention, yet many existing approaches rely on vision-based systems or single-modality sensing that are limited in capturing spatial and temporal biomechanical dynamics. This paper presents a multimodal smart-skin sensing system for spatial and temporal ergonomic fatigue analysis in sitting postures. The proposed platform integrates 42 distributed pressure, temperature, and vibration sensors arranged in 14 trimodal sensing nodes embedded across anatomical seating and back regions to enable real-time multimodal acquisition of human–chair interaction patterns. The study introduces an analytical framework combining anatomical heatmap visualization, temporal evolution analysis, delta pressure mapping, fatigue intensity estimation, and hotspot detection to characterize dynamic pressure redistribution during prolonged sitting. Experimental evaluations were conducted using a biomechanical mannequin and a single human participant with identical anthropometric characteristics (165 cm height and 62 kg body mass) across nine seated conditions, including neutral sitting, reclining, leaning, periodic shifting, and vibration-induced motion. Each posture condition was recorded as a time-series session and segmented into temporal phases to analyze fatigue evolution during prolonged sitting. Statistical analysis of pressure redistribution dynamics indicates significantly higher pressure drift in human measurements compared with the mechanically stable mannequin baseline (p < 0.001). The proposed framework provides a scalable sensing approach for ergonomic monitoring, intelligent seating systems, and human–machine interface applications. Full article

Understanding intra- and inter-individual variability in muscle activation is essential for applications in rehabilitation, ergonomics, and motor control research. Surface electromyography (sEMG) provides a non-invasive tool to study these patterns by capturing the electrical activity of muscles. This study investigated the spectral pattern variability of sEMG signals recorded from the biceps brachii and brachioradialis during repeated near-maximal isometric elbow flexion tasks with supinated and neutral forearm postures. sEMG signals from 33 healthy adults were analyzed in the frequency domain to obtain power spectra for each repetition. Intra-individual variability was quantified by comparing each repetition to a participant-specific reference spectrum, while inter-individual variability was assessed by comparing these reference spectra across participants using distance-based metrics. Statistical analyses revealed systematic posture-dependent differences, with the neutral forearm posture generally exhibiting greater spectral variability than the supinated posture, particularly in the biceps brachii. These findings highlight potential posture-related trends in neuromuscular activation; however, they should be interpreted with caution, as variability may also reflect differences in contraction intensity, fatigue, or task-specific biomechanics. Full article

To address the high incidence of work-related musculoskeletal disorders (WMSDs) at manual edge-banding workstations in furniture factories, and in an effort to tackle the existing research challenges of poor cumulative risk quantification and inconsistent evaluations, this paper proposes a three-stage system for continuous, automated, non-invasive WMSD risk monitoring. First, MediaPipe 0.10.11 is used to extract 33 key joint coordinates, compute seven types of joint angles, and resolve missing joint data, ensuring biomechanical data integrity for subsequent analysis. Second, joint angles are converted into graded parameters via RULA, REBA, and OWAS criteria, enabling automatic calculation of posture risk scores and grades. Third, an Adaptive Pooling Convolutional Neural Network (CNN) and Long Short-Term Memory Network (LSTM) dual-branch hybrid model based on the Efficient Channel Attention (ECA) mechanism is built, which takes nine-dimensional features as the input to predict expert-rated fatigue states. For validation, 32 experienced female workers performed manual edge-banding tasks, with smartphones capturing videos of the eight work steps to ensure authentic and representative data. The results show the following findings: (1) system ratings strongly correlate with expert evaluations, verifying its validity for posture risk assessment; (2) the hybrid model successfully captures the complex mapping of expert-derived fatigue patterns, outperforming standalone CNN and LSTM models in fatigue prediction—by integrating CNN-based spatial feature extraction and LSTM-based temporal analysis—and accurately maps fatigue indexes while generating intervention recommendations. This study addresses the limitations of traditional manual evaluations (e.g., subjectivity, poor temporal resolution, and inability to capture cumulative risk), providing an engineered solution for WMSD prevention at these workstations and serving as a technical reference for occupational health management in labor-intensive industries. Full article

Background/Objectives: Postural orthostatic tachycardia syndrome (POTS) is a form of dysautonomia characterized by excessive tachycardia during orthostatic stress. It is frequently observed in patients with syncope, Chronic Fatigue Syndrome (CFS), and post-COVID-19 syndrome (PCS), yet the underlying mechanisms may differ across these conditions. This study aimed to assess autonomic nervous system (ANS) function in patients with syncope, CFS of insidious onset, and CFS post-COVID-19 who presented with POTS, and to compare them with age- and sex-matched patients without POTS. Methods: In this retrospective cross-sectional study, 138 patients over 18 years of age were included following head-up tilt testing (HUTT). Patients were divided into six groups: syncope with and without POTS, CFS with insidious onset with and without POTS, and CFS post-COVID-19 with and without POTS. All participants underwent HUTT, cardiovascular reflex testing (CART) by Ewing, five-minute resting ECG with short-term Heart Rate Variability (HRV) analysis, and 24 h Holter ECG monitoring. Results: The prevalence of POTS across groups ranged from 5% to 7%. Female predominance was consistent across all subgroups. In syncope with POTS, hypertensive responses during HUTT, lower rates of normal Valsalva maneuver results, and reduced HF values in short-term HRV suggested baroreceptor dysfunction with sympathetic overdrive. In both CFS subgroups with POTS, CART revealed higher rates of definite parasympathetic dysfunction, along with more frequent extreme blood pressure variation during HUTT and reduced vagally mediated HRV parameters (rMSSD, pNN50). Across groups, no significant differences were observed with regard to long-term HRV across groups. Conclusions: Distinct autonomic profiles were identified in POTS patients depending on the underlying condition. Syncope-related POTS was associated with baroreceptor dysfunction and sympathetic predominance, whereas CFS-related POTS was characterized by parasympathetic impairment and impaired short-term baroreflex regulation. Evaluating dysautonomia patterns across disease contexts may inform tailored therapeutic strategies and improve management of patients with POTS. Full article

Background/Objectives: Orthostatic intolerance is prevalent in patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and is caused by an abnormal reduction in cerebral blood flow (CBF). In healthy controls (HCs), CBF is regulated complexly, and cardiac output (CO) is an important determinant of CBF. A review in HC showed that a 30% reduction in CO results in a 10% reduction in CBF. In contrast, we showed in ME/CFS patients with a normal HR (HR) and blood pressure response during a tilt test that CO and CBF decreased to a similar extent. The relation between CO and CBF in ME/CFS patients with postural orthostatic tachycardia syndrome (POTS) is unknown. Therefore, the aim of this study is to assess the relation between CBF and CO, in ME/CFS patients with POTS. The methods used in this retrospective study analyze this relation in a large group of patients. We also analyzed the influence of clinical data. A total of 260 ME/CFS patients with POTS underwent tilt testing with measurements of HR, BP, CBF, CO, and end-tidal PCO₂. We measured CBF using extracranial Doppler flow velocity and vessel diameters obtained with a General Electric echo system, and suprasternal aortic flow velocities were measured using the same device. We recorded end-tidal PCO₂ using a Nonin Lifesense device. Results: End-tilt HR and the HR increase were significantly higher in the patients with a %CO reduction ≥ −15% than in the other group. End-tilt CO was higher and the %CO reduction was lower in patients with %CO reduction ≥ −15% than in the other group. CBF data (supine, end-tilt and the %CBF reduction) were not different between the two patient groups. The use of HR increases and %SV reductions were not as discriminative as the %CO reduction. Conclusions: In ME/CFS patients with POTS during tilt testing with measurements of both the CO and the CBF, two different patterns were observed: (1) appr. two-thirds of patients had an almost 1:1 relation between the %CBF reduction and the %CO reduction. (2) Appr. one-third of patients showed a limited reduction in CO together with a substantial increase in HR. In these patients, there was no relation between the CO and CBF reduction. These data suggest the presence of a hyperadrenergic response. Full article

This study introduces a novel wearable Inertial Measurement Unit (IMU)-based system for an objective and comprehensive assessment of Work-Related Musculoskeletal Disorders (WMSDs), thus enhancing workplace safety. The system integrates wearable technology with a user-friendly interface, providing magnetometer-free orientation estimation, joint angle measurements, and WMSDs risk evaluation. Tested in a cable manufacturing facility, the system was evaluated with ten female employees. The evaluation involved work cycle identification, inter-subject comparisons, and benchmarking against standard WMSD risk assessments like RULA, REBA, Strain Index, and Rodgers Muscle Fatigue Analysis. The evaluation demonstrated uniform joint patterns across participants ($ICC=0.72\pm 0.23$) and revealed a higher occurrence of postures warranting further investigation, which is not easily detected by traditional methods such as RULA. The experimental results showed that the proposed system’s risk assessments closely aligned with the established methods and enabled detailed and targeted risk assessments, pinpointing specific bodily areas for immediate ergonomic interventions. This approach not only enhances the detection of ergonomic risks but also supports the development of personalized intervention strategies, addressing common workplace issues such as tendinitis, low back pain, and carpal tunnel syndrome. The outcomes highlight the system’s sensitivity and specificity in identifying ergonomic hazards. Future efforts should focus on broader validation and exploring the relative influence of various WMSDs risk factors to refine risk assessment and intervention strategies for improved applicability in occupational health. Full article

Driver mental fatigue is considered a major factor affecting driver behavior that may result in fatal accidents. Several approaches are addressed in the literature to detect fatigue behavior in a timely manner through either physiological or in-vehicle measurement methods. However, the literature lacks the implementation of hybrid approaches that combine the strength of individual approaches to develop a robust fatigue detection system. In this regard, a hybrid temporal approach is proposed in this paper to detect driver mental fatigue through the combination of driver postural configuration with vehicle longitudinal and lateral behavior on a study sample of 34 diverse participants. A novel fully adaptive symbolic aggregate approximation (faSAX) algorithm is proposed, which adaptively segments and assigns symbols to the segmented time-variant fatigue patterns according to the discrepancy in postural behavior and vehicle parameters. These multivariate symbols are then combined to prepare the bag of words (text format dataset), which is further processed to generate a semantic report of the driver’s status and vehicle situations. The report is then analyzed by a natural language processing scheme working as a sequence-to-label classifier that detects the driver’s mental state and a possible outcome of the vehicle situation. The ground truth of report formation is validated against measurements of mental fatigue through brain signals. The experimental results show that the proposed hybrid system successfully detects time-variant driver mental fatigue and drowsiness states, along with vehicle situations, with an accuracy of 99.6% compared to state-of-the-art systems. The limitations of the current work and directions for future research are also explored. Full article

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic disease of unknown etiology, sharing a similar clinical presentation with the increasingly recognized post-COVID syndrome. We performed the first cross-sectional study of ME/CFS in a community population in Russia. Then we described and compared some clinical and pathophysiological characteristics of ME/CFS and post-COVID syndrome as neuroimmune disorders. Of the cohort of 76 individuals who suggested themselves as suffering from ME/CFS, 56 were diagnosed with ME/CFS by clinicians according to ≥1 of the four most commonly used case definitions. Of the cohort of 14 individuals with post-COVID-19 syndrome, 14 met the diagnostic criteria for ME/CFS. The severity of anxiety/depressive symptoms did not correlate with the severity of fatigue either in ME/CFS or in post-COVID ME/CFS. Still, a positive correlation was found between the severity of fatigue and 20 other symptoms of ME/CFS related to the domains of “post-exertional exhaustion”, “immune dysfunction”, “sleep disturbances”, “dysfunction of the autonomic nervous system”, “neurological sensory/motor disorders” and “pain syndromes”. Immunological abnormalities were identified in 12/12 patients with ME/CFS according to the results of laboratory testing. The prevalence of postural orthostatic tachycardia assessed in the active orthostatic test amounted to 37.5% in ME/CFS and 75.0% in post-COVID ME/CFS (the latter was higher than in healthy controls, p = 0.02). There was a more pronounced increase in heart rate starting from the 6th minute of the test in post-COVID ME/CFS compared with the control group. Assessment of the functional characteristics of microcirculation by laser doppler flowmetry revealed obvious and very similar changes in ME/CFS and post-COVID ME/CFS compared to the healthy controls. The identified laser doppler flowmetry pattern corresponded to the hyperemic form of microcirculation disorders usually observed in acute inflammatory response or in case of systemic vasoconstriction failure. Full article

Prolonged sitting and inadequate sleep can impact driving performance. Therefore, objective knowledge of a driver’s recent sitting and sleep history could help reduce safety risks. This study aimed to apply deep learning to raw accelerometry data collected during a simulated driving task to classify recent sitting and sleep history. Participants (n = 84, Mean ± SD age = 23.5 ± 4.8, 49% Female) completed a seven-day laboratory study. Raw accelerometry data were collected from a thigh-worn accelerometer during a 20-min simulated drive (8:10 h and 17:30 h each day). Two convolutional neural networks (CNNs; ResNet-18 and DixonNet) were trained to classify accelerometry data into four classes (sitting or breaking up sitting and 9-h or 5-h sleep). Accuracy was determined using five-fold cross-validation. ResNet-18 produced higher accuracy scores: 88.6 ± 1.3% for activity (compared to 77.2 ± 2.6% from DixonNet) and 88.6 ± 1.1% for sleep history (compared to 75.2 ± 2.6% from DixonNet). Class activation mapping revealed distinct patterns of movement and postural changes between classes. Findings demonstrate the suitability of CNNs in classifying sitting and sleep history using thigh-worn accelerometer data collected during a simulated drive. This approach has implications for the identification of drivers at risk of fatigue-related impairment. Full article

Neurotransmitter release during trains of activity usually involves two vesicle pools (readily releasable pool, or RRP, and reserve pool, or RP) and two exocytosis mechanisms (“full-collapse” and “kiss-and-run”). However, synaptic terminals are adapted to differing patterns of use and the relationship of these factors to enabling terminals to adapt to differing transmitter release demands is not clear. We have therefore tested their contribution to a terminal’s ability to maintain release, or synaptic fatiguability in motor terminals innervating fast-twitch (fatiguable), and postural slow-twitch (fatigue-resistant) muscles. We used electrophysiological recording of neurotransmission and fluorescent dye markers of vesicle recycling to compare the effects of kinase inhibitors of varying myosin light chain kinase (MLCK) selectivity (staurosporine, wortmannin, LY294002 & ML-9) on vesicle pools, exocytosis mechanisms, and sustained neurotransmitter release, using postural-type activity train (20 Hz for 10 min) in these muscles. In both muscles, a small, rapidly depleted vesicle pool (the RRP) was inhibitor insensitive, continuing to release FM1-43, which is a marker of full-collapse exocytosis. MLCK-inhibiting kinases blocked all remaining FM1-43 loss from labelled vesicles. However, FM2-10 release only slowed, indicating continuing kiss-and-run exocytosis. Despite this, kinase inhibitors did not affect transmitter release fatiguability under normal conditions. However, augmenting release in high Ca²⁺ entirely blocked the synaptic fatigue-resistance of terminals in slow-twitch muscles. Thus, full-collapse exocytosis from most vesicles (the RP) is not essential for maintaining release during a single prolonged train. However, it becomes critical in fatigue-resistant terminals during high vesicle demand. Full article