Driver Fatigue Detection Using Heart Rate Variability Features from 2-Minute Electrocardiogram Signals While Accounting for Sex Differences.

Traffic accidents due to fatigue account for a large proportion of road fatalities. Based on simulated driving experiments with drivers recruited from college students, this paper investigates the use of heart rate variability (HRV) features to detect driver fatigue while considering sex differences. Sex-independent and sex-specific differences in HRV features between alert and fatigued states derived from 2 min electrocardiogram (ECG) signals were determined. Then, decision trees were used for driver fatigue detection using the HRV features of either all subjects or those of only males or females. Nineteen, eighteen, and thirteen HRV features were significantly different (Mann-Whitney U test, p < 0.01) between the two mental states for all subjects, males, and females, respectively. The fatigue detection models for all subjects, males, and females achieved classification accuracies of 86.3%, 94.8%, and 92.0%, respectively. In conclusion, sex differences in HRV features between drivers' mental states were found according to both the statistical analysis and classification results. By considering sex differences, precise HRV feature-based driver fatigue detection systems can be developed. Moreover, in contrast to conventional methods using HRV features from 5 min ECG signals, our method uses HRV features from 2 min ECG signals, thus enabling more rapid driver fatigue detection.

Sleep profiles of different psychiatric traits.

Disturbed sleep comes in many forms. While the key role of sleep in mental health is undisputed, our understanding of the type of sleeping problems that manifest in the early stages of psychiatric disorders is limited. A sample without psychiatric diagnoses (N = 440, 341 women, 97 men, 2 non-binaries; Mage = 32.1, SD = 9.4, range 18-77) underwent a comprehensive assessment, evaluating eight sleep features and 13 questionnaires on common psychiatric complaints. Results revealed that traits of affect disorders, generalized anxiety, and ADHD had the worst sleep profiles, while autism disorder, eating disorder, and impulsivity traits showed milder sleep issues. Mania was the only trait associated with an overall better sleep profile. Across traits, insomnia and fatigue dominated and sleep variability was least prominent. These findings provide support for both transdiagnostic and disorder-specific targets for prevention and treatment.

Medical intelligence using PPG signals and hybrid learning at the edge to detect fatigue in physical activities.

The educational environment plays a vital role in the development of students who participate in athletic pursuits both in terms of their physical health and their ability to detect fatigue. As a result of recent advancements in deep learning and biosensors benefitting from edge computing resources, we are now able to monitor the physiological fatigue of students participating in sports in real time. These devices can then be used to analyze the data using contemporary technology. In this paper, we present an innovative deep learning framework for forecasting fatigue in athletic students following physical exercise. It addresses the issue of lack of precision computational models and extensive data analysis in current approaches to monitoring students' physical activity. In our study, we classified fatigue and non-fatigue based on photoplethysmography (PPG) signals. Several deep learning models are compared in the study. Using limited training data, determining the optimal parameters for PPG presents a significant challenge. For datasets containing many data points, several models were trained using PPG signals: a deep residual network convolutional neural network (ResNetCNN) ResNetCNN, an Xception architecture, a bidirectional long short-term memory (BILSTM), and a combination of these models. Training and testing datasets were assigned using a fivefold cross validation approach. Based on the testing dataset, the model demonstrated a proper classification accuracy of 91.8%.

Previously healthy unvaccinated adults have significant functional limitations in the medium and long term after mild COVID-19.

BACKGROUND AND OBJECTIVES: Ongoing symptoms of COVID-19 can persist for weeks or months after the initial COVID-19 infection. The aim of this study was to identify persistent symptoms (fatigue, cognition, quality of life, anxiety, depression and physical measures) in unvaccinated community-managed patients following COVID-19 infection. METHOD: This was a prospective nested observational study of health and wellbeing measures determined seven and 13 months after COVID-19 infection, alongside physical abilities after 18 months. RESULTS: Data analyses were completed on 62 participants (60% female, median age 35 years). Severe fatigue was noted in 47% of participants at seven months and this had not improved significantly by 13 months (45%). Quality of life and mental health scores were significantly worse in individuals with severe fatigue. One-quarter of participants demonstrated mild cognitive impairment at seven months. After 18 months, walking and lung function were normal, but grip strength was reduced in 26% of participants. DISCUSSION: A significant proportion of unvaccinated COVID-19 patients had not returned to pre-illness levels of health and function after one year; screening functional ability and mental wellbeing is warranted in unvaccinated people with COVID-19.

A follow-up study on respiratory outcomes, quality of life and performance perception of SARS-CoV-2 primary and reinfection in elite athletes: A 9-month prospective study.

The prolonged consequences of SARS-CoV-2 on young elite athletes recovering from primary and reinfection are unclear. This study aimed to assess inspiratory/expiratory muscle strength and respiratory function at the time of spontaneous recovery at 3, 6, and 9 months after SARS-CoV-2 primary and reinfection in elite athletes. The study enrolled 25 elite male judoists, including 11 primary infection cases, five reinfection cases, and nine controls from the Türkiye Olympic Preparation Center. Inspiratory/expiratory muscle strength and respiratory function were measured, including maximal inspiratory pressure (MIP), maximal expiratory pressure (MEP), forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, and peak expiratory flow (PEF) before and up to 9 months after SARS-CoV-2 infection in the early pre-competition preparation phases. The most common symptoms reported by reinfection cases were fatigue (80%), dyspnea (60%), and muscle/joint pain (60%), while primary infection cases reported fatigue (73%), muscle/joint pain (45%), and headache (45%). MIP decreased by -14% and MEP decreased by -13% following the SARS-CoV-2 infection in reinfection cases. Likewise, FEV1 and FVC decreased by -5% and -8%, respectively; consequently, FEV1/FVC increased by 3%. Inspiratory/expiratory muscle strength and respiratory function improved rapidly after 9 months of SARS-CoV-2 infection in primary cases, whereas dysfunction persisted in reinfection cases. PEF was unaffected throughout the 9-month follow-up period. Reinfection may lead to further alterations in respiratory system relative to the primary infection, with a suspected restrictive pattern that remains dysfunctional in the third month; however, it improves significantly during a 9-month follow-up period.

Circadian Disruption in Civilian Airline Pilots.

INTRODUCTION: Most airline pilots reported having suffered from sleep disorders and fatigue due to circadian disruption, a potential risk to flight safety. This study attempted to uncover the actual scenario of circadian disruption and working load status among airline pilots.METHODS: In study 1, 21 pilots were invited to participate in a 14-d sleep monitoring and a dual 2-back test to monitor their sleep patterns and cognitive function level. To provide an in-depth view, data from scheduled flights, including 567 airline pilots, was analyzed in Study 2. The present study used cluster analysis to reflect the distribution of the flight scheduling characteristics, including working time and actual working hours. A simulation model was then developed to predict the pilots' 1-mo sleep-wake pattern.RESULTS: The results indicated that sleep problems were prevalent in this population, especially the night before an earlier morning shift. Regarding the cognitive test, they scored the lowest on earlier morning shifts compared with daytime and evening shifts. It was found that over 70% of the flight schedules can lead to circadian disruption, and 47.44% of the pilots worked under high-load status.DISCUSSION: Airline pilots inevitably work irregular hours and the current policies for coping with circadian disruption seem inefficient. This study thus calls for urgency in improving scheduling and fatigue management systems from the circadian rhythm perspective.Yang SX, Cheng S, Sun Y, Tang X, Huang Z. Circadian disruption in civilian airline pilots. Aerosp Med Hum Perform. 2024; 95(7):381-389.

Disrupted hemodynamic response within dorsolateral prefrontal cortex during cognitive tasks among people with multiple sclerosis-related fatigue.

INTRODUCTION: Mental fatigue is an early and enduring symptom in persons with autoimmune disease particularly multiple sclerosis (MS). Neuromodulation has emerged as a potential treatment although optimal cortical targets have yet to be determined. We aimed to examine cortical hemodynamic responses within bilateral dorsolateral prefrontal cortex (dlPFC) and frontopolar areas during single and dual cognitive tasks in persons with MS-related fatigue compared to matched controls. METHODS: We recruited persons (15 MS and 12 age- and sex-matched controls) who did not have physical or cognitive impairment and were free from depressive symptoms. Functional near infrared spectroscopy (fNIRS) registered hemodynamic responses during the tasks. We calculated oxyhemoglobin peak, time-to-peak, coherence between channels (a potential marker of neurovascular coupling) and functional connectivity (z-score). RESULTS: In MS, dlPFC demonstrated disrupted hemodynamic coherence during both single and dual tasks, as evidenced by non-significant and negative correlations between fNIRS channels. In MS, reduced coherence occurred in left dorsolateral PFC during the single task but occurred bilaterally as the task became more challenging. Functional connectivity was lower during dual compared to single tasks in the right dorsolateral PFC in both groups. Lower z-score was related to greater feelings of fatigue. Peak and time-to-peak hemodynamic response did not differ between groups or tasks. CONCLUSIONS: Hemodynamic responses were inconsistent and disrupted in people with MS experiencing mental fatigue, which worsened as the task became more challenging. Our findings point to dlPFC, but not frontopolar areas, as a potential target for neuromodulation to treat cognitive fatigue.

Connecting the dots: the role of fatigue in female infertility.

Fatigue, an increasingly acknowledged symptom in various chronic diseases, has garnered heightened attention, during the medical era of bio-psycho-social model. Its persistence not only significantly compromises an individual's quality of life but also correlates with chronic organ damage. Surprisingly, the intricate relationship between fatigue and female reproductive health, specifically infertility, remains largely unexplored. Our exploration into the existing body of evidence establishes a compelling link between fatigue with uterine and ovarian diseases, as well as conditions associated with infertility, such as rheumatism. This observation suggests a potentially pivotal role of fatigue in influencing overall female fertility. Furthermore, we propose a hypothetical mechanism elucidating the impact of fatigue on infertility from multiple perspectives, postulating that neuroendocrine, neurotransmitter, inflammatory immune, and mitochondrial dysfunction resulting from fatigue and its co-factors may further contribute to endocrine disorders, menstrual irregularities, and sexual dysfunction, ultimately leading to infertility. In addition to providing this comprehensive theoretical framework, we summarize anti-fatigue strategies and accentuate current knowledge gaps. By doing so, our aim is to offer novel insights, stimulate further research, and advance our understanding of the crucial interplay between fatigue and female reproductive health.

Habitual physical activity and COVID-19.

BACKGROUND: Physical activity (PA) is known to decrease COVID-19 risk factors and can attenuate symptoms of viral infections. However, difficulty exercising and fatigue are common complaints after COVID-19. It is unknown whether prior habitual PA will improve outcomes and what the time course is until full recovery of PA after COVID-19. METHODS: Invitations were emailed to 21,933 adults who were SARS-CoV-2 positive between March 2020 and February 2021. Participants completed intake surveys and the Physical Activity History (PAH) questionnaire regarding PA during the 3-month prior to infection. Monthly thereafter, for up to 23 months, participants were emailed surveys. Scores were computed for moderate and heavy PA. Long COVID (LC) was defined as having recurring/persistent symptoms 9 months after diagnosis. RESULTS: Overall, 993 patients completed the intake survey (age 50.7±15.8 years, BMI 27.3±9.2, 58% women); 28% had been hospitalized. One-third had recovered to their pre-infection level of PA at 9 months post-infection; this increased to 65% at one year, and 90% at two years. Higher pre-diagnosis PA reduced odds of hospitalization (P<0.05) but not of LC. Factors predictive of poor PA recovery were higher pre-diagnosis PA, shortness of breath and fatigue during acute illness, and fatigue chronically. Participants who reported ongoing symptoms had consistently poorer recovery of habitual PA compared to those not reporting chronic symptoms. CONCLUSIONS: Habitual PA reduced odds of hospitalization but not of LC. Thirty-five percent had not returned to pre-COVID-19 levels of PA one year after infection, representing a major public health threat.

Systematic review of fatigue severity in ME/CFS patients: insights from randomized controlled trials.

BACKGROUND: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating illness medically unexplained, affecting approximately 1% of the global population. Due to the subjective complaint, assessing the exact severity of fatigue is a clinical challenge, thus, this study aimed to produce comprehensive features of fatigue severity in ME/CFS patients. METHODS: We systematically extracted the data for fatigue levels of participants in randomized controlled trials (RCTs) targeting ME/CFS from PubMed, Cochrane Library, Web of Science, and CINAHL throughout January 31, 2024. We normalized each different measurement to a maximum 100-point scale and performed a meta-analysis to assess fatigue severity by subgroups of age, fatigue domain, intervention, case definition, and assessment tool, respectively. RESULTS: Among the total of 497 relevant studies, 60 RCTs finally met our eligibility criteria, which included a total of 7088 ME/CFS patients (males 1815, females 4532, and no information 741). The fatigue severity of the whole 7,088 patients was 77.9 (95% CI 74.7-81.0), showing 77.7 (95% CI 74.3-81.0) from 54 RCTs in 6,706 adults and 79.6 (95% CI 69.8-89.3) from 6 RCTs in 382 adolescents. Regarding the domain of fatigue, 'cognitive' (74.2, 95% CI 65.4-83.0) and 'physical' fatigue (74.3, 95% CI 68.3-80.3) were a little higher than 'mental' fatigue (70.1, 95% CI 64.4-75.8). The ME/CFS participants for non-pharmacological intervention (79.1, 95% CI 75.2-83.0) showed a higher fatigue level than those for pharmacological intervention (75.5, 95% CI 70.0-81.0). The fatigue levels of ME/CFS patients varied according to diagnostic criteria and assessment tools adapted in RCTs, likely from 54.2 by ICC (International Consensus Criteria) to 83.6 by Canadian criteria and 54.2 by MFS (Mental Fatigue Scale) to 88.6 by CIS (Checklist Individual Strength), respectively. CONCLUSIONS: This systematic review firstly produced comprehensive features of fatigue severity in patients with ME/CFS. Our data will provide insights for clinicians in diagnosis, therapeutic assessment, and patient management, as well as for researchers in fatigue-related investigations.

Perceived and physiological strains of societal participation in people with multiple sclerosis: a real-time assessment study.

OBJECTIVE: To examine the relationship between perceived and physiological strains of real-time societal participation in people with multiple sclerosis. DESIGN: Observational study. SUBJECTS/PATIENTS: 70 people with multiple sclerosis. METHODS: Perceived and physiological strain of societal participation (10 participation-at-location and 9 transport domains) were measured in real time using the Whereabouts smartphone app and Fitbit over 7 consecutive days. Longitudinal relationships between perceived (1 not strenuous to 10 most strenuous) and physiological strains (heart rate reserve) were examined using mixed-model analyses. Type of event (participation-at-location or transport) was added as covariate, with further adjustments for fatigue and walking ability. RESULTS: Median perceived strain, summarized for all societal participation domains, varied between 3 and 6 (range: 1-10), whereas physiological strain varied between 18.5% and 33.2% heart rate reserve. Perceived strain (outcome) and physiological strain were not associated (ß -0.001, 95%CI -0.008; 0.005, with a 7-day longitudinal correlation coefficient of -0.001). Transport domains were perceived as less strenuous (ß -0.80, 95%CI -0.92; -0.68). Higher fatigue levels resulted in higher perceived strain (all societal participation domains) (ß 0.05, 95%CI 0.02; 0.08). CONCLUSION: Societal participation resulted in low-to-moderate perceived and physiological strain. Perceived and physiological strain of societal participation were unrelated and should be considered different constructs in multiple sclerosis.

Exploring the impact of cognitive dysfunction, fatigue, and shortness of breath on activities of daily life after COVID-19 infection, until 1-year follow-up.

OBJECTIVE: Despite expanding knowledge on COVID-19,  the long-term effects on daily-life activities remain unclear. The prevalence and changes in fatigue, cognitive dysfunction, and activity limitations in the first year after COVID-19 infection in hospitalized and non-hospitalized patients were explored. SUBJECTS: A total of 122 patients were recruited from hospital care and 90 from primary care. METHOD: Baseline data comprised the Montreal Cognitive Assessment and Trail Making Test. Participants were followed up at 3 and 12 months using these tests and a semi-structured interview to identify symptoms and how they affected participation in daily-life activities. Both within- and between-group analyses were performed to explore changes over time and compare groups. RESULT: High levels of fatigue and cognitive dysfunction were found in both groups, which persisted for 12 months. A significant impact on daily-life activities was also observed, with marginal change at the 12-month follow-up. The hospital care group performed worse than the primary care group in the cognitive tests, although the primary care group perceived a higher level of fatigue and cognitive dysfunction. Activity limitations were higher in the primary care group than in the hospital care group. CONCLUSION: These findings highlight the need for long-term follow-up and further investigation of the impact of persistent deficits on rehabilitation.

A cross-scenario and cross-subject domain adaptation method for driving fatigue detection.

Objective.The scarcity of electroencephalogram (EEG) data, coupled with individual and scenario variations, leads to considerable challenges in real-world EEG-based driver fatigue detection. We propose a domain adaptation method that utilizes EEG data collected from a laboratory to supplement real-world EEG data and constructs a cross-scenario and cross-subject driver fatigue detection model for real-world scenarios.Approach.First, we collect EEG data from subjects participating in a driving experiment conducted in both laboratory and real-world scenarios. To address the issue of data scarcity, we build a real-world fatigued driving detection model by integrating the real-world data with the laboratory data. Then, we propose a method named cross-scenario and cross-subject domain adaptation (CS2DA), which aims to eliminate the domain shift problem caused by individual variances and scenario differences. Adversarial learning is adopted to extract the common features observed across different subjects within the same scenario. The multikernel maximum mean discrepancy (MK-MMD) method is applied to further minimize scenario differences. Additionally, we propose a conditional MK-MMD constraint to better utilize label information. Finally, we use seven rules to fuse the predicted labels.Main results.We evaluate the CS2DA method through extensive experiments conducted on the two EEG datasets created in this work: the SEED-VLA and the SEED-VRW datasets. Different domain adaptation methods are used to construct a real-world fatigued driving detection model using data from laboratory and real-world scenarios, as well as a combination of both. Our findings show that the proposed CS2DA method outperforms the existing traditional and adversarial learning-based domain adaptation approaches. We also find that combining data from both laboratory and real-world scenarios improves the performance of the model.Significance.This study contributes two EEG-based fatigue driving datasets and demonstrates that the proposed CS2DA method can effectively enhance the performance of a real-world fatigued driving detection model.

[THE MUSCULAR COMPONENT OF FIBROMYALGIA PATHOPHYSIOLOGY].

INTRODUCTION: Fibromyalgia syndrome (FMS) is a chronic pain syndrome, prevalent in women more than men. The main symptoms are widespread musculoskeletal pain, fatigue, and weakness. To date, the pathophysiological mechanisms are unclear, and there are several pathogenic theories elucidating this condition. In this review, we summarized articles published in the past few years, regarding the effect of musculoskeletal dysfunction on FMS. We focused on the musculoskeletal system and central nervous system (CNS) disarrays.

Individual Variability in Brain Connectivity Patterns and Driving-Fatigue Dynamics.

Mental fatigue during driving poses significant risks to road safety, necessitating accurate assessment methods to mitigate potential hazards. This study explores the impact of individual variability in brain networks on driving fatigue assessment, hypothesizing that subject-specific connectivity patterns play a pivotal role in understanding fatigue dynamics. By conducting a linear regression analysis of subject-specific brain networks in different frequency bands, this research aims to elucidate the relationships between frequency-specific connectivity patterns and driving fatigue. As such, an EEG sustained driving simulation experiment was carried out, estimating individuals' brain networks using the Phase Lag Index (PLI) to capture shared connectivity patterns. The results unveiled notable variability in connectivity patterns across frequency bands, with the alpha band exhibiting heightened sensitivity to driving fatigue. Individualized connectivity analysis underscored the complexity of fatigue assessment and the potential for personalized approaches. These findings emphasize the importance of subject-specific brain networks in comprehending fatigue dynamics, while providing sensor space minimization, advocating for the development of efficient mobile sensor applications for real-time fatigue detection in driving scenarios.

Transcranial magnetic stimulation in the assessment of acupuncture effect on exercise-induced fatigue.

BACKGROUND: Acupuncture as a traditional Chinese medicine therapy relies on unique theories to alleviate fatigue. The aim of this study is to evaluate the effect of acupuncture on exercise-induced fatigue utilizing transcranial magnetic stimulation (TMS). METHODS: A total of 20 participants with regular exercise habits were recruited for this study. All participants were randomly assigned to receive either acupuncture or sham acupuncture intervention for exercise-induced fatigue. TMS and a heart rate monitor were used to measure the amplitude and latency of motor evoked potential (MEP) as well as heart rate every 5 min over a 30-min period. The blood lactic acid (BLA) levels were measured using Lactate Scout+ at baseline, 0 min, and 30 min after fatigue. Two-way repeated measures analysis of variance was utilized to compare the differences between the effects of acupuncture method and time. Bonferroni post hoc tests were conducted to compare specific differences. Statistical significance was set at p < .05. RESULTS: Interaction effect was observed between acupuncture method and time effect in terms of amplitude (F(1, 38) = 5.40, p < .001, η2 = 0.12) and latency (F(1, 38) = 3.78, p = .008, η2 = .09) of MEP. The application of acupuncture can promote the recovery of heart rate especially at 30 min (p < .05), but which seem insufficient to generate significant difference in BLA (F(1, 38) = 0.067, p = .797, η2 = 0.002). CONCLUSIONS: Acupuncture can promote the increase of MEP amplitude, shorten MEP latency, and restore heart rate. Preliminary findings provide novel insights for individuals with exercise habits to alleviate fatigue and enhance sports performance.

The Influence of Fatigue, Recovery, and Environmental Factors on the Body Stability of Construction Workers.

In the construction industry, falls, slips, and trips (FST) account for 42.3% of all accidents. The primary cause of FST incidents is directly related to the deterioration of workers' body stability. To prevent FST-related accidents, it is crucial to understand the interaction between physical fatigue and body stability in construction workers. Therefore, this study investigates the impact of fatigue on body stability in various construction site environments using Dynamic Time Warping (DTW) analysis. We conducted experiments reflecting six different fatigue levels and four environmental conditions. The analysis process involves comparing changes in DTW values derived from acceleration data obtained through wearable sensors across varying fatigue levels and construction environments. The results reveal the following changes in DTW values across different environments and fatigue levels: for non-obstacle, obstacle, water, and oil conditions, DTW values tend to increase as fatigue levels rise. In our experiments, we observed a significant decrease in body stability against external environments starting from fatigue Levels 3 or 4 (30% and 40% of the maximum failure point). In the non-obstacle condition, the DTW values were 9.4 at Level 0, 12.8 at Level 3, and 23.1 at Level 5. In contrast, for the oil condition, which exhibited the highest DTW values, the values were 10.5 at Level 0, 19.1 at Level 3, and 34.5 at Level 5. These experimental results confirm that the body stability of construction workers is influenced by both fatigue levels and external environmental conditions. Further analysis of recovery time, defined as the time it takes for body stability to return to its original level, revealed an increasing trend in recovery time as fatigue levels increased. This study quantitatively demonstrates through wearable sensor data that, as fatigue levels increase, workers experience decreased body stability and longer recovery times. The findings of this study can inform individual worker fatigue management in the future.

Resistance training in women with myotonic dystrophy type 1: a multisystemic therapeutic avenue.

Myotonic dystrophy type 1 (DM1) is a hereditary disease characterized by muscular impairments. Fundamental and clinical positive effects of strength training have been reported in men with DM1, but its impact on women remains unknown. We evaluated the effects of a 12-week supervised strength training on physical and neuropsychiatric health. Women with DM1 performed a twice-weekly supervised resistance training program (3 series of 6-8 repetitions of squat, leg press, plantar flexion, knee extension, and hip abduction). Lower limb muscle strength, physical function, apathy, anxiety and depression, fatigue and excessive somnolence, pain, and patient-reported outcomes were assessed before and after the intervention, as well as three and six months after completion of the training program. Muscle biopsies of the vastus lateralis were also taken before and after the training program to assess muscle fiber growth. Eleven participants completed the program (attendance: 98.5 %). Maximal hip and knee extension strength (p < 0.006), all One-Repetition Maximum strength measures (p < 0.001), apathy (p = 0.0005), depression (p = 0.02), pain interference (p = 0.01) and perception of the lower limb function (p = 0.003) were significantly improved by training. Some of these gains were maintained up to six months after the training program. Strength training is a good therapeutic strategy for women with DM1.

Evaluation of walking activity and gait to identify physical and mental fatigue in neurodegenerative and immune disorders: preliminary insights from the IDEA-FAST feasibility study.

BACKGROUND: Many individuals with neurodegenerative (NDD) and immune-mediated inflammatory disorders (IMID) experience debilitating fatigue. Currently, assessments of fatigue rely on patient reported outcomes (PROs), which are subjective and prone to recall biases. Wearable devices, however, provide objective and reliable estimates of gait, an essential component of health, and may present objective evidence of fatigue. This study explored the relationships between gait characteristics derived from an inertial measurement unit (IMU) and patient-reported fatigue in the IDEA-FAST feasibility study. METHODS: Participants with IMIDs and NDDs (Parkinson's disease (PD), Huntington's disease (HD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary Sjogren's syndrome (PSS), and inflammatory bowel disease (IBD)) wore a lower-back IMU continuously for up to 10 days at home. Concurrently, participants completed PROs (physical fatigue (PF) and mental fatigue (MF)) up to four times a day. Macro (volume, variability, pattern, and acceleration vector magnitude) and micro (pace, rhythm, variability, asymmetry, and postural control) gait characteristics were extracted from the accelerometer data. The associations of these measures with the PROs were evaluated using a generalised linear mixed-effects model (GLMM) and binary classification with machine learning. RESULTS: Data were recorded from 72 participants: PD = 13, HD = 9, RA = 12, SLE = 9, PSS = 14, IBD = 15. For the GLMM, the variability of the non-walking bouts length (in seconds) with PF returned the highest conditional R2, 0.165, and with MF the highest marginal R2, 0.0018. For the machine learning classifiers, the highest accuracy of the current analysis was returned by the micro gait characteristics with an intrasubject cross validation method and MF as 56.90% (precision = 43.9%, recall = 51.4%). Overall, the acceleration vector magnitude, bout length variation, postural control, and gait rhythm were the most interesting characteristics for future analysis. CONCLUSIONS: Counterintuitively, the outcomes indicate that there is a weak relationship between typical gait measures and abnormal fatigue. However, factors such as the COVID-19 pandemic may have impacted gait behaviours. Therefore, further investigations with a larger cohort are required to fully understand the relationship between gait and abnormal fatigue.

Intrinsic and extrinsic variables impacting upper quarter Y-balance test scores in sporting cohorts: A systematic review.

INTRODUCTION: The upper quarter y-balance test (YBT-UQ) is a functional screening tool used to detect musculoskeletal injury risk, aid rehabilitation, and monitor dynamic function, strength and control, yet little is currently known about intrinsic and extrinsic factors that influence reach scores. OBJECTIVES: This systematic review aimed to determine if age, sex, or interventions influenced reach scores and whether between-limb differences were common in non-injured sporting populations, with a secondary aim to identify if sport impacted YBT-UQ reach. METHODS: Web of Science, PubMed, and SportDiscus were systematically searched from January 2012 to November 16, 2023, revealing twenty-three studies satisfying inclusion criteria of published in English between 2012 and 2023, healthy participants of any age including both males and females, athletic populations, YBT-UQ use to assess upper limb mobility/stability, report normalised reach scores, and peer-reviewed full-texts. Methodological quality was evaluated via National Institutes of Health (NIH) quality assessment tools for controlled interventions, observational cohort and cross-sectional designs, and pre-post with no control group. RESULTS: Age, sex, sport, and fatigue were influencing factors; greater reach scores were achieved in older athletes (i.e. >18 years), males, and in a well-rested state. Between-limb differences were not common in sporting populations; therefore, asymmetries may be useful for practitioners to aid injury risk identification. CONCLUSION: This is the first systematic review investigating YBT-UQ influencing factors and thereby provides context for clinicians regarding characteristics that impact reach scores in sporting populations, from which normative values could be determined and further aid clinical decisions or areas to improve regarding injury risk.