Non-Invasive Physiological Monitoring for Physical Exertion and Fatigue Assessment in Military Personnel: A Systematic Review

Complementary and Integrative Medicine Prevalence and Utilization in International Military and Veteran Settings and Communities: A Systematic Review

INTRODUCTION

Active duty military personnel and veterans have unique and complex health needs, with the high demands of military life often leading to chronic physical and mental health conditions. Complementary and integrative medicine (CIM) could be a possible solution to this problem. Some military health systems have started integrating CIM into health care delivery. However, there has been no systematic evaluation of the prevalence and utilization of CIM in military and veteran populations globally.

MATERIALS AND METHODS

A Preferred Reporting Items For Systematic Reviews and Meta-Analysis Protocols protocol was used to systematically search for original research assessing the prevalence and utilization of CIM among active serving military or veterans. CINAHL, MEDLINE, Scopus, and AMED databases were searched up to February 3, 2023.

RESULTS

A total of 27 studies met the inclusion criteria and were included in this review. The overall quality of evidence was high with a low risk of bias. Utilization of CIM varied. The lowest utilization demonstrated that only 1.9% of services delivered by military health system were CIM. The majority of studies found utilization rates between 30% and 80%, with some studies reporting use as high as 90%. The most commonly used CIM therapies included chiropractic care, massage, mindfulness/meditation, and acupuncture. Utilization of CIM products was high and ranged from 32% to 87%. The most frequently used products were dietary supplements, particularly multivitamins and minerals and protein supplements/amino acids. The use of herbal products was high among veterans ranging from 10% to 79%.

CONCLUSIONS

The high demand for CIM by military personnel and veterans has important implications for policy, funding allocation, and integration of these services into clinical practice, particularly by countries not currently doing so. Further research is needed to assess the implementation of CIM into real-world settings to explore barriers and facilitators for their use in clinical practice and, by extension, their integration into the wider health care system.

Impact of Fatigue on Ergonomic Risk Scores and Foot Kinetics: A Field Study Employing Inertial and In-Shoe Plantar Pressure Measurement Devices

(1) Background: Occupational fatigue is a primary factor leading to work-related musculoskeletal disorders (WRMSDs). Kinematic and kinetic experimental studies have been able to identify indicators of WRMSD, but research addressing real-world workplace scenarios is lacking. Hence, the authors of this study aimed to assess the influence of physical strain on the Borg CR-10 body map, ergonomic risk scores, and foot pressure in a real-world setting. (2) Methods: Twenty-four participants (seventeen men and seven women) were included in this field study. Inertial measurement units (IMUs) (n = 24) and in-shoe plantar pressure measurements (n = 18) captured the workload of production and office workers at the beginning of their work shift and three hours later, working without any break. In addition to the two 12 min motion capture processes, a Borg CR-10 body map and fatigue visual analog scale (VAS) were applied twice. Kinematic and kinetic data were processed using MATLAB and SPSS software, resulting in scores representing the relative distribution of the Rapid Upper Limb Assessment (RULA) and Computer-Assisted Recording and Long-Term Analysis of Musculoskeletal Load (CUELA), and in-shoe plantar pressure. (3) Results: Significant differences were observed between the two measurement times of physical exertion and fatigue, but not for ergonomic risk scores. Contrary to the hypothesis of the authors, there were no significant differences between the in-shoe plantar pressures. Significant differences were observed between the dominant and non-dominant sides for all kinetic variables. (4) Conclusions: The posture scores of RULA and CUELA and in-shoe plantar pressure side differences were a valuable basis for adapting one-sided requirements in the work process of the workers. Traditional observational methods must be adapted more sensitively to detect kinematic deviations at work. The results of this field study enhance our knowledge about the use and benefits of sensors for ergonomic risk assessments and interventions.

Effect of Fatigue on Movement Patterns During a Loaded Ruck March

INTRODUCTION

Loaded ruck marching is a common training and operational task for many members of the military. It is known to cause fatigue, affect soldier readiness, and can lead to traumatic and overuse injuries. Quantifying the gait changes that occur over the course of a loaded ruck march may provide a better understanding of injury mechanisms and potentially allow for development of individualized injury-prevention training programs. This study examined the change in soldiers' gait patterns over the course of a loaded ruck march in order to examine the correlation between fatigue and kinematic parameters. Fatigue is a subjective term that may encompass factors such as energy expenditure, muscle exhaustion, and cognitive engagement. Since it can be difficult to quantify, the current study makes the broad assumption that fatigue increases in some (potentially nonlinear) fashion during a loaded ruck march.

METHOD

Three platoons of soldiers participated in a field training exercise with inertial measurement sensors placed on their chests and ankles to record gait parameters throughout a 7-mile ruck march. The effects of fatigue on stride length, stride width, ankle yaw, and torso lean (anterior-posterior [AP] and side-to-side [SS]) were compared using one-way repeated measure analyses of variance.

RESULTS

In comparing the first and last quarters of the ruck march, stride length decreased, stride width increased, stride width variability increased, AP torso lean variability increased, and SS torso lean variability increased.

CONCLUSION

Although they do not describe a direct relationship to injury, these results can inform enhanced approaches to quantify and predict soldier fatigue and more reliably prevent future injury.

Pupillometry as a new window to player fatigue? A glimpse inside the eyes of a Euro Cup Women's Basketball team

A rapidly emerging area of interest in high-pressure environments is that of pupillometry, where handheld quantitative infrared pupillometers (HQIPs) are able to track psycho-physiological fatigue in a fast, objective, valid, reliable, and non-invasive manner. However, the application of HQIPs in the context of athlete monitoring is yet to be determined. Therefore, the main aim of this pilot study was to examine the potential usefulness of a HQIP to monitor game-induced fatigue inside a professional female basketball setting by determining its (1) test-retest repeatability, (2) relationship with other biomarkers of game-induced fatigue, and (3) time-course from rested to fatigued states. A non-ophthalmologic practitioner performed a standardized Pupil Light Reflex (PLR) test using a medically graded HQIP among 9 professional female basketball players (2020-2021 Euro Cup) at baseline, 24-h pre-game (GD-1), 24-h post-game (GD+1) and 48-h post-game (GD+2). This was repeated over four subsequent games, equalling a total of 351 observations per eye. Two out of seven pupillometrics displayed good ICCs (0.95-0.99) (MinD and MaxD). Strong significant relationships were found between MaxD, MinD, and all registered biomarkers of game-induced fatigue (r = 0.69-0.82, p < 0.05), as well as between CV, MCV, and cognitive, lower-extremity muscle, and physiological fatigue markers (r = 0.74-0.76, p < 0.05). Three pupillometrics were able to detect a significant difference between rested and fatigued states. In particular, PC (right) (F = 5.173, η2 = 0.115 p = 0.028) and MCV (right) (F = 3.976, η2 = 0.090 p = 0.049) significantly decreased from baseline to GD+2, and LAT (left) (F = 4.023, η2 = 0.109 p = 0.009) significantly increased from GD-1 to GD+2. HQIPs have opened a new window of opportunity for monitoring game-induced fatigue in professional female basketball players. However, future research initiatives across larger and heterogenous samples, and longer investigation periods, are required to expand upon these preliminary findings.

Psychophysiological Responses in Soldiers during Close Combat: Implications for Occupational Health and Fitness in Tactical Populations

This study explores the psychophysiological responses and subjective exertion experiences of soldiers in simulated hand-to-hand combat, aligning these findings with established physiological benchmarks. Active military personnel were monitored for heart rate, blood lactate levels, subjective exertion, cortical arousal, and muscle strength during combat scenarios. The results showed significant increases in heart rate and blood lactate, indicating intense cardiovascular demands and a reliance on anaerobic energy systems. Contrary to these physiological changes, soldiers reported lower levels of exertion, suggesting a possible underestimation of physical effort or individual differences in perception and mental resilience to stress. Notably, a decrease in cortical arousal post-combat was observed, potentially signaling cognitive function deficits in decision-making and information processing in high-stress environments. This decline was more pronounced than typically seen in other high-stress situations, highlighting the unique cognitive demands of hand-to-hand combat. Additionally, an increase in muscle strength was noted, underscoring the physiological adaptations arising from intensive combat training. These findings provide valuable insights into the psychophysiological effects of hand-to-hand combat, emphasizing the complex interplay between physical exertion, cognitive function, and stress response in military contexts. The study underscores the need for comprehensive training strategies that address both physical and psychological aspects to enhance combat readiness and decision-making under stress.

Occupation-Induced Fatigue and Impacts on Emergency First Responders: A Systematic Review

Fatigue in emergency first responders (EFRs) is known to affect performance abilities and safety outcomes for both patients and EFRs. The primary aim of this review was to determine the main contributors to occupation-induced fatigue in EFRs and its subsequent impacts. Following the PRIMSA checklist, academic databases (Medline, Embase, CINAHL, and SPORTDiscus) were searched using key terms with results subjected to inclusion and exclusion criteria. Populations of interest were firefighters, paramedics, or emergency call centre personnel. Of the 5633 records identified, 43 studies, which reported on 186 unique measures from a total population of 6373 participants, informed the review. Synthesis revealed fatigue was caused by lack of sleep during the shift and consistent poor sleep quality which negatively impacted cognitive function, alertness, and physical and mental health while increasing safety-compromising behaviours and injuries. Both subjective and objective assessments of fatigue are necessary for effective risk management in EFRs. EFRs that are consistently fatigued are at a greater risk of poor physical and mental health, reduced cognitive function, and increased injuries. No studies reported on fatigue in emergency call centre personnel, highlighting a literature gap. Funding was provided by the Australian Capital Territory Emergency Services Agency. Preregistration was filed in OSF: osf.io/26f3s.

Exploring the Applicability of Physiological Monitoring to Manage Physical Fatigue in Firefighters

Physical fatigue reduces productivity and quality of work while increasing the risk of injuries and accidents among safety-sensitive professionals. To prevent its adverse effects, researchers are developing automated assessment methods that, despite being highly accurate, require a comprehensive understanding of underlying mechanisms and variables' contributions to determine their real-life applicability. This work aims to evaluate the performance variations of a previously developed four-level physical fatigue model when alternating its inputs to have a comprehensive view of the impact of each physiological variable on the model's functioning. Data from heart rate, breathing rate, core temperature and personal characteristics from 24 firefighters during an incremental running protocol were used to develop the physical fatigue model based on an XGBoosted tree classifier. The model was trained 11 times with different input combinations resulting from alternating four groups of features. Performance measures from each case showed that heart rate is the most relevant signal for estimating physical fatigue. Breathing rate and core temperature enhanced the model when combined with heart rate but showed poor performance individually. Overall, this study highlights the advantage of using more than one physiological measure for improving physical fatigue modelling. The findings can contribute to variables and sensor selection in occupational applications and as the foundation for further field research.

Peak performance and cardiometabolic responses of modern US army soldiers during heavy, fatiguing vest-borne load carriage

INTRODUCTION

Physiological limits imposed by vest-borne loads must be defined for optimal performance monitoring of the modern dismounted warfighter.

PURPOSE

To evaluate how weighted vests affect locomotion economy and relative cardiometabolic strain during military load carriage while identifying key physiological predictors of exhaustion limits.

METHODS

Fifteen US Army soldiers (4 women, 11 men; age, 26 ± 8 years; height, 173 ± 10 cm; body mass (BM), 79 ± 16 kg) performed four incremental walking tests with different vest loads (0, 22, 44, or 66% BM). We examined the effects of vest-borne loading on peak walking speed, the physiological costs of transport, and relative work intensity. We then sought to determine which of the cardiometabolic indicators (oxygen uptake, heart rate, respiration rate) was most predictive of task failure.

RESULTS

Peak walking speed significantly decreased with successively heavier vest loads (p < 0.01). Physiological costs per kilometer walked were significantly higher with added vest loads for each measure (p < 0.05). Relative oxygen uptake and heart rate were significantly higher during the loaded trials than the 0% BM trial (p < 0.01) yet not different from one another (p > 0.07). Conversely, respiration rate was significantly higher with the heavier load in every comparison (p < 0.01). Probability modeling revealed heart rate as the best predictor of task failure (marginal R², 0.587, conditional R², 0.791).

CONCLUSION

Heavy vest-borne loads cause exceptional losses in performance capabilities and increased physiological strain during walking. Heart rate provides a useful non-invasive indicator of relative intensity and task failure during military load carriage.

Machine Learning Approach to Model Physical Fatigue during Incremental Exercise among Firefighters

Physical fatigue is a serious threat to the health and safety of firefighters. Its effects include decreased cognitive abilities and a heightened risk of accidents. Subjective scales and, recently, on-body sensors have been used to monitor physical fatigue among firefighters and safety-sensitive professionals. Considering the capabilities (e.g., noninvasiveness and continuous monitoring) and limitations (e.g., assessed fatiguing tasks and models validation procedures) of current approaches, this study aimed to develop a physical fatigue prediction model combining cardiorespiratory and thermoregulatory measures and machine learning algorithms within a firefighters' sample. Sensory data from heart rate, breathing rate and core temperature were recorded from 24 participants during an incremental running protocol. Various supervised machine learning algorithms were examined using 21 features extracted from the physiological variables and participants' characteristics to estimate four physical fatigue conditions: low, moderate, heavy and severe. Results showed that the XGBoosted Trees algorithm achieved the best outcomes with an average accuracy of 82% and accuracies of 93% and 86% for recognising the low and severe levels. Furthermore, this study evaluated different methods to assess the models' performance, concluding that the group cross-validation method presents the most practical results. Overall, this study highlights the advantages of using multiple physiological measures for enhancing physical fatigue modelling. It proposes a promising health and safety management tool and lays the foundation for future studies in field conditions.

Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review

The emergence of physiological monitoring technologies has produced exceptional opportunities for real-time collection and analysis of workers' physiological information. To benefit from these safety and health prognostic opportunities, research efforts have explored the applicability of these devices to control workers' wellbeing levels during occupational activities. A systematic review is proposed to summarise up-to-date progress in applying physiological monitoring systems for occupational groups. Adhering with the PRISMA Statement, five databases were searched from 2014 to 2021, and 12 keywords were combined, concluding with the selection of 38 articles. Sources of risk of bias were assessed regarding randomisation procedures, selective outcome reporting and generalisability of results. Assessment procedures involving non-invasive methods applied with health and safety-related goals were filtered. Working-age participants from homogeneous occupational groups were selected, with these groups primarily including firefighters and construction workers. Research objectives were mainly directed to assess heat stress and physiological workload demands. Heart rate related variables, thermal responses and motion tracking through accelerometry were the most common approaches. Overall, wearable sensors proved to be valid tools for assessing physiological status in working environments. Future research should focus on conducting sensor fusion assessments, engaging wearables in real-time evaluation methods and giving continuous feedback to workers and practitioners.