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Review

Physiological State Monitoring in Advanced Soldiers: Precision Health Strategies for Modern Military Operations

1
Department of Medical Imaging, Faculty of Health Sciences, University of Pécs, 7400 Kaposvár, Hungary
2
Dr. József Baka Diagnostic, Radiation Oncology, Research and Teaching Center, “Moritz Kaposi” Teaching Hospital, Guba Sándor Street 40, 7400 Kaposvár, Hungary
3
Department of Oxyology and Emergency Care, Pedagogy of Health and Nursing Sciences, Institute of Emergency Care, Faculty of Health Sciences, University of Pécs, 7624 Pécs, Hungary
*
Author to whom correspondence should be addressed.
Sci 2025, 7(4), 137; https://doi.org/10.3390/sci7040137
Submission received: 30 June 2025 / Revised: 1 September 2025 / Accepted: 25 September 2025 / Published: 2 October 2025

Abstract

Modern military operations place significant physiological and cognitive demands on soldiers, necessitating innovative strategies to monitor and optimize health and performance. This narrative review examines the role of continuous physiological state monitoring and precision health strategies to enhance soldier resilience and operational readiness. Advanced wearable biosensors were analyzed for their ability to measure vital physiological parameters—such as heart-rate variability, core temperature, hydration status, and biochemical markers—in real-time operational scenarios. Emerging technological solutions, including AI-driven analytics and edge computing, facilitate rapid data interpretation and predictive health assessments. Results indicate that real-time physiological feedback significantly enhances early detection and prevention of conditions like exertional heat illness and musculoskeletal injuries, reducing medical attrition and improving combat effectiveness. However, ethical challenges related to data privacy, informed consent, and secure data management highlight the necessity for robust governance frameworks and stringent security protocols. Personalized training regimens and rehabilitation programs informed by monitoring data demonstrate potential for substantial performance optimization and sustained force readiness. In conclusion, integrating precision health strategies into military operations offers clear advantages in soldier health and operational effectiveness, contingent upon careful management of ethical considerations and data security.

1. Introduction

The modern battlespace exposes soldiers to a multifaceted and rapidly shifting interplay of extreme thermal, hypoxic, and hyperbaric environments that impose relentless demands on both somatic and neurocognitive systems [1,2]. Sustained operations in austere settings—ranging from desert heat to high-altitude hypoxia—generate a spectrum of acute physiological stressors (e.g., thermal strain, dehydration, electrolyte imbalance, circadian disruption, oxidative stress) as well as chronic cumulative insults (e.g., musculoskeletal microtrauma, endocrine dysregulation, persistent inflammatory responses, prolonged sleep deprivation, and immune suppression) [3]. Concurrently, intensified psychological burdens—such as combat-related stress, decision fatigue, sensory overload from constant information streams, moral injury, and continuous threat anticipation—exert profound strain on executive function, attentional control, working memory, and situational awareness [4]. Under these multifactorial pressures, even marginal declines in cardiovascular output, cerebral perfusion, neuromuscular coordination, or synaptic efficiency can precipitate cascading mission-critical errors, heightened injury risk, or catastrophic system failure.
Conventional medical surveillance programs—predominantly based on pre-deployment screening and periodic in-garrison health assessments—remain fundamentally inadequate for capturing the highly dynamic and mission-specific perturbations in soldiers’ homeostatic equilibrium [5,6]. Biweekly or monthly check-ups cannot identify early subclinical biomarkers of fatigue, overtraining, oxidative stress, neurocognitive decline, or incipient soft-tissue and connective-tissue injuries before clinical symptoms emerge [7]. Such retrospective evaluations are inherently reactive and often miss rapid and nonlinear fluctuations in autonomic function (e.g., heart-rate variability, vagal tone), thermoregulatory capacity (e.g., sweat rate efficiency, core-peripheral temperature gradients), and metabolic status (e.g., glycogen depletion, lactate accumulation) that occur during extended patrols or high-intensity engagements [7]. As a result, subclinical deterioration in both physical resilience and cognitive alertness frequently progresses undetected, only becoming apparent once performance decrements, systemic collapse, or medical evacuation thresholds are reached [8].
Integrating continuous, wearable-based physiological monitoring with precision health paradigms represents a paradigm shift in military medicine, transforming soldier care from episodic and reactive to continuous, adaptive, and anticipatory. Real-time capture of multimodal biometrics—including heart rate, core and skin temperature, sweat electrolyte composition, oxygen saturation, respiratory rate, motion kinematics, sleep architecture, neurocognitive response times, and even emerging analytes such as real-time lactate and cortisol levels—feeds into hybrid onboard and cloud-based analytic platforms powered by advanced machine-learning algorithms and edge-computing frameworks [9,10]. These systems generate individualized risk scores for heat illness, musculoskeletal overload, and cognitive fatigue, enabling dynamic adjustment of workload, nutrition, and hydration protocols. Coupling these insights with genomic and proteomic profiles further refines personalized prophylactic and rehabilitative interventions, thereby accelerating recovery, optimizing performance, and sustaining force readiness across the full spectrum of military operations [11,12].
Over the past two decades, physiological monitoring has progressed from simple heart-rate and activity trackers to sophisticated multi-sensor platforms capable of integrating cardiovascular, metabolic, and biochemical data in real time. Organizing these technological advancements in a chronological manner provides important context, allowing readers to understand how current state-of-the-art systems have evolved from earlier, more limited approaches. This historical perspective also highlights the trajectory of innovation, illustrating how early consumer-grade devices and sports science applications laid the foundation for today’s military-tailored monitoring systems.
This narrative review aims to explore and synthesize emerging strategies and technologies for physiological state monitoring and precision health management in modern military operations. By examining current advancements in wearable biosensor technologies, AI-driven analytics, and edge computing, the review highlights how continuous, real-time biometric surveillance can support proactive medical intervention, enhance operational safety, and optimize individual and unit performance. Furthermore, the review critically assesses the integration of genomic and biometric data for personalized medical treatment and rehabilitation, alongside performance optimization strategies that reduce injury risk and improve recovery. In addition to evaluating the operational benefits of these systems, the review addresses the associated ethical and security concerns, particularly regarding data privacy, autonomy, and informed consent in military health monitoring. Through a multidisciplinary analysis, this review provides a consolidated understanding of how data-driven physiological monitoring frameworks, when properly governed, can enhance soldier resilience, combat readiness, and long-term health outcomes. At the same time, it identifies persistent gaps, interoperability challenges, and governance dilemmas that must be resolved to ensure ethically responsible, secure, and sustainable integration of precision health monitoring into future military healthcare ecosystems.

2. Materials and Methods

This narrative review synthesizes current literature and developments related to physiological state monitoring and precision health strategies in military contexts. The review was conducted to provide a comprehensive, multidisciplinary overview of emerging technologies, operational applications, ethical implications, and performance outcomes associated with continuous biometric monitoring and personalized health interventions for soldiers.
A structured, non-systematic search was performed across multiple academic databases, including PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar, to identify relevant peer-reviewed articles, conference proceedings, technical reports, and military research publications published primarily between 2010 and 2025. Key search terms included combinations of the following: “physiological monitoring,” “military wearables,” “precision health,” “AI in military medicine,” “biosensors,” “soldier performance optimization,” and “ethical concerns in biometric surveillance.” Inclusion criteria focused on studies and reviews that addressed (i) wearable sensor technologies for physiological data acquisition, (ii) AI-based analytics and predictive modeling for health management, (iii) personalized medicine applications in military populations, (iv) operational safety and performance enhancement strategies, and (v) ethical and data security concerns in military health monitoring systems. Articles not available in English or lacking relevance to human military populations were excluded. However, this exclusion criterion may warrant reconsideration, as technologies not originally intended for military applications—such as those developed for sports science, space exploration, or civilian healthcare—may still hold significant future potential when adapted for defense contexts.
The data extracted from the literature were thematically categorized and synthesized into seven main domains: (1) physiological state monitoring, (2) precision health applications, (3) advanced technological systems for high-stakes environments, (4) enhanced responsiveness and safety, (5) ethical and security concerns, (6) performance optimization, and (7) overarching implications for operational readiness. Cross-sectional insights from biomedical engineering, defense policy, clinical medicine, and applied physiology were integrated to ensure a comprehensive understanding of the state-of-the-art and future directions in this evolving field.

3. Physiological State Monitoring

Continuous physiological state monitoring represents a transformative approach in military medicine, enabling the real-time, dynamic assessment of a wide array of critical biometric parameters, including heart-rate variability, core body temperature, respiration rate, hydration status, and biochemical markers such as lactate and electrolyte concentrations, heart-rate variability, core and peripheral body temperature, respiration rate and breathing patterns, hydration status, oxygen saturation, sleep architecture, and biochemical markers such as lactate, glucose, cortisol, and electrolyte concentrations [13,14]. Utilizing miniaturized, low-power wearable sensor technologies, these systems offer uninterrupted and non-invasive surveillance of soldiers’ physiological conditions across varied operational environments. Continuous data acquisition allows for the early identification of subclinical and often imperceptible indicators such as cardiovascular strain, autonomic imbalance, impaired thermoregulatory feedback loops, musculoskeletal microtrauma, endocrine disruption, and metabolic disturbances, well before they escalate to clinically significant injuries or operational incapacitation [15,16]. Advanced biosensor platforms, often seamlessly integrated into combat uniforms, helmets, or equipment vests, enable high-frequency data collection without impeding mobility or performance, thereby preserving the natural operational dynamics while vastly enhancing situational physiological awareness [17,18]. These integrated monitoring networks, when combined with real-time analytics and predictive modeling, provide commanders and medical personnel with actionable insights, enabling immediate intervention strategies such as workload redistribution, mission pacing adjustments, targeted hydration and nutritional optimization, micro-recovery protocols, and timely evacuation or medical triage decisions if necessary. Ultimately, continuous physiological monitoring not only strengthens individual soldier resilience but also enhances overall unit readiness, reduces attrition rates from preventable medical conditions, minimizes the logistical burden of casualty management, and ensures sustained operational effectiveness in increasingly complex and hostile theaters of engagement [19,20] as you can see in Figure 1.

4. Precision Health Applications

Precision health applications in military contexts represent a paradigm shift from standardized medical protocols to data-driven, individualized care strategies tailored to the unique biological and operational profiles of each soldier. These approaches leverage integrated physiological, genomic, and environmental datasets to inform highly specific diagnostic, preventive, and therapeutic decisions that directly enhance force health protection and operational effectiveness [21,22]. Central to this model is the use of advanced genomic sequencing, epigenetic analysis, proteomic and metabolomic profiling, and biomarker identification, which enable military clinicians to anticipate individual susceptibilities to conditions such as exertional heat stroke, altitude intolerance, metabolic syndromes, and adverse drug reactions. This molecular-level insight facilitates the formulation of personalized medical regimens—ranging from pharmacological interventions to immunizations—designed to optimize efficacy while minimizing risks associated with generalized treatment strategies [23,24].
Moreover, precision health plays a pivotal role in recovery and rehabilitation protocols. Using real-time biometrics—including musculoskeletal load metrics, heart-rate variability, hormonal biomarkers, and sleep quality—clinicians can construct dynamic rehabilitation programs that are continually adjusted to reflect the soldier’s physiological recovery trajectory. This personalization improves rehabilitation adherence, accelerates return-to-duty timelines, and reduces the risk of reinjury [25]. Environmental exposure data, including climate, altitude, and operational stress, are also incorporated to contextualize health decisions within the soldier’s deployment environment, ensuring medical and physical readiness is maintained across diverse operational settings [26]. The cumulative effect of these personalized interventions is a measurable improvement in mission capability, individual resilience, unit cohesion, and overall force sustainability. A comparative overview of the main advantages and disadvantages of implementing precision health in military contexts is summarized in Table 1.

5. Advanced Technological Systems for High-Stakes Environments

Advancements in digital health technologies are increasingly focused on integrated systems designed to enhance individual safety and overall effectiveness in high-stakes, performance-critical environments. At the forefront of these innovations are advanced wearable sensor technologies, which have evolved into compact, energy-efficient devices capable of continuously and unobtrusively monitoring a broad spectrum of physiological and biomechanical parameters [27,28]. These biosensors, often embedded into uniforms or functional gear, can track vital metrics such as electrocardiogram (ECG) signals, skin temperature and conductivity, gait dynamics, posture, oxygen saturation, and key biochemical markers including glucose, lactate, and electrolyte levels. The real-time physiological data captured under demanding operational conditions provide continuous health status assessments, enabling early detection of abnormal trends and supporting timely, evidence-based interventions [29].
The capabilities of these sensor systems are significantly enhanced through the integration of artificial intelligence (AI), particularly hierarchical deep learning and temporal sequence modeling algorithms that process large volumes of high-velocity data in near real-time. These AI-driven platforms are designed to identify complex physiological patterns, classify levels of operational stress, and accurately predict injury risks—often achieving over 93% predictive accuracy in validated datasets [30,31]. By facilitating predictive diagnostics, AI systems support a shift from reactive to preventive healthcare approaches, helping to reduce the incidence of environment-induced injuries such as exertional heat stress, overuse musculoskeletal conditions, and acute cardiovascular events. Moreover, these platforms continuously learn from individual baseline data, allowing for personalized alerts and adaptive interventions tailored to each individual’s physiological profile and historical responses to stress.
The effective implementation of these capabilities relies on robust edge computing architectures and secure communication protocols. Edge computing enables decentralized, real-time data processing directly on wearable devices or proximal computing nodes, thereby minimizing latency and ensuring uninterrupted function in low-connectivity or resource-constrained environments [32,33]. This decentralized architecture not only enhances real-time decision-making but also mitigates cybersecurity risks by limiting the need for data transmission across potentially insecure networks. Complementary encrypted communication frameworks preserve the confidentiality and integrity of sensitive physiological and operational data, ensuring secure information exchange even in adverse conditions [34]. Collectively, these technologies support a resilient, intelligent, and responsive health monitoring infrastructure that is transforming standards of safety, performance optimization, and health surveillance in high-demand operational contexts.

6. Enhanced Responsiveness and Safety

Enhanced responsiveness and safety in contemporary military operations are increasingly dependent on the capacity to dynamically monitor physiological states and initiate real-time, data-driven responses to mitigate emerging health risks. Wearable biosensors, now capable of continuously capturing high-resolution physiological data such as heart-rate variability, skin temperature, core body temperature, and respiration rates, provide both soldiers and commanding officers with immediate situational awareness of individual and unit health status [35,36]. These systems are particularly critical in sustained, high-intensity operations, extreme thermal environments, or prolonged missions with limited recovery opportunities, where physiological stress can escalate rapidly. Continuous feedback allows for timely tactical adaptations, including redistribution of physical workloads, enforcement of structured hydration and rest protocols, modification of environmental exposure through shade or cooling systems, and adjustment of mission pacing. Notably, early warning systems for exertional heat illness have advanced through algorithmic interpretation of thermoregulatory biomarkers, cardiovascular strain indices, and fluid balance markers, allowing for preemptive deployment of targeted cooling strategies, electrolyte replenishment, or mission pause protocols before critical thresholds are reached, thereby preventing irreversible heat-related morbidity [37,38].
The implementation of such proactive countermeasures has led to a measurable reduction in the incidence and severity of heat injuries and other physiological impairments, particularly in environments with extreme temperatures, humidity, or high physical load demands [39]. Data from field deployments and controlled military studies underscore that these systems not only reduce the need for medical evacuations but also preserve unit cohesion and maintain combat effectiveness over longer operational cycles [40]. This represents a fundamental shift in the military medical doctrine—from episodic monitoring and delayed reaction to continuous assessment and immediate intervention. The practical outcomes include enhanced mission sustainability, improved operational decision-making, and increased individual survivability under adverse conditions [41]. Furthermore, these monitoring capabilities contribute to the development of long-term risk profiles and safety guidelines that adapt to varying mission demands and environmental stressors, reinforcing a culture of health-informed tactical planning and execution [42].

7. Ethical and Security Concerns

The implementation of advanced physiological state monitoring systems in military operations presents a complex array of ethical and security challenges that must be carefully navigated to ensure responsible use of sensitive health data. These technologies, while offering substantial operational benefits, inherently involve the continuous collection of highly personal biometric information—such as heart-rate variability, stress levels, and thermal responses—raising legitimate concerns about privacy, autonomy, and informed consent [43,44]. The invasive nature of such persistent surveillance introduces risks of psychological distress, stigmatization, or coercive use, particularly when military priorities—such as unit readiness or force health protection—are emphasized at the potential expense of individual rights. In many instances, military personal health monitoring (PHM) programs prioritize utilitarian outcomes, such as mission optimization, without fully addressing the ethical implications of data collection and long-term physiological profiling [45,46].
To mitigate these risks, it is imperative robust, multilayered cybersecurity infrastructures and clearly defined regulatory safeguards. These should include end-to-end data encryption across all transmission channels, secure hybrid local and remote storage solutions with redundancy, tamper-proof blockchain-based or cryptographic logging of access events, multi-factor authentication, and strict tiered access controls that delineate authorized personnel, legitimate data use cases, and emergency override procedures [47,48]. Moreover, soldiers must be provided with transparent, comprehensive, and context-specific informed consent protocols that clearly articulate how their data will be collected, stored, analyzed, and shared; what operational and personal risks are involved; and under what specific conditions data access, transfer, or third-party utilization may occur. Consent procedures should also include mechanisms for opting out or withdrawing consent where operationally feasible, alongside structured support for comprehension of these implications within the constraints of a high-pressure, hierarchical military environment. This ensures that ethical autonomy is preserved to the greatest extent possible without undermining operational integrity [49].
Ultimately, the ethical deployment of physiological monitoring in defense settings depends on the development and enforcement of robust governance frameworks that balance the imperative for operational advantage with a non-negotiable respect for human dignity and data sovereignty. These frameworks must address critical issues such as data ownership, legal accountability, cross-jurisdictional use in multinational operations, data retention limits, and third-party access protocols [50,51]. Institutional review boards, independent oversight committees, and regular ethical audits should be embedded into military research and implementation processes to ensure ongoing compliance and public trust. As these technologies become more integrated into force health management, a principled approach grounded in biomedical ethics, legal transparency, and operational necessity is essential to safeguard both individual rights and collective security. The key ethical and security concerns associated with physiological state monitoring in military contexts are illustrated in Figure 2.

8. Performance Optimization

Performance optimization in modern military settings is increasingly driven by the integration of advanced physiological monitoring systems that provide continuous, individualized data to inform evidence-based training and rehabilitation protocols. These systems allow for the dynamic assessment of biomechanical, cardiovascular, and metabolic parameters, enabling the development of precision-based conditioning programs tailored to each soldier’s physiological profile and real-time functional capacity [52,53]. Frameworks such as WearableMil exemplify the practical application of this approach, combining high-resolution activity recognition, joint load estimation, and gait analysis to modulate training intensity and progression with pinpoint accuracy. This ensures that physical training stimuli remain within safe and effective thresholds, mitigating the risk of musculoskeletal overuse injuries and significantly decreasing dropout rates and medical costs during physically demanding phases like basic training [54,55]. Such individualized regimens not only preserve physical integrity but also enhance motor performance and movement efficiency—key determinants of combat readiness and prolonged operational endurance [56]. The process of performance optimization through physiological monitoring, individualized training, and adaptive workload management is summarized in Figure 3.
In parallel, these monitoring systems support the design of holistic performance recovery protocols by continuously tracking physiological recovery markers such as sleep architecture and quality indices, heart-rate variability patterns, cortisol and other stress hormone levels, inflammatory biomarkers, and muscle glycogen restoration dynamics [57,58]. These data streams allow for the real-time customization of rest–work cycles, macronutrient and micronutrient intake, hydration strategies, and recovery modalities (e.g., cooling, compression, or neuromuscular stimulation) based on individual metabolic demands and circadian rhythms. Precision-guided recovery protocols help prevent cumulative fatigue syndromes, optimize tissue repair and musculoskeletal adaptation, stabilize endocrine balance, and sustain both cognitive alertness and neuromuscular performance during high-tempo operations [59]. Furthermore, adaptive workload management guided by biometric insights ensures long-term force resilience by reducing the likelihood of chronic performance decrements and psychological burnout. Ultimately, the convergence of wearable technology, physiological analytics, and personalized intervention strategies enables a new era of data-driven military human performance management—one that enhances mission capability, extends career longevity, and supports comprehensive warfighter health across diverse operational contexts [60,61].

9. Discussion

The integration of physiological state monitoring, precision health applications, advanced technologies, enhanced responsiveness, ethical considerations, and performance optimization strategies represents a significant advancement for modern military operations. Continuous physiological state monitoring using wearable biosensors allows commanders and medical personnel to track real-time health parameters such as heart-rate variability, core temperature, hydration status, and biochemical markers, facilitating timely interventions that significantly reduce the incidence of preventable injuries, heat illness, and operational fatigue [13,14,15,16,17,18,19,20]. For operational reliability, such systems typically require an accuracy of ±1 bpm for heart rate, ±0.2 °C for core temperature, and hydration status detection within ±2% of actual body water levels, with latency under 2 s to ensure actionable insights in the field. These monitoring capabilities bridge critical gaps left by traditional periodic health assessments, enabling proactive rather than reactive healthcare measures within challenging operational environments [5,15,18]. To provide context on existing capabilities, Table 2 compares commercially available and experimental physiological monitoring systems relevant to military settings, highlighting their measurement parameters, operational limits, and current technological constraints.
While many wearable technologies originate in civilian contexts, their direct adoption in defense settings is not straightforward. Civilian-oriented systems are generally designed for wellness or fitness tracking in controlled environments, where moderate accuracy and short battery life are acceptable. In contrast, military-oriented systems must withstand extreme operational environments, deliver high-precision data for mission-critical decisions, and comply with strict security requirements. Table 3 summarizes these distinctions, underscoring why technologies purpose-built for soldiers are essential, even as civilian devices continue to offer valuable insights and potential adaptation pathways.
Precision health applications further augment these advantages by enabling highly personalized medical and rehabilitation strategies tailored to each soldier’s unique genetic, physiological, and environmental profile. Individualized risk assessment and personalized medication protocols minimize adverse drug reactions and optimize therapeutic efficacy, thus enhancing overall health outcomes and significantly accelerating recovery processes [21,22,23,24,25,26]. Consequently, precision medicine reduces downtime related to preventable medical conditions, directly benefiting force readiness and operational effectiveness.
Technological advancements underpinning these capabilities include sophisticated wearable sensor technologies, AI-driven analytics, and secure data processing infrastructures. Miniaturized, low-power biosensors provide continuous, accurate physiological data streams, while hierarchical deep learning frameworks rapidly analyze these data to predict injury risk and physiological strain with impressive accuracy [27,28,29,30,31]. In current military-grade systems, predictive injury models achieve sensitivities above 90% and specificities between 85 and 92%, but performance may decline by up to 15% in extreme heat, high-altitude, or high-motion environments due to sensor signal noise and reduced skin contact quality. Furthermore, edge computing and secure communications ensure real-time analytics can be reliably performed even in austere and contested operational conditions, protecting sensitive biometric data from unauthorized access or adversarial compromise [32,33,34].
Enhanced responsiveness and safety are direct outcomes of these technological implementations. Immediate physiological feedback allows dynamic adjustment of soldiers’ physical workloads and tactical decisions, effectively reducing heat-related injuries and other exertional health risks through timely preventive measures [35,36,37,38]. Evidence from recent operational scenarios underscores that these proactive monitoring systems are instrumental in maintaining combat effectiveness, especially in extreme climates or prolonged physical engagements, by significantly mitigating health-related attrition [39,40,41,42].
Despite these benefits, the widespread collection and analysis of sensitive biometric data pose substantial ethical and security concerns. Issues surrounding data privacy, informed consent, autonomy, and data misuse require careful consideration, highlighting the necessity for robust governance frameworks and transparent regulatory policies [43,44,45,46]. Military personal health monitoring initiatives must explicitly define data access controls, establish stringent encryption standards, and clearly delineate permissible data usage to protect soldiers from unauthorized exploitation or ethical breaches [47,48,49,50,51]. Balancing operational advantages with ethical obligations remains essential for sustainable and accepted integration of these technologies.
Finally, leveraging physiological monitoring insights to optimize soldier performance through personalized training and recovery protocols offers substantial operational benefits. Systems such as WearableMil exemplify how continuous biometric data facilitate precise adjustments to training intensity and load management, effectively reducing musculoskeletal injuries and training attrition [52,53,54,55,56]. Additionally, tailored rest-work-nutrition strategies based on real-time biometrics significantly enhance physical recovery, minimize cumulative fatigue, and sustain soldier readiness over prolonged operational periods [57,58,59,60,61]. Collectively, these precision-driven interventions foster enhanced resilience, improved physical conditioning, and optimized mission performance across diverse operational contexts.
In addition to recognizing the operational benefits of advanced physiological monitoring systems, it is equally important to acknowledge their current limitations. Each technique carries specific drawbacks—ranging from motion artifacts in cardiovascular sensors to limited durability of sweat-based hydration monitors and the invasiveness of certain biochemical assays—that restrict their reliability in demanding military contexts. Future research should prioritize the development of more robust, non-invasive, and environmentally resilient technologies, alongside improved data integration frameworks that combine multimodal inputs for greater predictive accuracy. Addressing these shortcomings through interdisciplinary innovation will be essential to translating emerging technologies into practical, ethical, and mission-ready solutions for the modern warfighter.

10. Conclusions

The integration of continuous physiological monitoring, precision health applications, and advanced data analytics represents a transformative shift in military health management, enabling a proactive, personalized, and operationally responsive approach to soldier care. Wearable biosensors, real-time biometric analysis, and AI-driven predictive frameworks allow for the early detection of physiological stress, injury risk, and cognitive fatigue, facilitating timely interventions that preserve performance and enhance survivability in demanding environments. Precision health strategies—grounded in genomic, metabolic, and environmental data—enable highly individualized medical, rehabilitative, and training protocols that improve recovery timelines, reduce attrition, and sustain long-term force readiness.
In parallel, emerging technologies such as edge computing and encrypted communication networks enable the secure, real-time deployment of these capabilities even in remote, resource-limited, or high-demand environments. These technological advancements, however, are accompanied by complex ethical and security challenges, particularly concerning data privacy, informed consent, and the governance of personal health information. A principled, ethically grounded framework is essential to guide the responsible integration of such technologies, ensuring trust, individual autonomy, and compliance with legal and regulatory standards.
Collectively, the implementation of these technologies marks a new era in high-performance health systems—one that not only enhances immediate physiological functioning in demanding environments but also promotes long-term health, resilience, and sustainability for individuals operating under high stress. Ongoing interdisciplinary research, policy development, and real-world validation are essential to ensure the safe, effective, and ethical integration of these innovations into future health and performance optimization strategies.

Author Contributions

Conceptualization, D.S. and A.A.P.; methodology, G.F.; formal analysis, K.V. and D.P.; investigation, B.B. and K.V.; resources, J.B.; writing—original draft preparation, D.S.; writing—review and editing, A.A.P., J.B. and G.F.; supervision, A.A.P.; project administration, K.V.; funding acquisition, J.B. All authors have read and agreed to the published version of the manuscript.

Funding

The project “Cooperative Technologies National Laboratory” (ID: 2022-2.1.1-NL-2022-00012) was implemented with the support of the National Research, Development, and Innovation Fund provided by the Ministry of Culture and Innovation, under the financing of the National Laboratories Program.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Sawka, M.N.; Cheuvront, S.N.; Kenefick, R.W. Hypohydration and human performance: Impact of environment and fluid intake. Sports Med. 2015, 45 (Suppl. 1), S51–S60. [Google Scholar] [CrossRef]
  2. Gibson, O.R.; James, C.A.; Mee, J.A.; Willmott, A.G.; Turner, G.; Hayes, M.; Maxwell, N.S. Heat alleviation strategies for athletic performance: A review and practitioner guidelines. Temperature 2019, 7, 3–36. [Google Scholar] [CrossRef] [PubMed]
  3. González-Alonso, J.; Teller, C.; Andersen, S.L.; Jensen, F.B.; Hyldig, T.; Nielsen, B. Influence of body temperature on the development of fatigue during prolonged exercise in the heat. J. Appl. Physiol. 1999, 86, 1032–1039. [Google Scholar] [CrossRef]
  4. Lieberman, H.R. Cognitive methods for assessing mental energy. Nutr. Neurosci. 2007, 10, 229–242. [Google Scholar] [CrossRef] [PubMed]
  5. Bourdon, P.C.; Cardinale, M.; Murray, A.; Gastin, P.; Kellmann, M.; Varley, M.C.; Gabbett, T.J.; Coutts, A.J.; Burgess, D.J.; Gregson, W.; et al. Monitoring athlete training loads: Consensus statement. Int. J. Sports Physiol. Perform. 2017, 12 (Suppl. 2), S161–S170. [Google Scholar] [CrossRef] [PubMed]
  6. Corrigan, S.L.; Bulmer, S.; Roberts, S.S.H.; Warmington, S.; Drain, J.; Main, L.C. Monitoring Responses to Basic Military Training with Heart Rate Variability. Med. Sci. Sports Exerc. 2022, 54, 1506–1514. [Google Scholar] [CrossRef]
  7. Berg Rice, V.J.; Connolly, V.L.; Pritchard, A.; Bergeron, A.; Mays, M.Z. Effectiveness of a screening tool to detect injuries during Army Health Care Specialist training. Work 2007, 29, 177–188. [Google Scholar] [CrossRef]
  8. Grant, C.C.; Mongwe, L.; van Rensburg, D.C.J.; Fletcher, L.; Wood, P.S.; Terblanche, E.; du Toit, P.J. The Difference Between Exercise-Induced Autonomic and Fitness Changes Measured After 12 and 20 Weeks of Medium-to-High Intensity Military Training. J. Strength Cond. Res. 2016, 30, 2453–2459. [Google Scholar] [CrossRef]
  9. Helén, J.; Kyröläinen, H.; Ojanen, T.; Pihlainen, K.; Santtila, M.; Heikkinen, R.; Vaara, J.P. High-Intensity Functional Training Induces Superior Training Adaptations Compared With Traditional Military Physical Training. J. Strength Cond. Res. 2023, 37, 2477–2483. [Google Scholar] [CrossRef]
  10. Patel, S.; Park, H.; Bonato, P.; Chan, L.; Rodgers, M. A review of wearable sensors and systems with application in rehabilitation. J. Neuroeng. Rehabil. 2012, 9, 21. [Google Scholar] [CrossRef]
  11. De Castro, M.; Biesecker, L.G.; Turner, C.; Brenner, R.; Witkop, C.; Mehlman, M.; Bradburne, C.; Green, R.C. Genomic medicine in the military. NPJ Genom. Med. 2016, 1, 15008. [Google Scholar] [CrossRef] [PubMed]
  12. Giudice, G.; Petsalaki, E. Proteomics and phosphoproteomics in precision medicine: Applications and challenges. Brief. Bioinform. 2019, 20, 767–777. [Google Scholar] [CrossRef] [PubMed]
  13. Friedl, K.E. Military applications of soldier physiological monitoring. J. Sci. Med. Sport. 2018, 21, 1147–1153. [Google Scholar] [CrossRef] [PubMed]
  14. Buller, M.J.; Welles, A.P.; Friedl, K.E. Wearable physiological monitoring for human thermal-work strain optimization. J. Appl. Physiol. 2018, 124, 432–441. [Google Scholar] [CrossRef]
  15. de Vries, H.J.; van der Wal, S.J.; Delahaij, R.; Venrooij, W.; Kamphuis, W. Real-time monitoring of military health and readiness: A perspective on future research. Front. Digit. Health 2025, 7, 1542140. [Google Scholar] [CrossRef]
  16. O’Leary, T.J.; Wardle, S.L.; Rawcliffe, A.J.; Chapman, S.; Mole, J.; Greeves, J.P. Understanding the musculoskeletal injury risk of women in combat: The effect of infantry training and sex on musculoskeletal injury incidence during British Army basic training. BMJ Mil. Health 2023, 169, 57–61. [Google Scholar] [CrossRef]
  17. Aroganam, G.; Manivannan, N.; Harrison, D. Review on wearable technology sensors used in consumer sport applications. Sensors 2019, 19, 1983. [Google Scholar] [CrossRef]
  18. Liu, Y.; Zhu, S.H.; Wang, G.H.; Ye, F.; Li, P.Z. Validity and reliability of multiparameter physiological measurements recorded by the Equivital LifeMonitor during activities of various intensities. J. Occup. Environ. Hyg. 2013, 10, 78–85. [Google Scholar] [CrossRef]
  19. Buller, M.J.; Tharion, W.J.; Cheuvront, S.N.; Montain, S.J.; Kenefick, R.W.; Castellani, J.; A Latzka, W.; Roberts, W.S.; Richter, M.; Jenkins, O.C.; et al. Estimation of human core temperature from sequential heart rate observations. Physiol. Meas. 2013, 34, 781–798. [Google Scholar] [CrossRef]
  20. Drain, J.; Billing, D.; Neesham-Smith, D.; Aisbett, B. Predicting physiological capacity of human load carriage—A review. Appl. Ergon. 2016, 52, 85–94. [Google Scholar] [CrossRef]
  21. Ashley, E.A. Towards precision medicine. Nat. Rev. Genet. 2016, 17, 507–522. [Google Scholar] [CrossRef]
  22. Schork, N.J. Personalized medicine: Time for one-person trials. Nature 2015, 520, 609–611. [Google Scholar] [CrossRef]
  23. Wang, R.C.; Wang, Z. Precision Medicine: Disease Subtyping and Tailored Treatment. Cancers 2023, 15, 3837. [Google Scholar] [CrossRef] [PubMed]
  24. Sutehall, S.; Pitsiladis, Y. Personalized Nutrition for the Enhancement of Elite Athletic Performance. Scand. J. Med. Sci. Sports. 2025, 35, e70044. [Google Scholar] [CrossRef] [PubMed]
  25. Nindl, B.C.; Beals, K.; Witchalls, J.; Friedl, K.E. Military human performance optimization and injury prevention: Strategies for the 21st century warfighter. J. Sci. Med. Sport. 2017, 20 (Suppl. 4), S1–S2. [Google Scholar] [CrossRef] [PubMed]
  26. Ahmed, A.; Mustafa, M. Precision Emergency Medicine: A Systematic Review. Cureus 2024, 16, e75068. [Google Scholar] [CrossRef]
  27. Shi, H.; Zhao, H.; Liu, Y.; Gao, W.; Dou, S.C. Systematic Analysis of a Military Wearable Device Based on a Multi-Level Fusion Framework: Research Directions. Sensors 2019, 19, 2651. [Google Scholar] [CrossRef]
  28. Bustos, D.; Guedes, J.C.; Vaz, M.P.; Pombo, E.; Fernandes, R.J.; Costa, J.T.; Baptista, J.S. Non-Invasive Physiological Monitoring for Physical Exertion and Fatigue Assessment in Military Personnel: A Systematic Review. Int. J. Environ. Res. Public Health 2021, 18, 8815. [Google Scholar] [CrossRef]
  29. Doody, C.B.; Robertson, L.; Cox, K.M.; Bogue, J.; Egan, J.; Sarma, K.M. Pre-deployment programmes for building resilience in military and frontline emergency service personnel. Cochrane Database Syst Rev. 2021, 12, CD013242. [Google Scholar] [CrossRef]
  30. Russell, B.K.; McGeown, J.; Beard, B.L. Developing AI enabled sensors and decision support for military operators in the field. J. Sci. Med. Sport. 2023, 26 (Suppl. 1), S40–S45. [Google Scholar] [CrossRef]
  31. Ordóñez, F.J.; Roggen, D. Deep convolutional and LSTM recurrent neural networks for multimodal wearable activity recognition. Sensors 2016, 16, 115. [Google Scholar] [CrossRef]
  32. Shi, W.; Cao, J.; Zhang, Q.; Li, Y.; Xu, L. Edge computing: Vision and challenges. IEEE Internet Things J. 2016, 3, 637–646. [Google Scholar] [CrossRef]
  33. Porambage, P.; Okwuibe, J.; Liyanage, M.; Ylianttila, M.; Taleb, T. Survey on multi-access edge computing for Internet of Things realization. IEEE Commun. Surv. Tutor. 2018, 20, 2961–2991. [Google Scholar] [CrossRef]
  34. Zhou, L.; Kang, M.; Chen, W. Lightweight Security Transmission in Wireless Sensor Networks through Information Hiding and Data Flipping. Sensors 2022, 22, 823. [Google Scholar] [CrossRef]
  35. Buller, M.J.; Delves, S.K.; Fogarty, A.L.; Veenstra, B.J. On the real-time prevention and monitoring of exertional heat illness in military personnel. J. Sci. Med. Sport. 2021, 24, 975–981. [Google Scholar] [CrossRef]
  36. Hunt, A.P.; Billing, D.C.; Patterson, M.J.; Caldwell, J.N. Heat strain during military training activities: The dilemma of balancing force protection and operational capability. Temperature 2016, 3, 307–317. [Google Scholar] [CrossRef]
  37. Pearsons, A.; Hanson, C.L.; Neubeck, L.; Blackstock, C.; Clarke, E.; Reed, M.J. Usability and acceptability of ambulatory moni-toring in undiagnosed syncope: Insights from the ASPIRED-Q qualitative study. BMJ Open. 2025, 15, e095927. [Google Scholar] [CrossRef] [PubMed]
  38. Epstein, Y.; Druyan, A.; Heled, Y. Heat injury prevention: A military perspective. J. Strength. Cond. Res. 2012, 26 (Suppl. 2), S82–S86. [Google Scholar] [CrossRef] [PubMed]
  39. Westwood, C.S.; Fallowfield, J.L.; Delves, S.K.; Nunns, M.; Ogden, H.B.; Layden, J.D. Individual risk factors associated with exertional heat illness in military populations. J. Sci. Med. Sport 2021, 24, 386–392. [Google Scholar]
  40. Parsons, I.T.; Stacey, M.J.; Woods, D.R. Heat adaptation in military personnel: Mitigating risk, maximizing readiness. J. R. Army Med. Corps 2019, 165, 313–318. [Google Scholar]
  41. Yankelson, L.; Sadeh, B.; Gershovitz, L.; Werthein, J.; Heller, K.; Halpern, P.; Halkin, A.; Adler, A.; Steinvil, A.; Viskin, S. Life-threatening events during endurance sports: Is heat stroke more prevalent than arrhythmic death? J. Am. Coll. Cardiol. 2014, 64, 463–469. [Google Scholar] [CrossRef] [PubMed]
  42. Kenny, G.P.; Flouris, A.D.; Yagouti, A.; Notley, S.R. Towards establishing evidence-based guidelines on maximum workplace temperatures to reduce occupational heat injury risk: A6 systematic review. BMC Public Health 2019, 19, 453. [Google Scholar]
  43. Mittelstadt, B.D.; Floridi, L. The ethics of biomedical big data. Philos. Trans. A Math. Phys. Eng. Sci. 2016, 374, 20160112. [Google Scholar]
  44. Kalkman, S.; Mostert, M.; Gerlinger, C.; van Delden, J.J.; van Thiel, G.J. Responsible data sharing in international health research: A systematic review of principles and norms. BMC Med. Ethics. 2019, 20, 21. [Google Scholar] [CrossRef]
  45. Mehlman, M.J.; Li, T.Y. Ethical, legal, social, and policy issues in the use of genomic technology by the US military. J. Law. Biosci. 2014, 1, 244–280. [Google Scholar] [CrossRef]
  46. Almeida, D.; Shmarko, K.; Lomas, E. The ethics of facial recognition technologies, surveillance, and accountability in an age of artificial intelligence: A comparative analysis of US, EU, and UK regulatory frameworks. AI Ethics 2022, 2, 377–387. [Google Scholar] [CrossRef]
  47. Kshetri, N. Blockchain’s roles in meeting key supply chain management objectives. Int. J. Inf. Manag. 2018, 39, 80–89. [Google Scholar] [CrossRef]
  48. Alotaibi, B. A Survey on Industrial Internet of Things Security: Requirements, Attacks, AI-Based Solutions, and Edge Computing Opportunities. Sensors 2023, 23, 7470. [Google Scholar] [CrossRef]
  49. Volpato, L.; Del Río Carral, M.; Senn, N.; Santiago Delefosse, M. General Practitioners’ Perceptions of the Use of Wearable Electronic Health Monitoring Devices: Qualitative Analysis of Risks and Benefits. JMIR Mhealth Uhealth 2021, 9, e23896. [Google Scholar] [CrossRef]
  50. Gasser, U.; Ienca, M.; Scheibner, J.; Sleigh, J.; Vayena, E. Digital tools against COVID-19: Taxonomy, ethical challenges, and navigation aid. Lancet Digit. Health 2020, 2, e425–e434. [Google Scholar] [CrossRef]
  51. Nebeker, C.; Torous, J.; Bartlett Ellis, R.J. Building the case for actionable ethics in digital health research supported by artificial intelligence. BMC Med. 2019, 17, 137. [Google Scholar] [CrossRef] [PubMed]
  52. Halson, S.L. Monitoring training load to understand fatigue in athletes. Sports Med. 2014, 44 (Suppl. 2), S139–S147. [Google Scholar] [CrossRef] [PubMed]
  53. Soligard, T.; Schwellnus, M.; Alonso, J.-M.; Bahr, R.; Clarsen, B.; Dijkstra, H.P.; Gabbett, T.; Gleeson, M.; Hägglund, M.; Hutchinson, M.R.; et al. How much is too much? (Part 1) International Olympic Committee consensus statement on load in sport and risk of injury. Br. J. Sports Med. 2016, 50, 1030–1041. [Google Scholar] [CrossRef] [PubMed]
  54. Preatoni, E.; Bergamini, E.; Fantozzi, S.; Giraud, L.I.; Bustos, A.S.O.; Vannozzi, G.; Camomilla, V. The Use of Wearable Sensors for Preventing, Assessing, and Informing Recovery from Sport-Related Musculoskeletal Injuries: A Systematic Scoping Review. Sensors 2022, 22, 3225. [Google Scholar] [CrossRef]
  55. Li, R.T.; Kling, S.R.; Salata, M.J.; Cupp, S.A.; Sheehan, J.; Voos, J.E. Wearable Performance Devices in Sports Medicine. Sports Health 2016, 8, 74–78. [Google Scholar] [CrossRef]
  56. Wardle, S.L.; Greeves, J.P. Mitigating the risk of musculoskeletal injury: A systematic review of the most effective injury prevention strategies for military personnel. J. Sci. Med. Sport. 2017, 20 (Suppl. 4), S3–S10. [Google Scholar] [CrossRef]
  57. Halson, S.L.; Burke, L.M.; Pearce, J. Nutrition for travel: From jet lag to catering. Int. J. Sport. Nutr. Exerc. Metab. 2019, 29, 228–235. [Google Scholar] [CrossRef]
  58. de Rijk, M.G.; van Eekelen, A.P.J.; Boesveldt, S.; Kaldenberg, E.; Holwerda, T.; Lansink, C.J.M.; Feskens, E.J.M.; de Vries, J.H.M. Macronutrient intake and alertness during night shifts—The time interval matters. Front. Nutr. 2023, 10, 1245420. [Google Scholar] [CrossRef]
  59. McClung, J.P.; Gaffney-Stomberg, E. Optimizing Performance, Health, and Well-being: Nutritional Factors. Mil Med. 2016, 181 (Suppl. 1), 86–91. [Google Scholar] [CrossRef]
  60. Nässi, A.; Ferrauti, A.; Meyer, T.; Pfeiffer, M.; Kellmann, M. Psychological tools used for monitoring training responses of athletes. Perform. Enhanc. Health 2017, 5, 125–133. [Google Scholar] [CrossRef]
  61. Scofield, D.E.; Kardouni, J.R. The tactical athlete: A product of 21st-century strength and conditioning. Strength. Cond. J. 2015, 37, 2–7. [Google Scholar] [CrossRef]
  62. He, M.; Cerna, J.; Alkurdi, A.; Dogan, A.; Zhao, J.; Clore, J.L.; Sowers, R.; Hsiao-Wecksler, E.T.; Hernandez, M.E. Physical, Social and Cognitive Stressor Identification using Electrocardiography-derived Features and Machine Learning from a Wearable Device. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2024, 2024, 1–4. [Google Scholar] [CrossRef] [PubMed]
  63. Goods, P.S.R.; Maloney, P.; Miller, J.; Jennings, D.; Fahey-Gilmour, J.; Peeling, P.; Galna, B. Concurrent validity of the CORE wearable sensor with BodyCap temperature pill to assess core body temperature during an elite women’s field hockey heat training camp. Eur. J. Sport. Sci. 2023, 23, 1509–1517. [Google Scholar] [CrossRef]
  64. Moyen, N.E.; Bapat, R.C.; Tan, B.; Hunt, L.A.; Jay, O.; Mündel, T. Accuracy of Algorithm to Non-Invasively Predict Core Body Temperature Using the Kenzen Wearable Device. Int. J. Environ. Res. Public Health 2021, 18, 13126. [Google Scholar] [CrossRef]
  65. Budig, M.; Stoohs, R.; Keiner, M. Validity of Two Consumer Multisport Activity Tracker and One Accelerometer against Polysomnography for Measuring Sleep Parameters and Vital Data in a Laboratory Setting in Sleep Patients. Sensors 2022, 22, 9540. [Google Scholar] [CrossRef]
  66. Gahtan, B.; Funk, S.; Ketko, I.; Kodesh, E.; Kuflik, T.; Bronstein, A.M. WearableMil: An End-to-End Framework for Military Activity Recognition and Performance Monitoring. In Proceedings of the 2025 IEEE 13th International Conference on Healthcare Informatics (ICHI), Rende, Italy, 18–21 June 2025; pp. 618–623. [Google Scholar] [CrossRef]
  67. Nazari, G.; Bobos, P.; MacDermid, J.C.; Sinden, K.E.; Richardson, J.; Tang, A. Psychometric properties of the Zephyr bioharness device: A systematic review. BMC Sports Sci Med. Rehabil. 2018, 10, 6. [Google Scholar] [CrossRef]
  68. Chapman, C.L.; A Schafer, E.; Potter, A.W.; Lavoie, E.M.; Roberts, B.M.; Castellani, J.W.; E Friedl, K.; Looney, D.P. Day-to-day reliability of basal heart rate and short-term and ultra short-term heart rate variability assessment by the Equivital eq02+ LifeMonitor in US Army soldiers. BMJ Mil. Health 2024, 14, e002687. [Google Scholar] [CrossRef]
Figure 1. Flowchart of physiological state monitoring.
Figure 1. Flowchart of physiological state monitoring.
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Figure 2. Ethical and security concerns.
Figure 2. Ethical and security concerns.
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Figure 3. The flowchart of performance optimization.
Figure 3. The flowchart of performance optimization.
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Table 1. Advantages and Disadvantages of Precision Health in the Military.
Table 1. Advantages and Disadvantages of Precision Health in the Military.
AdvantagesDisadvantages
Enables personalized medical treatments based on genomic and physiological dataRequires complex data integration and high infrastructure investment
Improves early detection of illness or injury risk through biomarker analysisRaises ethical concerns regarding data privacy, consent, and ownership
Optimizes rehabilitation and return-to-duty timelines via real-time biometric feedbackMay lead to over-reliance on technology in decision-making processes
Reduces adverse drug reactions through individualized pharmacogenomicsLogistical challenges in deploying and maintaining advanced systems in the field
Enhances operational readiness and resilience across diverse environmentsPotential inequality in access or benefit depending on technological availability
Table 2. Available and experimental physiological monitoring systems relevant to military settings, measurement parameters, operational limits, and current technological constraints [13,14,15,16,17,18,19,20,62,63,64,65,66,67,68].
Table 2. Available and experimental physiological monitoring systems relevant to military settings, measurement parameters, operational limits, and current technological constraints [13,14,15,16,17,18,19,20,62,63,64,65,66,67,68].
Technology/DeviceParameters MonitoredMeasurement AccuracyOperational Range/EnvironmentBattery LifeAdvantagesLimitations
Equivital EQ02+ LifeMonitorECG, HR, RR, skin temperature, activityHR: ±1 bpm, Temp: ±0.1 °C−20 °C to +55 °C, up to 95% RH48–72 hHigh accuracy; proven in field trials; ruggedLimited biochemical sensing; chest-strap form factor may cause discomfort
Zephyr BioHarness 3HR, RR, posture, activity, skin temperatureHR: ±1 bpm, Temp: ±0.2 °C−10 °C to +50 °C~26 hLightweight; wireless connectivityShort battery life; limited biochemical data
Hexoskin Smart ShirtECG, RR, activity, sleep metricsHR: ±1 bpm−5 °C to +40 °C~30 hComfortable garment integrationNot fully ruggedized for extreme environments
BodyCap e-Celsius® PerformanceCore body temperature±0.2 °C−20 °C to +50 °C~20 h continuousIngestible capsule; precise internal measurementSingle-use; no multi-parameter capability
Kenzen PatchHydration status, sweat electrolyte analysis±2% hydration−10 °C to +45 °C24–48 hReal-time biochemical feedbackAdhesive lifespan limits use; less robust in extreme sweat/heat
Garmin Tactix Delta SolarHR, GPS, SpO2, environmental dataHR: ±3 bpm, SpO2: ±2%−20 °C to +50 °CWeeks (solar assist)Long battery; integrated navigationConsumer-grade accuracy; limited clinical validation
WearableMil PrototypeHRV, lactate, joint load, gait analysisHR: ±1 bpm, Lactate: ±0.5 mmol/L−20 °C to +50 °C36–48 hMulti-parameter; AI injury predictionPrototype stage; requires validation
Table 3. Key distinctions between civilian-oriented and military-oriented physiological monitoring [62,63,64,65,66,67,68].
Table 3. Key distinctions between civilian-oriented and military-oriented physiological monitoring [62,63,64,65,66,67,68].
DimensionCivilian-Oriented SystemsMilitary-Oriented Systems
Primary PurposeFitness tracking, wellness monitoring, chronic disease managementOperational readiness, injury/illness prevention, mission performance optimization
Design EnvironmentControlled, low-risk daily settings (home, gym, hospital)Extreme environments (heat, cold, altitude, high humidity, combat stress)
Durability & RuggedizationConsumer-grade; limited water/sweat resistanceMilitary-grade; resistant to shock, dust, extreme temperatures, and electromagnetic interference
Data Accuracy RequirementsModerate (e.g., ±5 bpm HR, ±1 °C skin temp sufficient for wellness)High precision (e.g., ±1 bpm HR, ±0.2 °C core temp, hydration ±2%) for mission-critical decisions
Battery LifeOptimized for daily use (12–72 h typical)Extended endurance (≥48–72 h continuous use, sometimes weeks with solar assist)
ConnectivityCloud-based, commercial networks (Bluetooth/Wi-Fi)Secure, encrypted tactical communication systems; often works offline with edge computing
Ethical/Privacy ConcernsFocus on consumer consent, data-sharing policiesInvolves chain-of-command oversight, limited autonomy, heightened risks of coercion or misuse
ExamplesApple Watch, Fitbit, Oura Ring, Hexoskin Smart ShirtEquivital EQ02+, Zephyr BioHarness, WearableMil, BodyCap e-Celsius®
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Sipos, D.; Vészi, K.; Bogár, B.; Pető, D.; Füredi, G.; Betlehem, J.; Pandur, A.A. Physiological State Monitoring in Advanced Soldiers: Precision Health Strategies for Modern Military Operations. Sci 2025, 7, 137. https://doi.org/10.3390/sci7040137

AMA Style

Sipos D, Vészi K, Bogár B, Pető D, Füredi G, Betlehem J, Pandur AA. Physiological State Monitoring in Advanced Soldiers: Precision Health Strategies for Modern Military Operations. Sci. 2025; 7(4):137. https://doi.org/10.3390/sci7040137

Chicago/Turabian Style

Sipos, David, Kata Vészi, Bence Bogár, Dániel Pető, Gábor Füredi, József Betlehem, and Attila András Pandur. 2025. "Physiological State Monitoring in Advanced Soldiers: Precision Health Strategies for Modern Military Operations" Sci 7, no. 4: 137. https://doi.org/10.3390/sci7040137

APA Style

Sipos, D., Vészi, K., Bogár, B., Pető, D., Füredi, G., Betlehem, J., & Pandur, A. A. (2025). Physiological State Monitoring in Advanced Soldiers: Precision Health Strategies for Modern Military Operations. Sci, 7(4), 137. https://doi.org/10.3390/sci7040137

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