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Laboratory-Based Wearable Heart Rate Data Efficacies for Informing Real-world Department of Defense Wearables
Nathan B Knodel1, Scott G McLean1, Christopher DiCesare1
1Exponent, Inc, Biomechanics, Farmington Hills, MI 48331, United States.
Introduction:
Wearable data efficacy directly impacts soldier performance and health, and thus many Department of Defense (DoD) mission readiness decisions. Although wearables and the data they generate are typically validated in controlled lab settings, it remains unclear as to the extent that associated outcomes translate to real-world use cases. This study thus compared wearable data efficacies derived from lab-based and real-world protocols to evaluate their suitability for DoD wearables decisions and requirements.
Materials And Methods:
Heart rate (HR) data were collected from 40 to 70 participants demographically aligned with active military profiles during lab-based protocols and 2 multi-obstacle Spartan Beast races (Texas and Hawaii), respectively. Participants wore a Garmin fēnix 6X Pro Solar (GM) and a Polar H10 chest strap (PT) as the ground truth device. Lab and Spartan protocols included a broad range of activity intensities and dynamics. Garmin fēnix 6X Pro Solar HR efficacies were compared across lab and Spartan datasets to assess congruence. Data contextualization was applied to assess comparative efficacy sensitivities to specific activity characteristics.
Results:
Spartan race obstacles were categorized by intensity and movement dynamics to enable meaningful comparisons. Garmin fēnix 6X Pro Solar HR accuracy was consistent between lab and Spartan datasets for high- and moderate-intensity and dynamic activities, though efficacy decreased as activity intensities and dynamics increased. Garmin fēnix 6X Pro Solar HR accuracy for low-intensity, low-dynamic Spartan obstacles aligned with lab-based activities of daily living.
Conclusions:
Lab-based protocols for wearable HR validation demonstrate strong ecological validity for real-world DoD-relevant scenarios. Minor discrepancies likely stem from differences in activity types or limitations in the race contextualization model adopted herein. Future work should focus on actual military-specific demographics, diverse activity types, and enhanced contextualization to refine a validation framework optimized for DoD applications.
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