Objective Exertional heat stroke (EHS), characterised by a high core body temperature (Tcr) and central nervous system (CNS) dysfunction, is a concern for athletes, workers and military personnel who must train and perform in hot environments. The objective of this study was to determine whether algorithms that estimate Tcr from heart rate and gait instability from a trunk-worn sensor system can forward predict EHS onset. Methods Heart rate and three-axis accelerometry data were collected from chest-worn sensors from 1806 US military personnel participating in timed 4/5-mile runs, and loaded marches of 7 and 12 miles; in total, 3422 high EHS-risk training datasets were available for analysis. Six soldiers were diagnosed with heat stroke and all had rectal temperatures of >41°C when first measured and were exhibiting CNS dysfunction. Estimated core temperature (ECTemp) was computed from sequential measures of heart rate. Gait instability was computed from three-axis accelerometry using features of pattern dispersion and autocorrelation. Results The six soldiers who experienced heat stroke were among the hottest compared with the other soldiers in the respective training events with ECTemps ranging from 39.2°C to 40.8°C. Combining ECTemp and gait instability measures successfully identified all six EHS casualties at least 3.5 min in advance of collapse while falsely identifying 6.1% (209 total false positives) examples where exertional heat illness symptoms were neither observed nor reported. No false-negative cases were noted. Conclusion The combination of two algorithms that estimate Tcr and ataxic gate appears promising for real-time alerting of impending EHS. No data are available. Data are not publicly available.

中文翻译：

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步态不稳定性和估计的核心温度预测劳力性中暑

目的 以高核心体温 (Tcr) 和中枢神经系统 (CNS) 功能障碍为特征的运动性中暑 (EHS) 是必须在炎热环境中训练和表演的运动员、工人和军事人员所关心的问题。本研究的目的是确定根据心率估计 Tcr 的算法和来自躯干佩戴传感器系统的步态不稳定性是否可以向前预测 EHS 的发作。方法 从 1806 名参加定时 4/5 英里跑步和 7 英里和 12 英里长跑的美国军人的胸戴传感器收集心率和三轴加速度测量数据；总共有 3422 个高 EHS 风险培训数据集可供分析。六名士兵被诊断出中暑，第一次测量时他们的直肠温度都超过了 41°C，并且表现出 CNS 功能障碍。估计的核心温度（ECTemp）是从心率的连续测量中计算出来的。使用模式分散和自相关的特征从三轴加速度计计算步态不稳定性。结果 6名中暑士兵在各训练项目中较其他士兵最热，ECTemps范围为39.2°C至40.8°C。结合 ECTemp 和步态不稳定性测量成功地在倒塌前至少 3.5 分钟识别了所有六名 EHS 伤亡，同时错误地识别了 6.1%（总共 209 个假阳性）的例子，其中既没有观察到也没有报告劳累性热病症状。没有发现假阴性病例。结论 估计 Tcr 和共济失调门的两种算法的组合似乎有望用于实时警报即将发生的 EHS。没有可用的数据。数据不公开。