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Abstract：
OBJECTIVE: We collected naturalistic heart rate data from veterans diagnosed with post-traumatic stress disorder (PTSD) to investigate the effects of various factors on heart rate.
BACKGROUND: PTSD is prevalent among combat veterans in the United States. While a positive correlation between PTSD and heart rate has been documented, specific heart rate profiles during the onset of PTSD symptoms remain unknown.
METHODS: Veterans were recruited during five cycling events in 2017 and 2018 to record resting and activity-related heart rate data using a wrist-worn device. The device also logged self-reported PTSD hyperarousal events. Regression analyses were performed on demographic and behavioral covariates including gender, exercise, antidepressants, smoking habits, sleep habits, average heart rate during reported hyperarousal events, age, glucocorticoids consumption, and alcohol consumption. Heart rate patterns during self-reported PTSD hyperarousal events were analyzed using Auto Regressive Integrated Moving Average (ARIMA). Heart rate data were also compared to an open-access non-PTSD representative case.
RESULTS: Of 99 veterans with PTSD, 91 participants reported at least one hyperarousal event, with a total of 1023 events; demographic information was complete for 38 participants who formed the subset for regression analyses. The results show that factors including smoking, sleeping, gender, and medication significantly affect resting heart rate. Moreover, unique heart rate patterns associated with PTSD symptoms in terms of stationarity, autocorrelation, and fluctuation characteristics were identified.
CONCLUSIONS: Our findings show distinguishable heart rate patterns and characteristics during PTSD hyperarousal events.
CONCLUSIONS: These findings show promise for future work to detect the onset of PTSD symptoms.
BACKGROUND: PTSD is prevalent among combat veterans in the United States. While a positive correlation between PTSD and heart rate has been documented, specific heart rate profiles during the onset of PTSD symptoms remain unknown.
METHODS: Veterans were recruited during five cycling events in 2017 and 2018 to record resting and activity-related heart rate data using a wrist-worn device. The device also logged self-reported PTSD hyperarousal events. Regression analyses were performed on demographic and behavioral covariates including gender, exercise, antidepressants, smoking habits, sleep habits, average heart rate during reported hyperarousal events, age, glucocorticoids consumption, and alcohol consumption. Heart rate patterns during self-reported PTSD hyperarousal events were analyzed using Auto Regressive Integrated Moving Average (ARIMA). Heart rate data were also compared to an open-access non-PTSD representative case.
RESULTS: Of 99 veterans with PTSD, 91 participants reported at least one hyperarousal event, with a total of 1023 events; demographic information was complete for 38 participants who formed the subset for regression analyses. The results show that factors including smoking, sleeping, gender, and medication significantly affect resting heart rate. Moreover, unique heart rate patterns associated with PTSD symptoms in terms of stationarity, autocorrelation, and fluctuation characteristics were identified.
CONCLUSIONS: Our findings show distinguishable heart rate patterns and characteristics during PTSD hyperarousal events.
CONCLUSIONS: These findings show promise for future work to detect the onset of PTSD symptoms.
摘要：
目的：我们收集了被诊断患有创伤后应激障碍（PTSD）的退伍军人的自然心率数据，以研究各种因素对心率的影响。
背景：PTSD在美国退伍军人中普遍存在。虽然创伤后应激障碍和心率之间存在正相关，PTSD症状发作期间的具体心率特征仍未知.
方法：在2017年和2018年的五次自行车比赛中招募了退伍军人，使用腕部佩戴设备记录静息和活动相关的心率数据。该设备还记录了自我报告的PTSD过度唤醒事件。对人口统计学和行为协变量进行回归分析，包括性别，锻炼,抗抑郁药,吸烟习惯,睡眠习惯,报告的过度觉醒事件期间的平均心率，年龄,糖皮质激素消费，和酒精消费。使用自回归综合移动平均（ARIMA）分析了自我报告的PTSD过度唤醒事件期间的心率模式。还将心率数据与开放式非PTSD代表性病例进行了比较。
结果：在99名患有PTSD的退伍军人中，91名参与者报告了至少一次过度觉醒事件，共有1023个事件;构成回归分析子集的38名参与者的人口统计学信息是完整的.结果表明，包括吸烟在内的因素，睡觉,性别,和药物显著影响静息心率。此外，就平稳性而言，与PTSD症状相关的独特心率模式，自相关，并确定了波动特征。
结论：我们的发现显示了PTSD过度觉醒事件期间可区分的心率模式和特征。
结论：这些发现显示了未来检测PTSD症状发作的工作前景。
背景：PTSD在美国退伍军人中普遍存在。虽然创伤后应激障碍和心率之间存在正相关，PTSD症状发作期间的具体心率特征仍未知.
方法：在2017年和2018年的五次自行车比赛中招募了退伍军人，使用腕部佩戴设备记录静息和活动相关的心率数据。该设备还记录了自我报告的PTSD过度唤醒事件。对人口统计学和行为协变量进行回归分析，包括性别，锻炼,抗抑郁药,吸烟习惯,睡眠习惯,报告的过度觉醒事件期间的平均心率，年龄,糖皮质激素消费，和酒精消费。使用自回归综合移动平均（ARIMA）分析了自我报告的PTSD过度唤醒事件期间的心率模式。还将心率数据与开放式非PTSD代表性病例进行了比较。
结果：在99名患有PTSD的退伍军人中，91名参与者报告了至少一次过度觉醒事件，共有1023个事件;构成回归分析子集的38名参与者的人口统计学信息是完整的.结果表明，包括吸烟在内的因素，睡觉,性别,和药物显著影响静息心率。此外，就平稳性而言，与PTSD症状相关的独特心率模式，自相关，并确定了波动特征。
结论：我们的发现显示了PTSD过度觉醒事件期间可区分的心率模式和特征。
结论：这些发现显示了未来检测PTSD症状发作的工作前景。
