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Acoustic Monitoring of First Responder's Physiology for Health and Performance Surveillance

机译:关于健康和性能监测的第一响应者生理学的声学监测

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Acoustic sensors have been used to monitor human physiology to assess health and performance. Soldiers, firefighters, and other first responders often have very strenuous and demanding missions in environments that are hazardous to their health. Heart rate variability, breath rate, blood pressure, activity, and other parameters can be continuously monitored with acoustic sensors and transmitted for remote surveillance of personnel status. Body-worn acoustic sensors located at the neck and wrist do an excellent job at detecting heartbeats and other physiological parameters. However, they have difficulty extracting physiology during rigorous exercise or movements due to the motion artifacts sensed. Rigorous activity often indicates that the person is healthy by virtue of being active, and injury often causes the subject to become less active or incapacitated making the detection of physiology easier. One important measure of performance, heart rate variability, is the measure of beat-to-beat timing fluctuations derived from the interval between two adjacent beats. The Lomb periodogram is optimized for non-uniformly sampled data, and can be applied to non-stationary acoustic heart rate features (such as 1st and 2nd heart sounds) to derive heart rate variability and help eliminate errors created by motion artifacts. Simple peak-detection above or below a certain threshold or waveform derivative parameters can produce the timing and amplitude features necessary for the Lomb periodogram and cross-correlation techniques. High-amplitude motion artifacts may contribute to a different frequency or baseline noise due to the timing differences between the noise artifacts and heartbeat features. Data from a firefighter experiment will be presented.
机译:声学传感器已被用于监测人类生理学以评估健康和性能。士兵,消防队员和其他第一个受访者通常在对健康有害的环境中具有非常艰苦和要求的任务。心率可变性,呼吸速率,血压,活动和其他参数可以用声学传感器连续监测,并传输以进行遥控监控人员地位。位于颈部和手腕的身体磨损的声学传感器在检测心跳和其他生理参数时进行优异的工作。然而,由于感测的运动伪影,它们难以在严格的运动或运动期间提取生理学。严谨的活动通常表明,由于活跃,该人是健康的,并且伤害往往会导致受试者变得不那么活跃或丧失能力,使得物理学的检测更容易。性能,心率变异性的一个重要衡量标准,是从两个相邻节拍之间的间隔产生的节拍时间波动的量度。 LONB周期图针对非均匀采样数据进行了优化,并且可以应用于非静止的声学心率特征(例如第一和第二心脏声音),以导出心率变异性并帮助消除由运动伪影产生的误差。在某个阈值或波形衍生物参数的上方或下方的简单峰值检测可以产生LOMB期间图和互相关技术所需的定时和幅度特征。由于噪声伪像和心跳特征之间的定时差异,高幅度运动伪影可能导致不同的频率或基线噪声。将提出消防员实验的数据。

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