Remote photoplethysmography (rPPG) is an unobtrusive solution to heart rate monitoring in drivers. However, disturbances that occur during driving such as driver behavior, motion artifacts, and illuminance variation complicate the monitoring of heart rate. Faced with disturbance, one commonly used assumption is heart rate periodicity (or spectrum sparsity). Several methods improve stability at the expense of tracking sensitivity for heart rate variation. Based on statistical signal processing (SSP) and Monte Carlo simulations, the outlier probability is derived and ADaptive spectral filter banks (AD) is proposed as a new algorithm which provides an explicable tuning option for spectral filter banks to strike a balance between robustness and sensitivity in remote monitoring for driving scenarios. Moreover, we construct a driving database containing over 23 hours of data to verify the proposed algorithm. The influence on rPPG from driver habits (both amateurs and professionals), vehicle types (compact cars and buses), and routes are also evaluated. In comparison to state-of-the-art rPPG for driving scenarios, the mean absolute error in the Passengers, Compact Cars, and Buses scenarios is 3.43, 7.85, and 5.02 beats per minute, respectively. Moreover, AD also won the top third place in the first challenge on remote physiological signal sensing (RePSS) with relative low computational complexity.

中文翻译：

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使用远程光电容积描记法的真实世界驾驶员心率监测框架

远程光电容积脉搏波 (rPPG) 是一种用于驾驶员心率监测的不显眼的解决方案。然而，驾驶过程中发生的干扰，例如驾驶员行为、运动伪影和照度变化，使心率监测变得复杂。面对干扰，一种常用的假设是心率周期性（或频谱稀疏性）。有几种方法以跟踪心率变化的灵敏度为代价来提高稳定性。基于统计信号处理 (SSP) 和蒙特卡罗模拟，推导出异常值概率，并提出了自适应频谱滤波器组 (AD) 作为一种新算法，该算法为频谱滤波器组提供了可解释的调谐选项，以在鲁棒性和灵敏度之间取得平衡在驾驶场景的远程监控中。而且，我们构建了一个包含超过 23 小时数据的驾驶数据库来验证所提出的算法。还评估了驾驶员习惯（业余爱好者和专业人士）、车辆类型（小型汽车和公共汽车）和路线对 rPPG 的影响。与最先进的驾驶场景 rPPG 相比，乘客、紧凑型汽车和巴士场景的平均绝对误差分别为每分钟 3.43、7.85 和 5.02 次。此外，AD还在远程生理信号传感（RePSS）的第一次挑战赛中以相对较低的计算复杂度获得了前三名。与最先进的驾驶场景 rPPG 相比，乘客、紧凑型汽车和巴士场景的平均绝对误差分别为每分钟 3.43、7.85 和 5.02 次。此外，AD还在远程生理信号传感（RePSS）的第一次挑战赛中以相对较低的计算复杂度获得了前三名。与最先进的驾驶场景 rPPG 相比，乘客、紧凑型汽车和巴士场景的平均绝对误差分别为每分钟 3.43、7.85 和 5.02 次。此外，AD还在远程生理信号传感（RePSS）的第一次挑战赛中以相对较低的计算复杂度获得了前三名。