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Continuous low latency heart rate estimation from painful faces in real time

机译:实时从痛苦的面孔连续低潜伏期心率估计

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Video based heart rate estimation has several advantages compared to the classical method. Current approaches use long time windows (30sec) to calculate heart rates, which results in high latency and is a big disadvantage for a practical use. To overcome this constraint, we propose a low latency approach for continuous frame based heart rate estimation. It is based on combination of face tracking and skin detection using short time windows (10sec) to filter and analyze the extracted PPG signals in real time. In experiments the presented approach performs with high accuracy (85,2%, with error <;3 BPM) under stable illumination conditions using a pain recognition data set including facial expressions and head movement for validation.
机译:与经典方法相比,基于视频的心率估计具有多个优势。当前的方法使用长时间窗口(30秒)来计算心率,这导致高延迟,并且对于实际使用而言是一个很大的缺点。为了克服此约束,我们提出了一种基于连续帧心率估计的低等待时间方法。它基于结合了面部跟踪和使用短时间窗口(10秒)进行皮肤检测的功能,可以实时过滤和分析提取的PPG信号。在实验中,使用包括面部表情和头部移动的疼痛识别数据集进行验证,所提出的方法在稳定的照明条件下具有很高的准确度(85.2%,误差<; 3 BPM)。

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