论文标题
信噪比比在光合估算的光学传感器估算中比采样率更重要
Signal-to-noise ratio is more important than sampling rate in beat-to-beat interval estimation from optical sensors
论文作者
论文摘要
光杀菌成像成像(PPGI)允许从空间分辨记录的脉搏波来确定顺序Beat-to-Beat间隔(BBI)(BBI)和脉搏波速度的脉搏率变化。无论哪种情况,都必须有足够的时间准确性。 提出的工作调查了来自光摄像学信号的BBI估计的时间准确性。在综合数值模拟中,我们系统地评估了对均方根误差(RMSE)在真实BBI和估计的BBI之间的采样率,信噪比(SNR)以及beat-beat形状变化的影响。 我们的结果表明,在使用插值时,在超过14 Hz的采样速率下仅存在小错误。例如,平均RMSE为14 Hz的采样率为3 ms,SNR为18 dB。进一步提高采样率只会导致边际改善,例如将采样率提高到50 Hz的三倍以外,将误差降低了约。 14%。最重要的发现与SNR有关,SNR与采样率相比,该发现对误差的影响更大。例如,以14 Hz采样率以14 Hz采样率将SNR从18 dB增加到24 dB,将误差降低了几乎50%至1.5 ms。此外,微妙的跳动形状变化,果断地增加了800%的误差。 我们的结果在三个方面高度相关:首先,它们在文献中有关最低采样率的文献中部分解释了不同的结果。其次,他们强调了考虑SNR的重要性,并可能在调查最小采样率的研究中塑造了变化。第三,他们强调了适当的处理技术增加SNR的重要性。重要的是,尽管我们的动力是PPGI,但提出的工作立即适用于在其他设置(例如可穿戴设置)中与PPG和PPG联系。为了实现进一步的调查,我们可以免费提供用于建模和仿真的脚本。
Photoplethysmographic Imaging (PPGI) allows the determination of pulse rate variability from sequential beat-to-beat intervals (BBI) and pulse wave velocity from spatially resolved recorded pulse waves. In either case, sufficient temporal accuracy is essential. The presented work investigates the temporal accuracy of BBI estimation from photoplethysmographic signals. Within comprehensive numerical simulation, we systematically assess the impact of sampling rate, signal-to-noise ratio (SNR), and beat-to-beat shape variations on the root mean square error (RMSE) between real and estimated BBI. Our results show that at sampling rates beyond 14 Hz only small errors exist when interpolation is used. For example, the average RMSE is 3 ms for a sampling rate of 14 Hz and an SNR of 18 dB. Further increasing the sampling rate only results in marginal improvements, e.g. more than tripling the sampling rate to 50 Hz reduces the error by approx. 14%. The most important finding relates to the SNR, which is shown to have a much stronger influence on the error than the sampling rate. For example, increasing the SNR from 18 dB to 24 dB at 14 Hz sampling rate reduced the error by almost 50% to 1.5 ms. Subtle beat-to-beat shape variations, moreover, increase the error decisively by up to 800%. Our results are highly relevant in three regards: first, they partially explain different results in the literature on minimum sampling rates. Second, they emphasize the importance to consider SNR and possibly shape variation in investigations on the minimal sampling rate. Third, they underline the importance of appropriate processing techniques to increase SNR. Importantly, though our motivation is PPGI, the presented work immediately applies to contact PPG and PPG in other settings such as wearables. To enable further investigations, we make the scripts used in modelling and simulation freely available.