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一种用于智能手机摄像头光电容积脉搏波描记法的校准方法。

A calibration method for smartphone camera photophlethysmography.

作者信息

Xuan Yinan, Barry Colin, Antipa Nick, Wang Edward Jay

机构信息

Electrical and Computer Engineering, UC San Diego, La Jolla, CA, United States.

The Design Lab, UC San Diego, La Jolla, CA, USA.

出版信息

Front Digit Health. 2023 Nov 24;5:1301019. doi: 10.3389/fdgth.2023.1301019. eCollection 2023.

Abstract

Smartphone camera photoplethysmography (cPPG) enables non-invasive pulse oximetry and hemoglobin concentration measurements. However, the aesthetic-driven non-linearity in default image capture and preprocessing pipelines poses challenges for consistency and transferability of cPPG across devices. This work identifies two key parameters-tone mapping and sensor threshold-that significantly impact cPPG measurements. We propose a novel calibration method to linearize camera measurements, thus enhancing consistency and transferability of cPPG across devices. A benchtop calibration system is also presented, leveraging a microcontroller and LED setup to characterize these parameters for each phone model. Our validation studies demonstrate that, with appropriate calibration and camera settings, cPPG applications can achieve 74% higher accuracy than with default settings. Moreover, our calibration method proves effective across different smartphone models (), and calibrations performed on one phone can be applied to other smartphones of the same model (), enhancing consistency and scalability of cPPG applications.

摘要

智能手机摄像头光电容积脉搏波描记法(cPPG)可实现无创脉搏血氧饱和度和血红蛋白浓度测量。然而,默认图像采集和预处理流程中受美学驱动的非线性特性,给cPPG在不同设备间的一致性和可转移性带来了挑战。这项工作识别出两个对cPPG测量有显著影响的关键参数——色调映射和传感器阈值。我们提出了一种新颖的校准方法,以使摄像头测量线性化,从而提高cPPG在不同设备间的一致性和可转移性。还介绍了一种台式校准系统,利用微控制器和LED设置来为每个手机型号表征这些参数。我们的验证研究表明,通过适当的校准和摄像头设置,cPPG应用的准确率可比默认设置时提高74%。此外,我们的校准方法在不同智能手机型号上均证明有效,并且在一部手机上进行的校准可应用于同一型号的其他智能手机,提高了cPPG应用的一致性和可扩展性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b83f/10705321/4f6d4d2560f8/fdgth-05-1301019-g001.jpg

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