Moscato Serena, Palmerini Luca, Palumbo Pierpaolo, Chiari Lorenzo
Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi" - DEI, University of Bologna, Bologna, Italy.
Health Sciences and Technologies-Interdepartmental Center for Industrial Research (CIRI-SDV), University of Bologna, Bologna, Italy.
Front Digit Health. 2022 Jul 7;4:912353. doi: 10.3389/fdgth.2022.912353. eCollection 2022.
The photoplethysmographic (PPG) signal has been applied in various research fields, with promising results for its future clinical application. However, there are several sources of variability that, if not adequately controlled, can hamper its application in pervasive monitoring contexts. This study assessed and characterized the impact of several sources of variability, such as physical activity, age, sex, and health state on PPG signal quality and PPG waveform parameters (Rise Time, Pulse Amplitude, Pulse Time, Reflection Index, Delta T, and DiastolicAmplitude). We analyzed 31 24 h recordings by as many participants (19 healthy subjects and 12 oncological patients) with a wristband wearable device, selecting a set of PPG pulses labeled with three different quality levels. We implemented a Multinomial Logistic Regression (MLR) model to evaluate the impact of the aforementioned factors on PPG signal quality. We then extracted six parameters only on higher-quality PPG pulses and evaluated the influence of physical activity, age, sex, and health state on these parameters with Generalized Linear Mixed Effects Models (GLMM). We found that physical activity has a detrimental effect on PPG signal quality quality (94% of pulses with good quality when the subject is at rest vs. 9% during intense activity), and that health state affects the percentage of available PPG pulses of the best quality (at rest, 44% for healthy subjects vs. 13% for oncological patients). Most of the extracted parameters are influenced by physical activity and health state, while age significantly impacts two parameters related to arterial stiffness. These results can help expand the awareness that accurate, reliable information extracted from PPG signals can be reached by tackling and modeling different sources of inaccuracy.
光电容积脉搏波描记法（PPG）信号已应用于多个研究领域，其未来临床应用前景广阔。然而，存在多种变异性来源，如果控制不当，可能会阻碍其在普及监测环境中的应用。本研究评估并描述了身体活动、年龄、性别和健康状况等多种变异性来源对PPG信号质量和PPG波形参数（上升时间、脉搏幅度、脉搏时间、反射指数、ΔT和舒张期幅度）的影响。我们使用腕带可穿戴设备分析了31名参与者（19名健康受试者和12名肿瘤患者）的24小时记录，选择了一组标记有三种不同质量水平的PPG脉冲。我们实施了多项逻辑回归（MLR）模型来评估上述因素对PPG信号质量的影响。然后，我们仅对高质量的PPG脉冲提取了六个参数，并使用广义线性混合效应模型（GLMM）评估了身体活动、年龄、性别和健康状况对这些参数的影响。我们发现身体活动对PPG信号质量有不利影响（受试者休息时94%的脉冲质量良好，而剧烈活动时为9%），并且健康状况会影响最佳质量的可用PPG脉冲的百分比（休息时，健康受试者为44%，肿瘤患者为13%）。大多数提取的参数受身体活动和健康状况的影响，而年龄显著影响与动脉僵硬度相关的两个参数。这些结果有助于提高人们的认识，即通过解决和建模不同的不准确来源，可以从PPG信号中提取准确、可靠的信息。
