Reconsider photoplethysmogram signal quality assessment in the free living environment.

IF 2.3 4区 医学 Q3 BIOPHYSICS
Yan-Wei Su, Chia-Cheng Hao, Gi-Ren Liu, Yuan-Chung Sheu, Hau-Tieng Wu
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引用次数: 0

Abstract

Objective.Assessing signal quality is crucial for biomedical signal processing, yet a precise mathematical model for defining signal quality is often lacking, posing challenges for experts in labeling signal qualities. The situation is even worse in the free living environment.Approach.We propose to model a PPG signal by the adaptive non-harmonic model (ANHM) and apply a decomposition algorithm to explore its structure, based on which we advocate a reconsideration of the concept of signal quality.Main results.We demonstrate the necessity of this reconsideration and highlight the relationship between signal quality and signal decomposition with examples recorded from the free living environment. We also demonstrate that relying on mean and instantaneous heart rates derived from PPG signals labeled as high quality by experts without proper reconsideration might be problematic.Significance.A new method, distinct from visually inspecting the raw PPG signal to assess its quality, is needed. Our proposed ANHM model, combined with advanced signal processing tools, shows potential for establishing a systematic signal decomposition based signal quality assessment model.

重新考虑自由生活环境中的光敏血流图信号质量评估。
背景:评估信号质量对生物医学信号处理至关重要,但目前往往缺乏定义信号质量的精确数学模型,这给标注信号质量的专家带来了挑战。在自由生活环境中,情况甚至更糟:方法:我们建议使用自适应非谐波模型(ANHM)对 PPG 信号进行建模,并应用分解算法探索其结构,在此基础上重新考虑信号质量的概念:结果:我们证明了重新考虑的必要性,并通过自由生活环境中记录的例子强调了信号质量与信号分解之间的关系。我们还证明,如果不进行适当的重新考虑,就依赖于从被专家标注为高质量的 PPG 信号中得出的平均和瞬时心率,可能会出现问题:结论:我们需要一种新的方法来评估 PPG 信号的质量,而不是目测原始 PPG 信号。我们提出的 ANHM 模型与先进的信号处理工具相结合,显示出建立基于系统信号分解的信号质量评估模型的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Physiological measurement
Physiological measurement 生物-工程:生物医学
CiteScore
5.50
自引率
9.40%
发文量
124
审稿时长
3 months
期刊介绍: Physiological Measurement publishes papers about the quantitative assessment and visualization of physiological function in clinical research and practice, with an emphasis on the development of new methods of measurement and their validation. Papers are published on topics including: applied physiology in illness and health electrical bioimpedance, optical and acoustic measurement techniques advanced methods of time series and other data analysis biomedical and clinical engineering in-patient and ambulatory monitoring point-of-care technologies novel clinical measurements of cardiovascular, neurological, and musculoskeletal systems. measurements in molecular, cellular and organ physiology and electrophysiology physiological modeling and simulation novel biomedical sensors, instruments, devices and systems measurement standards and guidelines.
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