IEEE J Biomed Health Inform. 2024 Jun;28(6):3457-3465. doi: 10.1109/JBHI.2024.3383232. Epub 2024 Jun 6.
A novel method for tracking the tidal volume (TV) from electrocardiogram (ECG) is presented. The method is based on the amplitude of ECG-derived respiration (EDR) signals. Three different morphology-based EDR signals and three different amplitude estimation methods have been studied, leading to a total of 9 amplitude-EDR (AEDR) signals per ECG channel. The potential of these AEDR signals to track the changes in TV was analyzed. These methods do not need a calibration process. In addition, a personalized-calibration approach for TV estimation is proposed, based on a linear model that uses all AEDR signals from a device. All methods have been validated with two different ECG devices: a commercial Holter monitor, and a custom-made wearable armband. The lowest errors for the personalized-calibration methods, compared to a reference TV, were -3.48% [-17.41% / 12.93%] (median [first quartile / third quartile]) for the Holter monitor, and 0.28% [-10.90% / 17.15%] for the armband. On the other hand, medians of correlations to the reference TV were higher than 0.8 for uncalibrated methods, while they were higher than 0.9 for personal-calibrated methods. These results suggest that TV changes can be tracked from ECG using either a conventional (Holter) setup, or our custom-made wearable armband. These results also suggest that the methods are not as reliable in applications that induce small changes in TV, but they can be potentially useful for detecting large changes in TV, such as sleep apnea/hypopnea and/or exacerbations of a chronic respiratory disease.
一种从心电图(ECG)追踪潮气量(TV)的新方法。该方法基于 ECG 衍生呼吸(EDR)信号的幅度。研究了三种不同基于形态的 EDR 信号和三种不同的幅度估计方法,导致每个 ECG 通道有总共 9 个幅度衍生呼吸(AEDR)信号。分析了这些 AEDR 信号跟踪 TV 变化的潜力。这些方法不需要校准过程。此外,还提出了一种基于线性模型的个性化 TV 估计校准方法,该模型使用设备的所有 AEDR 信号。所有方法都使用两种不同的 ECG 设备进行了验证:商用 Holter 监测仪和定制的可穿戴臂带。与参考 TV 相比,个性化校准方法的最低误差为 -3.48%[-17.41%/12.93%](中位数[第一四分位数/第三四分位数])用于 Holter 监测仪,和 0.28%[-10.90%/17.15%]用于臂带。另一方面,未校准方法与参考 TV 的相关性中位数高于 0.8,而个人校准方法的相关性中位数高于 0.9。这些结果表明,使用传统(Holter)设置或我们定制的可穿戴臂带可以从 ECG 追踪 TV 的变化。这些结果还表明,这些方法在诱导 TV 变化较小的应用中不太可靠,但它们可能对检测 TV 的大幅变化(例如睡眠呼吸暂停/低通气和/或慢性呼吸系统疾病恶化)有用。