Institute of Psychology, University Greifswald, Greifswald, Germany.
Institute for Community Medicine, Prevention Research and Social Medicine, University Medicine Greifswald, Greifswald, Germany.
PLoS One. 2022 Oct 5;17(10):e0274994. doi: 10.1371/journal.pone.0274994. eCollection 2022.
Numerous wearables are used in a research context to record cardiac activity although their validity and usability has not been fully investigated. The objectives of this study is the cross-model comparison of data quality at different realistic use cases (cognitive and physical tasks). The recording quality is expressed by the ability to accurately detect the QRS complex, the amount of noise in the data, and the quality of RR intervals.
Five ECG devices (eMotion Faros 360°, Hexoskin Hx1, NeXus-10 MKII, Polar RS800 Multi and SOMNOtouch NIBP) were attached and simultaneously tested in 13 participants. Used test conditions included: measurements during rest, treadmill walking/running, and a cognitive 2-back task. Signal quality was assessed by a new local morphological quality parameter morphSQ which is defined as a weighted peak noise-to-signal ratio on percentage scale. The QRS detection performance was evaluated with eplimited on synchronized data by comparison to ground truth annotations. A modification of the Smith-Waterman algorithm has been used to assess the RR interval quality and to classify incorrect beat annotations. Evaluation metrics includes the positive predictive value, false negative rates, and F1 scores for beat detection performance.
All used devices achieved sufficient signal quality in non-movement conditions. Over all experimental phases, insufficient quality expressed by morphSQ values below 10% was only found in 1.22% of the recorded beats using eMotion Faros 360°whereas the rate was 8.67% with Hexoskin Hx1. Nevertheless, QRS detection performed well across all used devices with positive predictive values between 0.985 and 1.000. False negative rates are ranging between 0.003 and 0.017. eMotion Faros 360°achieved the most stable results among the tested devices with only 5 false positive and 19 misplaced beats across all recordings identified by the Smith-Waterman approach.
Data quality was assessed by two new approaches: analyzing the noise-to-signal ratio using morphSQ, and RR interval quality using Smith-Waterman. Both methods deliver comparable results. However the Smith-Waterman approach allows the direct comparison of RR intervals without the need for signal synchronization whereas morphSQ can be computed locally.
尽管尚未充分研究可穿戴设备在记录心脏活动方面的有效性和可用性，但研究中已使用了许多可穿戴设备来记录心脏活动。本研究的目的是比较不同实际使用情况下（认知和身体任务）的数据质量的跨模型比较。记录质量通过准确检测 QRS 复合体的能力、数据中的噪声量以及 RR 间隔的质量来表示。
将 5 个 ECG 设备（eMotion Faros 360°，Hexoskin Hx1，NeXus-10 MKII，Polar RS800 Multi 和 SOMNOtouch NIBP）连接并同时在 13 名参与者中进行测试。使用的测试条件包括：休息时、跑步机行走/跑步时和认知 2 背任务时的测量。使用新的局部形态质量参数 morphSQ 评估信号质量，该参数定义为百分比标度上的加权峰值噪声与信号比。通过与地面实况注释的比较，使用 eplimited 评估 QRS 检测性能来评估 QRS 检测性能。使用 Smith-Waterman 算法的修改来评估 RR 间隔质量并对不正确的节拍注释进行分类。评估指标包括节拍检测性能的阳性预测值、假阴性率和 F1 分数。
所有使用的设备在非运动条件下均达到了足够的信号质量。在所有实验阶段中，仅在使用 eMotion Faros 360°记录的 1.22％的节拍中发现形态质量值低于 10％的信号质量不足，而 Hexoskin Hx1 的信号质量不足率为 8.67％。尽管如此，所有使用的设备都具有良好的 QRS 检测性能，阳性预测值在 0.985 到 1.000 之间。假阴性率在 0.003 和 0.017 之间。eMotion Faros 360°在所有测试设备中取得了最稳定的结果，仅在通过 Smith-Waterman 方法识别的所有记录中发现 5 个假阳性和 19 个错位节拍。
使用两种新方法评估数据质量：使用 morphSQ 分析噪声与信号比，以及使用 Smith-Waterman 分析 RR 间隔质量。两种方法都提供了可比的结果。但是，Smith-Waterman 方法允许直接比较 RR 间隔，而无需信号同步，而 morphSQ 可以在本地计算。
