Dataset Information

Feasibility and Reliability of Smartwatch to Obtain Precordial Lead Electrocardiogram Recordings.

ABSTRACT: The Apple Watch is capable of recording single-lead electrocardiograms (ECGs). To incorporate such devices in routine medical care, the reliability of such devices to obtain precordial leads needs to be validated. The purpose of this study was to assess the feasibility and reliability of a smartwatch (SW) to obtain precordial leads compared to standard ECGs. We included 100 participants (62 male, aged 62.8 ± 13.1 years) with sinus rhythm and recorded a standard 12-lead ECG and the precordial leads with the Apple Watch. The ECGs were quantitively compared. A total of 98 patients were able to record precordial leads without assistance. A strong correlation was observed between the amplitude of the standard and SW-ECGs' waves, in terms of P waves, QRS-complexes, and T waves (all p-values < 0.01). A significant correlation was observed between the two methods regarding the duration of the ECG waves (all p-values < 0.01). Assessment of polarity showed a significant and a strong concordance between the ECGs' waves in all six leads (91-100%, all p-values < 0.001). In conclusion, 98% of patients were able to record precordial leads using a SW without assistance. The SW is feasible and reliable for obtaining valid precordial-lead ECG recordings as a validated alternative to a standard ECG.

SUBMITTER: Sprenger N

PROVIDER: S-EPMC8839669 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Feasibility and Reliability of Smartwatch to Obtain Precordial Lead Electrocardiogram Recordings.

Sprenger Nora N Sepehri Shamloo Alireza A Schäfer Jonathan J Burkhardt Sarah S Mouratis Konstantinos K Hindricks Gerhard G Bollmann Andreas A Arya Arash A

Sensors (Basel, Switzerland) 20220205 3

The Apple Watch is capable of recording single-lead electrocardiograms (ECGs). To incorporate such devices in routine medical care, the reliability of such devices to obtain precordial leads needs to be validated. The purpose of this study was to assess the feasibility and reliability of a smartwatch (SW) to obtain precordial leads compared to standard ECGs. We included 100 participants (62 male, aged 62.8 ± 13.1 years) with sinus rhythm and recorded a standard 12-lead ECG and the precordial lea ...[more]

PMID: 35161960

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Project description:BackgroundWenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device, can detect many kinds of abnormal heart disease and perform a single-lead ECG, but its reliability and validity among pregnant women is unclear. The aim of this study was to assess the reliability and validity of heart rate, ECG measurements and diagnostic results by compared the portable device with a clinical 12-lead ECG among pregnant women.MethodsWe conducted a clinical study at a municipal-level maternal and child health care hospital. The pregnant women who visited the ECG room for ECG examination were invited to participate in this study. Each participant underwent three ECG recordings: one with conventional 12-lead ECG and two with WenXinWuYang ECG. The first WenXinWuYang ECG was recorded simultaneously with the 12-lead ECG. We collected heart rate, ECG measurements, and diagnostic results related to arrhythmias from both ECG devices. The data were then analyzed using Spearman rank correlation coefficients, consistency analyses, and Bland-Altman plots.ResultsThe study included 287 ECG recordings from 99 pregnant women, with a balanced distribution across different stages of pregnancy. We observed strong to moderate correlations between the two WenXinWuYang measurements for heart rate (r = 0.847), PR interval (r = 0.728), QRS duration (r = 0.636), QT interval (r = 0.836), and QTc interval (r = 0.648), with a diagnostic consistency rate exceeding 90.0%. When compared with the 12-lead ECG, the mean differences for heart rate, PR interval, QRS duration, QT interval, and QTc interval were - 0.4 ± 3.1 bpm (r = 0.957), 14.6 ± 12.4 ms (r = 0.537), 7.0 ± 8.9 ms (r = 0.136), 2.1 ± 12.0 (r = 0.774), and 6.6 ± 16.5 (r = 0.663), respectively. Although the correlation coefficient was low in QRS duration, Bland-Altman results showed moderate to strong agreement between these intervals. Sinus rhythm recognition was fully consistent with the 12-lead ECG, with higher validity in detecting arrhythmias (sensitivity 84.2%, specificity 97.5%). Similar trends existed among different stages of pregnancy.ConclusionWenXinWuYang demonstrated acceptable reliability and validity in measuring heart rate, ECG measurements, and detecting arrhythmias among pregnant women.

Project description:BackgroundThe standard configuration's set of twelve electrocardiogram (ECG) leads is optimal for the medical diagnosis of diverse cardiac conditions. However, it requires ten electrodes on the patient's limbs and chest, which is uncomfortable and cumbersome. Interlead conversion methods can reconstruct missing leads and enable more comfortable acquisitions, including in wearable devices, while still allowing for adequate diagnoses. Currently, methodologies for interlead ECG conversion either require multiple reference (input) leads and/or require input signals to be temporally aligned considering the ECG landmarks.MethodsUnlike the methods in the literature, this paper studies the possibility of converting ECG signals into all twelve standard configuration leads using signal segments from only one reference lead, without temporal alignment (blindly-segmented). The proposed methodology is based on a deep learning encoder-decoder U-Net architecture, which is compared with adaptations based on convolutional autoencoders and label refinement networks. Moreover, the method is explored for conversion with one single shared encoder or multiple individual encoders for each lead.ResultsDespite the more challenging settings, the proposed methodology was able to attain state-of-the-art level performance in multiple target leads, and both lead I and lead II seem especially suitable to convert certain sets of leads. In cross-database tests, the methodology offered promising results despite acquisition setup differences. Furthermore, results show that the presence of medical conditions does not have a considerable effect on the method's performance.ConclusionsThis study shows the feasibility of converting ECG signals using single-lead blindly-segmented inputs. Although the results are promising, further efforts should be devoted towards the improvement of the methodologies, especially the robustness to diverse acquisition setups, in order to be applicable to cardiac health monitoring in wearable devices and less obtrusive clinical scenarios.

Dataset Information

Feasibility and Reliability of Smartwatch to Obtain Precordial Lead Electrocardiogram Recordings.

Publications

Feasibility and Reliability of Smartwatch to Obtain Precordial Lead Electrocardiogram Recordings.

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