Comparing twelve-lead electrocardiography with close-to-heart patch based electrocardiography

Hansen, Ingeborg Helbech; Hoppe, Karsten; Gjerde, Anna; Kanters, Jørgen K.; Sørensen, Helge Bjarup Dissing

doi:10.1109/embc.2015.7318366

Cited by 14 publications

(7 citation statements)

References 12 publications

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“…It has been shown, however, that it is possible to synthesize multiple ECG leads from only a few standard measurements [18]. Only a few studies have investigated the possibility to obtain standard leads from short inter-electrode ECG lead systems [19], but some findings suggest that even a 12-channel ECG reconstruction could be possible using a single 5 cm patch device, which incorporates multiple small-distance ECG lead recordings [20]. Even though the lead field theory seems to support the concept of short-distance ECG recordings, no recommendations on application-specific placements have been established yet, and the evaluation of methods beyond ECG lead estimation from short-distance ECG leads is yet sparse [21].…”

Section: Clinical Background and State-of-the-artmentioning

confidence: 99%

Wearable Cardiorespiratory Monitoring Employing a Multimodal Digital Patch Stethoscope: Estimation of ECG, PEP, LVET and Respiration Using a 55 mm Single-Lead ECG and Phonocardiogram

Klum

Tigges

Pielmuş

et al. 2020

Sensors

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Cardiovascular diseases are the main cause of death worldwide, with sleep disordered breathing being a further aggravating factor. Respiratory illnesses are the third leading cause of death amongst the noncommunicable diseases. The current COVID-19 pandemic, however, also highlights the impact of communicable respiratory syndromes. In the clinical routine, prolonged postanesthetic respiratory instability worsens the patient outcome. Even though early and continuous, long-term cardiorespiratory monitoring has been proposed or even proven to be beneficial in several situations, implementations thereof are sparse. We employed our recently presented, multimodal patch stethoscope to estimate Einthoven electrocardiogram (ECG) Lead I and II from a single 55 mm ECG lead. Using the stethoscope and ECG subsystems, the pre-ejection period (PEP) and left ventricular ejection time (LVET) were estimated. ECG-derived respiration techniques were used in conjunction with a novel, phonocardiogram-derived respiration approach to extract respiratory parameters. Medical-grade references were the SOMNOmedics SOMNO HD TM and Osypka ICON-Core TM . In a study including 10 healthy subjects, we analyzed the performances in the supine, lateral, and prone position. Einthoven I and II estimations yielded correlations exceeding 0.97. LVET and PEP estimation errors were 10% and 21%, respectively. Respiratory rates were estimated with mean absolute errors below 1.2 bpm, and the respiratory signal yielded a correlation of 0.66. We conclude that the estimation of ECG, PEP, LVET, and respiratory parameters is feasible using a wearable, multimodal acquisition device and encourage further research in multimodal signal fusion for respiratory signal estimation.

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Section: Clinical Background and State-of-the-artmentioning

confidence: 99%

Wearable Cardiorespiratory Monitoring Employing a Multimodal Digital Patch Stethoscope: Estimation of ECG, PEP, LVET and Respiration Using a 55 mm Single-Lead ECG and Phonocardiogram

Klum

Tigges

Pielmuş

et al. 2020

Sensors

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“…A non-telemetry version of this monitor, the ePatch (BioTelemetry Inc, USA), is also commercially available. The device can be worn for up to 14 days and needs to be sent back to the manufacturer for data acquisition and review (91).…”

Section: Mobile Continuous Outpatient Telemetrymentioning

confidence: 99%

Remote Cardiac Rhythm Monitoring in the Era of Smart Wearables: Present Assets and Future Perspectives

Xintarakou

Sousonis

Asvestas

et al. 2022

Front. Cardiovasc. Med.

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Remote monitoring and control of heart function are of primary importance for patient evaluation and management, especially in the modern era of precision medicine and personalized approach. Breaking technological developments have brought to the frontline a variety of smart wearable devices, such as smartwatches, chest patches/straps, or sensors integrated into clothing and footwear, which allow continuous and real-time recording of heart rate, facilitating the detection of cardiac arrhythmias. However, there is great diversity and significant differences in the type and quality of the information they provide, thus impairing their integration into daily clinical practice and the relevant familiarization of practicing physicians. This review will summarize the different types and dominant functions of cardiac smart wearables available in the market. Furthermore, we report the devices certified by official American and/or European authorities and the respective sources of evidence. Finally, we comment pertinent limitations and caveats as well as the potential answers that flow from the latest technological achievements and future perspectives.

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“…Healthcare can take advantage of it, especially through telemedical applications in rural areas. Promising approaches are made with ePatch to record data similar to 12-lead ECGs in more field like settings [62] and the Apple Heart Study shows first scientific possibilities to use consumer products for large scale clinical scenarios [63]. While most wearable HR detectors currently rely on PPG, this might change in the future with promising use cases from Apple Watch 4 and Withings Move.…”

Section: Plos Onementioning

confidence: 99%

ECG performance in simultaneous recordings of five wearable devices using a new morphological noise-to-signal index and Smith-Waterman-based RR interval comparisons

et al. 2022

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Background 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. Methods 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. Results 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. Conclusion 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.

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Comparing twelve-lead electrocardiography with close-to-heart patch based electrocardiography

Cited by 14 publications

References 12 publications

Wearable Cardiorespiratory Monitoring Employing a Multimodal Digital Patch Stethoscope: Estimation of ECG, PEP, LVET and Respiration Using a 55 mm Single-Lead ECG and Phonocardiogram

Wearable Cardiorespiratory Monitoring Employing a Multimodal Digital Patch Stethoscope: Estimation of ECG, PEP, LVET and Respiration Using a 55 mm Single-Lead ECG and Phonocardiogram

Remote Cardiac Rhythm Monitoring in the Era of Smart Wearables: Present Assets and Future Perspectives

ECG performance in simultaneous recordings of five wearable devices using a new morphological noise-to-signal index and Smith-Waterman-based RR interval comparisons

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