Key result
Combining ECG with skin hydration improves early AF detection.
Why the study?
Early detection of AF can reduce stroke risk, but the effects of AF on skin hydration level are missing in most previous studies.
This review highlights the potential of machine learning and deep learning techniques for detecting atrial fibrillation and assessing skin hydration, noting a potential link between dehydration and AF risk.
Answers are grounded in this paper and cite their sources.
Combining ECG with skin hydration sensing may aid early AF detection; extends single-modality algorithms but remains hypothesis-generating pending trials.
Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmia, with a prevalence of 1–2% in the community, increasing the risk of stroke and myocardial infarction. Early detection of AF, typically causing an irregular and abnormally fast heart rate, can help reduce the risk of strokes that are more common among older people. Intelligent models capable of automatic detection of AF in its earliest possible stages can improve the early diagnosis and treatment. Luckily, this can be made possible with the information about the heart's rhythm and electrical activity provided through electrocardiogram (ECG) and the decision-making machine learning-based autonomous models. In addition, AF has a direct impact on the skin hydration level and, hence, can be used as a measure for detection. In this paper, we present an independent review along with a comparative analysis of the state-of-the-art techniques proposed for AF detection using ECG and skin hydration levels. This paper also highlights the effects of AF on skin hydration level that is missing in most of the previous studies.
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Liaqat et al. (2021) conducted a review in Atrial fibrillation. ECG and skin hydration level-based AF detection techniques was evaluated. A comparative review of state-of-the-art techniques for atrial fibrillation detection highlights the utility of combining ECG with skin hydration levels to improve early diagnosis.
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