Key result
ECG signal analysis shows research potential for non-invasive diabetes detection despite non-specific QRS abnormalities.
Why the study?
It has become crucial to highlight the possibilities and advances that can be derived from an ECG signal, particularly for creating awareness, understanding, and finding the correlation between ECG signals and diabetes mellitus.
This review highlights the potential and challenges of using ECG signal processing and machine learning for the non-invasive detection and monitoring of diabetes mellitus.
ECG diabetes detection merits prospective validation; leaves open any clinical role pending higher-level evidence.
Electrocardiography (ECG) is crucial in the medical field to assess cardiovascular diseases. ECG signal generates information, i.e., QRS complexes that imply the cardiac health of the human body. It is depicted in the form of a graph with voltage versus time interval. A distorted, inverted, lagged, small waveform implies an abnormality in a cardiac system. This study highlights the generation of an ECG signal, QRS complexes undertoned towards different diseases, event detection, and signal processing methods. It has become crucial to highlight the possibilities and advances that can be derived from an ECG signal. Throughout this study, an instance of diabetes mellitus (DM) is considered for creating concrete awareness and understanding of an ECG signal in DM. This study focuses on finding the correlation between ECG and DM. Detection of DM from ECG signal is also studied. The findings of this survey paper conclude that the correlation between DM individuals with cardiovascular complications has autonomic neuropathy, which may lead to myocardial infarction. It is also found that the QRS complex and its abnormalities are not specific to complications in DM. However, non-invasive detection of diabetes through ECG signals demonstrates future research potential.
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Rajeswari et al. (2024) conducted a review in Diabetes mellitus. Electrocardiography (ECG) signal analysis was evaluated. Electrocardiography signal analysis indicates that while QRS complex abnormalities are not specific to diabetes mellitus, non-invasive detection of diabetes through ECG shows future research potential.
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