Executive Summary : | Atrial Fibrillation (AF) is a prevalent heart arrhythmia that affects 1-1.5% of the world's population, with almost 8 crore people suffering from it. The DARPAN technology aims to develop a stand-alone device at a point of care for early detection of AF, facilitating better clinical decision-making and disease management in rural India where there is no easy access to hospitals and doctors. This technology can be installed in rural medical centers, preventing patients from long travel and regular doctor visits. The DARPAN device uses a cloud platform to integrate diagnostic equipment and applications, enabling precise detection and prediction of cardiac illnesses in the initial state. It links patients to their medical professionals and enables the exchange of medical data over a secure platform, reducing unnecessary hospital trips and strain on healthcare organizations. The research proposal aims to develop new technology and processes in ECG recording to address AF health issues. The research vision is to develop a DARPAN ECG system to provide point-of-care diagnosis to patients from home through telemetry, assisting clinicians in real-time, improving diagnostic criteria and clinical decision-making, and allowing patients to prevent travel, especially for patients in rural India. The hypothesis to be tested includes building a reliable, efficient method for detecting AF automatically using Deep Learning (DL) from long-term surface Electrocardiogram (ECG) data, extracting high-level clinical features using a high-end AI model, training and verifying the model on distinct standard datasets, demonstrating "DARPAN" to clinical partners, and seeking commercialization partners to bring the device to market. |