Research Projects

Cardiovascular diseases are a major health concern and cause of mortality worldwide, particularly in India and the Us due to the COVID-19 pandemic. Electrocardiography (ECG) is a popular cardiac monitoring tool, but it is time-consuming and inefficient for detecting severe cardiac diseases. Vectorcardiogram (VCG) is a crucial physiological indicator used in detecting cardiovascular diseases, providing a more accurate and thorough depiction of heart electrical activity. However, cardiology examination facilities are not easily accessible, especially in remote and highly populated areas. Telemedicine or tele-cardiology units with the Internet of Things (IoT) are potential solutions, but they require costly bandwidth and digitized data, making them problematic for telemedicine-based applications. This research aims to develop efficient compression and reconstruction algorithms for VCG signals to save storage space and resources while preserving signal quality for diagnostic purposes. This research proposes a novel compression algorithm for real-time compression of VCG data and a reconstruction algorithm using matrix completion-based techniques to improve reconstruction performance. The proposed algorithm aims to minimize the data size of VCG signals while preserving the quality of clinical information contained within the compressed data. The research also aims to improve reconstruction efficiency for these signals using recently developed transforms like tunable-Q wavelet transform and hybrid transforms.