A Review of the Importance of Digital Signal Processing in the Medical field

Abstract

A paradigm change in healthcare has been sparked by recent advances in medical technology and the growth of digital health data. This research explores the critical role that data signal processing (DSP) plays in the medical field and how it might transform treatment options, diagnostics, and the standard of care in general. An overview of the growing amount of healthcare data gathered from several sources, such as wearable technology, digital medical records, medical imaging, and continuous patient monitoring devices, is given in the first part. It draws attention to the difficulties presented by the sheer volume, velocity, and diversity of data related to health, which need complex processing techniques to obtain useful insights. Moreover, DSP is essential to the creation of state-of-the-art medical devices, including wearable and implantable health monitoring ones. DSP makes a major contribution to personalized medicine in clinical settings by improving medication techniques. The findings emphasize how crucial DSP is for obtaining relevant patient information from complex biological signals. It looks at how signal processing methods—from simple methods to sophisticated machine learning algorithms—are used to improve signal quality, reduce noise, and reveal patterns in medical data. This study highlights the critical role that DSP plays in the medical industry, especially when it comes to managing digital health records, Internet of Things (IoT) devices, health-related data, prescription methods, and improving healthcare as a whole.