Contactless Monitoring and Diagnosis of Cardiovascular Disease Using mmWave Radar

Title of the Talk: Contactless Monitoring and Diagnosis of Cardiovascular Disease Using mmWave Radar
Host Faculty: Dr.Praveen Tammana
Speaker: Dr. Arjun Kumar
Date: 06th April 2026
Time: 4pm - 5pm
Venue: Online

Abstract Cardiovascular diseases (CVDs) are the leading causes of death worldwide. Recent global estimates indicate approximately 20.5 million deaths attributable to CVDs, highlighting the magnitude of this issue. Clinical evidence suggests that continuous monitoring and early diagnosis are essential to reduce adverse outcomes (e.g., stroke and heart failure) and support timely clinical decision-making. Conventional monitoring systems, such as electrocardiography (ECG), are considered a clinical gold standard. However, long-term and continuous monitoring is often limited by the need for contact sensors, clinical setups, and associated user burden. Consumer wearables, including single-lead ECG devices and smartwatches, offer potential benefits but are frequently constrained by issues of intermittent use, adherence, and discomfort during prolonged wear. Concurrently, many existing contactless approaches have demonstrated promising performance in controlled environments; however, the reliable monitoring and diagnosis of patients with cardiovascular diseases remain challenging owing to irregular cardiac dynamics. In this talk, I will discuss my research on contactless cardiovascular monitoring and diagnosis using millimeter-wave (mmWave) radar. My research focuses on signal processing and machine learning techniques to capture subtle cardiac-induced chest motion and convert it into physiologically meaningful cardiac waveforms. First, I will present a radar-driven contactless system for cardiac waveform reconstruction and reliable monitoring and diagnosis in patients with cardiovascular diseases. Subsequently, I will briefly discuss additional research on radar-based health sensing and selected studies on smart-device battery management and battery health estimation. Finally, I will outline future research directions toward scalable, non-contact monitoring and diagnosis systems to support next-generation digital health technologies.

Bio Dr. Arjun Kumar is currently a postdoctoral researcher at the Korea Advanced Institute of Science and Technology (KAIST), South Korea. He obtained his Doctor of Philosophy (Ph.D.) in Computer Science from KAIST. Dr. Arjun received his Bachelor of Technology (B.Tech.) in Computer Science and Engineering from the Indian Institute of Technology Guwahati, India. His research is centered on mobile and ubiquitous computing systems, with a particular focus on contactless cardiac health sensing and energy-efficient mobile systems. His work investigates the use of mmWave radar, signal processing, and machine learning for cardiovascular health monitoring, as well as system-level strategies for enhancing mobile battery performance. His research findings have been published at world-premier venues, including ACM MobiSys, ACM SenSys, ACM HotMobile, IEEE Transactions, and IEEE Translational journals.