New Frontiers of Cardiovascular Screening using Unobtrusive Sensors, AI, and IoT - Tapa blanda

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Anirban Dutta Choudhury received his B.E. in Electronics and Telecommunication Engineering in 2005 from Jadavpur University, India and M.Sc. in Embedded System Design in 2008 from University of Lugano, Switzerland.
He has more than 15 years of experience, all in R&D departments in various geographies and scale of companies such as NXP Semiconductors Netherlands, PIXY AG Switzerland and Tata Consultancy Services India. His research interests encompass Noninvasive Physiological sensing in Digital Health and AI-driven Sensor Signal Informatics.
Anirban has more than 40 publications till date in reputed Journals and Conferences. He has filed for more than 25 unique patents and has 10 patents granted to him.

Rohan Banerjee has more than 10 years of experience in digital signal processing and machine learning. Currently, works as a scientist at TCS Research. He received his M.Tech from the department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur in 2011. His main research area includes signal processing with a strong focus on biomedical signal processing, pattern recognition, machine learning in digital healthcare and cardiology. Rohan has more than thirty papers published in peer-reviewed conferences and journals and has five granted patents.

Sanjay Kimbahune received his BE degree in Electronics from Amravati University with distinction. He is working as a senior scientist in TCS Research and Innovation. He has experience of 32 years in diverse fields of CTI, Video Conference solutions and Mobile applications for masses. He is passionate about solving problems faced by the masses by developing frugal and scalable technology solutions. He has published 33 papers and has 48 granted patents. His current research focus is on engineering innovative devices for screening cardiovascular diseases in a scalable and frugal way. He is mentoring many startups working in the healthcare domain. He was instrumental in developing mKRISHI - platform for farmers. mKRISHI has reached about 1 million farmers as well has received many prestigious awards.

Arpan Pal has more than 29 years of experience in the areas of Intelligent Sensing, Signal Processing & AI, Edge Computing and Affective Computing. Currently, as Distinguished Chief Scientist and Research Area Head, Embedded Devices and Intelligent Systems, TCS Research, he is working in the areas of Connected Health, Smart Manufacturing and Remote Sensing.
He is on the editorial board of notable journals like ACM Transactions on Embedded Systems, Springer Nature Journal on Computer Science and is on the TPC of notable conferences like ICASSP and EUSIPCO. He has filed 180+ patents (out of which 95+ granted in different geographies) and has published 140+ papers and book chapters in reputed conferences and journals. He has also authored two books – one on IoT and another on Digital Twins in Manufacturing. He is on the governing/review/advisory board of some of the Indian Government organizations such as CSIR, MeitY, Educational Institutions like IIT, IIIT and Technology Incubation Centers like TIH.
Prior to joining Tata Consultancy Services (TCS), Arpan had worked for DRDO, India as Scientist for Missile Seeker Systems and in Rebeca Technologies (erstwhile Macmet Interactive Technologies) from as their Head of Real-time Systems. He is a B. Tech and M. Tech from IIT, Kharagpur, India and PhD. from Aalborg University, Denmark.

De la contraportada

New Frontiers of Cardiovascular Screening using Unobtrusive Sensors, AI and IoT offers unique coverage of processing time-series physiological sensor data. This book is a result of in-depth research on application of Artificial Intelligence using non-invasive sensors in order to detect tell-tale signatures of early cardiovascular diseases and associated health markers. The first section, consisting of three chapters, introduce the need for cardiovascular sensing followed by generalized techniques of physiological sensing and automated AI-based analytics. The second section demonstrates the strategy of fine-tuning AI for multiple use cases in four chapters: Arrhythmia, Heart blocks, Hypertension and Non-cardiac diseases. The final section has one chapter which highlights upcoming sensing and AI techniques which can facilitate screening and management of cardiovascular disease in future.

The authors have developed this book for graduate students, practitioners, researchers, engineers, and computer scientists interested in exploring a pragmatic approach to use of sensing and AI to screen for cardiovascular diseases and developing personalized and higher standards of patient care management with modern technologies.