Items related to Signal Processing-Driven AI for Healthcare

Signal Processing-Driven AI for Healthcare - Softcover

Rakhmatulin PhD, Ildar; Naik PhD, Ganesh R.

 
9780443492761: Signal Processing-Driven AI for Healthcare
Softcover
ISBN 10: 044349276X ISBN 13: 9780443492761
Publisher: Academic Press, 2026

Synopsis

Signal Processing-Driven AI for Healthcare examines how AI techniques can be applied across four major biosignals―EEG, EMG, EOG, and ECG―to derive clinically meaningful insights. As biomedical data becomes increasingly multimodal, there is a rising need for integrated methodologies that unite these signals within robust, explainable AI pipelines suitable for healthcare environments. This book provides a unified framework that spans data acquisition, preprocessing, feature extraction, modeling, evaluation, and deployment, with an emphasis on reproducibility, practical Python-based implementations, and real-world translation to clinical workflows.

  • Integrates AI-driven signal processing across EEG, EMG, EOG, and ECG
  • Presents end-to-end workflows from data acquisition to deployment
  • Demonstrates multimodal fusion and clinical decision support
  • Emphasizes interpretability, validation, and regulatory considerations
  • Features supplementary website to host the dataset
  • Offers ready-to-use Python notebooks and scripts optimized for Google Collaboration

"synopsis" may belong to another edition of this title.

About the Authors

Dr. Ildar Rakhmatulin is a scientist and the creator of several popular open-source brain-computer interface (BCI) projects. He is the founder of PiEEG, a low-cost BCI solution. His experience includes working as a BCI developer at Imperial College London, a machine learning researcher at Heriot-Watt University, and a researcher in the neurotechnology group at the University of Edinburgh, UK. Additionally, he is the author of neuroscience courses on Udemy.



Dr. Ganesh R. Naik is a leading researcher in biomedical engineering and signal processing, ranked among the top 2% of scientists globally (Stanford University). He earned his PhD in Electronics Engineering from RMIT University, Melbourne (2009), and is currently a Senior Academic and Researcher in Computer Science and IT at Torrens University Australia. Dr. Naik has edited 16 books and published over 150 peer-reviewed papers. He serves as Associate Editor for IEEE Access, Frontiers in Neurorobotics, and two Springer journals. His career is distinguished by fellowships from Baden–Württemberg (Germany), ISSI (Australia), the BridgeTech Program, and the Royal Academy of Engineering (UK). Previously, he held research roles at Flinders University, Western Sydney University, and UTS, contributing to major projects in sleep technology, wearable sensors, and AI-driven biomedical signal processing.

From the Back Cover

Signal Processing-Driven AI for Healthcare examines how AI techniques can be applied across four major biosignals―EEG, EMG, EOG, and ECG―to derive clinically meaningful insights. As biomedical data becomes increasingly multimodal, there is a rising need for integrated methodologies that unite these signals within robust, explainable AI pipelines suitable for healthcare environments. This book provides a unified framework that spans data acquisition, preprocessing, feature extraction, modeling, evaluation, and deployment, with an emphasis on reproducibility, practical Python-based implementations, and real-world translation to clinical workflows.

"About this title" may belong to another edition of this title.

Publisher
Academic Press
Publication date
2026
Language
English
ISBN 10 
044349276X
ISBN 13 
9780443492761
Binding
Paperback
Edition number
1
Number of pages
362