Deep Learning and Signal-Processing Methods for Multisensor Data Fusion

Applications to Ambulatory Health Monitoring

This book focuses on the development of multisensor fusion algorithms for wearable devices that are useful in ambulatory health monitoring using signal-processing and deep learning-based methods. The algorithms described account for the signal quality prior to fusion, in order to enable reliable inferences without contributing to additional computational overhead. The content discussed is beneficial in the broad application of multisensor fusion, as the algorithms developed or discussed in the final chapters are generalized cases of the methods developed in the initial chapters, offering relevance to the broader multisensor fusion community.

Provides a single-source reference to the history, methods and analysis of fusion algorithms

Autor:Arlene John

Verlag:

Springer International Publishing

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Veröffentlichung:	09.12.2025
Seiten	244
Art des Mediums	Digital [Kindle]
Reihe	Engineering (R0)
ISBN-13	978-3-031-96724-5
ISBN-10	3031967240

Über den Autor

Arlene John is an Assistant Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, the Netherlands and a researcher at the Delft Institute of Applied Mathematics at Technical University of Delft, the Netherlands. She received the Bachelor of Technology degree in electrical and electronics engineering from the National Institute of Technology, Calicut, India, in 2017 and the Ph.D. degree in electrical and electronic engineering from University College Dublin, Ireland, in 2022. In the summer of 2016, she was a Research Intern with the Indian Institute of Science, Bangalore, India. During June 2017–June 2018, she was with Bosch India Ltd., as a Project Manager and in engineering and strategy development for hybrid electric vehicles.