Graphene in Wearable Sensors for Health Monitoring

Erscheinungsjahr 2025
ISBN: 978-981-968849-4
Verlag: Springer

Buch, Englisch, 119 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 213 g

Reihe: SpringerBriefs in Applied Sciences and Technology

This book highlights the advancement of graphene-based non-invasive sensors for health monitoring. Graphene has been considered the strongest and thinnest known material to date. Unlike most semiconductor systems, its two-dimensional (2D) electronic state can be accessed directly by tunneling or other local probes. With their mechanical, thermal, and electrical properties, graphene-based materials have shown effectiveness in sensing various biophysical and biochemical signals such as body temperature, heart rate, respiration rate, blood pressure, blood glucose levels and electrocardiograms, electromyograms, and electroencephalograms.

Zielgruppe

Research

Autoren/Hrsg.

Debnath, Sourabhi

Debnath, Tanmoy

Moni, Mohammad Ali

Paul, Manoranjan

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Naturwissenschaften Biowissenschaften Biowissenschaften
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Forschungsmethodik, Wissenschaftliche Ausstattung
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Naturwissenschaften Physik Thermodynamik Festkörperphysik, Kondensierte Materie

Inhaltsverzeichnis

Chapter 1. Introduction of Graphene.- Chapter 2. Advantages of graphene over other materials.- Chapter 3. Biocompatibility of graphene.- Chapter 4. Application of graphene as a non-invasive biochemical sensor.- Chapter 5. Application of graphene as a non-invasive biochemical sensor.- Chapter 6. Challenges.

Über Autor(innen)

Dr Sourabhi Debnath is presently engaged as a researcher under the seed funding initiative of the Artificial Intelligence and Cyber Futures Institute (AICF) at Charles Sturt University (CSU), Australia. She holds a PhD in Nanotechnology from Technological University Dublin (TUD), Ireland, and an MSc by research from the Department of Electrical and Electronic Engineering (EEE), Rajshahi University (RU), Bangladesh. Dr Debnath graduated with distinction, achieving First Class First and First Class Third positions in her MSc and BSc (Hons) degrees, respectively, and was honoured with the prestigious University Gold Medal. Prior to her appointment at CSU, she served as an Assistant Professor in the EEE, RU and as an Assistant Lecturer at TUD, Ireland. Her primary research interests encompass data analysis, hyperspectral imaging, digital health, artificial intelligence, sensors, and nanotechnology.

Dr Tanmoy Debnath is currently employed as a Lecturer within the School of Computing, Mathematics and Engineering (SCME), and is also a Research Affiliate of the Artificial Intelligence and Cyber Futures Institute (AICF) at Charles Sturt University (CSU), Australia. He was awarded a PhD by Technological University Dublin (TUD), Ireland. Prior to this, he obtained MSc and BSc Engineering degrees from Chalmers University of Technology (CUT), Sweden, and the Bangladesh University of Engineering and Technology (BUET), Bangladesh, respectively. His research interests include artificial intelligence, e-Health, hyperspectral imaging, quantum computing, and computer vision.

Dr Mohammad Ali Moni obtained his Ph.D. in machine learning and data science from Cambridge University, UK. He is Program Lead of AI & Digital Health Technology at Charles Sturt University. He is also Research Professor at Washington University of Science & Technology, USA, and Group Leader and Head of the AI and Digital Health Technology Lab at the University of Queensland, Australia. His research interests are in the areas of AI-driven health data applications, AI-enabled portable device development, and bioinformatics.

Professor Manoranjan Paul is an experienced researcher in AI and Professor of Computer Science, Director of the Computer Vision Lab, and Head of the Machine Vision and Digital Health (MAVIDH) Research Group at CSU. He is an award-winning researcher e.g. Researcher of the Year in 2017 by Australian Computer Society (ACS), listed in the Best Computer Science Scientists in Australia, and Top 2% Scientist (Elsevier & Stanford). His research interests include AI, video compression, quantum computing, machine vision, and digital health.