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Introduction to Non-Invasive Biomedical Signals for Healthcare

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Advances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning

Abstract

With the advancement of medical science, new healthcare methods have been introduced. Biomedical signals have provided us with a deep insight into the working of the human body. Invasive biomedical signaling and sensing involve inserting sensors inside the human body. Non-invasive biomedical signals such as electroencephalogram (EEG), electromyogram (EMG), electrocardiogram (ECG), electrooculogram (EOG), phonocardiogram (PCG), and photoplethysmography (PPG) can be acquired by placing sensors on the surface of the human body. After the acquisition of these biomedical signals, further processing such as artifact removal and feature extraction is required to extract vital information about the subject’s health and well-being. In addition to conventional signal processing and analysis tools, advanced methods that involve machine and deep learning techniques were introduced to extract useful information from these signals. There are several applications of non-invasive biomedical signal processing, including monitoring, detecting, and estimating physiological and pathological states for diagnosis and therapy. For example, detection and monitoring of different types of cancer, heart diseases, blood vessel blockage, neurological disorders, etc. In addition, biomedical signals are also used in brain control interfaces (BCI), Neurofeedback and biofeedback systems to improve the mental and physical health of the subjects.

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Authors and Affiliations

  1. Department of Electronic Engineering, Faculty of Engineering and Green Technology, Universiti Tunku Abdul Rahman, Kampar, Malaysia

    Danyal Mahmood, Hannan Naseem Riaz & Humaira Nisar

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  1. Danyal Mahmood
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  2. Hannan Naseem Riaz
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  3. Humaira Nisar
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Correspondence to Humaira Nisar .

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Editors and Affiliations

  1. Electrical and Computer Engineering Department, Effat University, Jeddah, Saudi Arabia

    Saeed Mian Qaisar

  2. Department of Electronic Engineering Faculty of Engineering and Green Technology, Universiti Tunku Abdul Rahman, Kampar, Malaysia

    Humaira Nisar

  3. Institute of Biomedicine Faculty of Medicine, University of Turku, Turku, Finland

    Abdulhamit Subasi

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Mahmood, D., Riaz, H.N., Nisar, H. (2023). Introduction to Non-Invasive Biomedical Signals for Healthcare. In: Qaisar, S.M., Nisar, H., Subasi, A. (eds) Advances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning. Springer, Cham. https://doi.org/10.1007/978-3-031-23239-8_1

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  • DOI: https://doi.org/10.1007/978-3-031-23239-8_1

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