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Origin and Dynamics of Biomedical Signals

Part of the Intelligent Systems Reference Library book series (ISRL,volume 192)

Abstract

The human body is autonomous and self-controlled. It can coordinate and regulate all the activities in the body through various systems. Most of the systems are governed via some inherently generated and propagated stimuli otherwise known as biomedical signals. Biomedical signals can be broadly classified into electrical and non-electrical biomedical signals based on their origin. Major electrical biomedical signals also known as bioelectrical signals include ECG, EMG and EEG. They are extremely important from physiological and pathological perspectives. Most electrical activity in the body arises because of the potential difference created and maintained by the cell membrane. In addition, the generation and propagation of action potential as a result of different internal and external stimuli control various physiological processes. Thus, the origin, characteristics and variability, depending on external impulse and signal acquisition site, of prominent bioelectrical signals require thorough analysis. Apart from the above mentioned ones, there are other bioelectrical signals, originating from various parts and systems of the body, such as the EOG, ECoG and EGG. Furthermore, the dynamic variability of the bioelectrical signals indicates important physiological changes of the body. Also, there are magnetic, thermal, optic, chemical, mechanical and acoustic signals that can be measured from the body which can be broadly termed as non-electrical biomedical signals. These signals are of wide variety and contribute to several monitoring, diagnosis and analysis of human body.

Keywords

  • Biomedical signals
  • Action potential
  • Bioelectrical signals
  • ECG
  • EMG
  • EEG
  • Evoked Potentials

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Nahiyan, K.M.T., Arefin, A.S.M.S., Rabbani, M., Valdes, A.L. (2021). Origin and Dynamics of Biomedical Signals. In: Ahad, M.A.R., Ahmed, M.U. (eds) Signal Processing Techniques for Computational Health Informatics. Intelligent Systems Reference Library, vol 192. Springer, Cham. https://doi.org/10.1007/978-3-030-54932-9_1

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