Key result
Review highlights biomedical signal processing applications for ECG, EEG, and EMG analysis and noise reduction.
Why the study?
Physiological signals acquired from patients contain valuable diagnostic data but suffer from noise and artifacts, requiring amplification, extraction, and processing to help medical teams make optimal clinical decisions.
Answers are grounded in this paper and cite their sources.
This review highlights the importance of biomedical signal processing, including acquisition and pre-processing approaches, for physiological signals like ECG, EEG, and EMG in healthcare.
Biomedical signal processing is a key area within biomedical engineering that is interested in physiological signals acquired from patients. When these signals analyzed and processed can help medical teams to make their optimal decisions. Physiological signals such as electrocardiogram (ECG), electroencephalogram (EEG), electromyogram (EMG) involve valuable data that contribute solving the issues of patients. These physiological signals suffer from noise and artifacts, and require amplification, extraction and processing. This paper provides a comprehensive review about physiological signals their meanings, importance, applications in the healthcare field, and challenges face signal processing. Also, it includes highlights about signal acquisition and some pre-processing approaches required to obtain the useful information from signals.
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Eng. Aktham Ali Al-Omar, Eng. Sereen Suleiman Batarseh*, Eng. Haya Salem Al-Sheyab (2026) conducted a review in Physiological signals. Biomedical signal processing was evaluated. A comprehensive review of biomedical signal processing highlights its applications in analyzing ECG, EEG, and EMG signals for healthcare decision-making and addresses challenges like noise reduction.
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