Biomedical Signal Processing and Data Analytics in Healthcare Systems
This special issue belongs to the section "Biomedical Information and Health".
Special Issue Information
Dear Colleagues,
Internet of Thing (IOT) devices, noninvasive measurement methods, and wearable sensors have resulted in an abundant amount of data in biomedical and healthcare systems. The proper use and analysis of these data can assist clinicians and medical doctors in making real-time decisions and saving lives by sending early warning signals, predicting, monitoring, and diagnosing patients’ conditions. On the other hand, these measurement approaches are of course subject to significant noise effects due to sensor imperfections and imperfect sensor-patient contacts and subject to a high level of uncertainty. Thus, there is a significant signal processing challenge in extracting physiological state parameters reliably for all patient types. The aim of this Special Issue is to bring together original research and review articles researching the signal and pattern processing potential of extracting physiological parameters using traditional and modern advances in principled signal processing. Topics of interest include signal processing methods, machine learning, and intelligent methods to analyze biomedical signals, pattern processing, new measuring trends and analysis, and decision making.
Dr. Randa Herzallah
Guest Editor
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Keywords
- Analysis of biomedical signals and images
- Real-time decision making, prognosis, and diagnosis
- Statistical analysis, machine learning, and deep learning for biomedical signals
- Signal processing of data collected using noninvasive sensors
- Frequency and time-domain analysis of biomedical signals
- New classification, filtering, and visualization methods
- New advancements and applications of advanced and intelligent processing of biosignals for various applications
- New measuring trends and analysis
- Current and future trends in analyzing the most popular biosignals such as EEG, ECG, and EMG
- Uncertainty characterization and incorporation for more robust clinical decisions
- Differences between adult, infant, and neonate biomedical signals and image analysis
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Published Papers
Information - ISSN 2078-2489