Physiological Signal Analysis Methods in Healthcare
A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Methodology, Drug and Device Discovery".
Deadline for manuscript submissions: closed (10 March 2023) | Viewed by 16828
Special Issue Editors
Interests: medical data analysis; multiscale entropy; photoplethysmograph applications; diabetes and prognostic indicators
Special Issues, Collections and Topics in MDPI journals
Interests: hepatobiliary and alimentary tract surgeries; endocrine and breast surgeries; cardiovascular and circulatory physiology; translational research in medicine; stem cell medicine; quality improvement in patient care; translational medicine; physiological signals; cardiovascular physics
2. Taichung Tzuchi Hospital, The Buddhist Tzuchi Medical Foundation, Taichung 42743, Taiwan
Interests: pulse diagnosis; Chinese medicine, translational research in medicine; quality improvement in patient care
Special Issue Information
Dear Colleagues,
With the advances in medical technology and pharmacology in recent decades, the aged population is increasing worldwide. When combined with the Westernized lifestyle of developed countries, this gives rise to chronic diseases such as hypertension and diabetes mellitus that have been reported to contribute to the development of atherosclerosis and dysfunction of the autonomic nervous system, thereby leading to more severe and even life-threatening cardiovascular diseases. On the other hand, serious though they seem, there are no obvious symptoms suggestive of cardiovascular or autonomic nervous diseases in their early stages. Early detection of the signs of these potentially fatal diseases through signal analysis methods, therefore, is of utmost importance in the field of preventive medicine and requires the collaborative effort of clinicians and medical technologists.
In the clinical domain, physiological signal analysis methods aiming at extracting hidden information from medical data are incessantly being explored. They are now commonly used for research activities or in clinical routines for the diagnosis or treatment of various disease entities. In addition to the requirement for the development of new methods in an attempt to improve the cost-effectiveness and accuracy of the existing ones, new applications for new and existing methods also keep emerging. Despite the apparently remote relationship between bioengineering and medicine, the development of the former has begun to unlock the secrets hidden inside different physiological signals through which clinicians could follow the progression or even predict the outcome of a variety of diseases.
This Special Issue is intended to present and discuss physiological signal analysis methods in healthcare (linear/nonlinear analysis) and their applications. It also aims at facilitating the exchange of ideas and promoting interactions between investigators across different specialties. To emphasize the comprehensiveness of the topic, papers focusing on signal analysis ranging from organ to system level in both physiological and pathological situations are anticipated. We sincerely invite investigators to contribute to this Special Issue by submitting reviews and original papers.
Potential topics include, but are not limited to:
- Linear and nonlinear analysis of physiological time series
- Methods in diagnosis or treatment optimization
- Diagnostic decision support systems
- Comprehensive and intensive computing in healthcare information systems
- Visualization methods for healthcare big data
- Artificial intelligence for cardiovascular disease diagnosis
- Computation in healthy aging for nursing home residents
- Data analysis for hypertension and coronary sclerosis
- Data analysis for adult diseases
- Data analysis in personalized and precision medicine
- Medical image analysis for cardiovascular disease diagnosis
- Data analysis for wearable devices
- Traditional Chinese therapeutic approaches
Prof. Dr. Hsien-Tsai Wu
Prof. Dr. Cheuk-Kwan Sun
Prof. Dr. Jian-Jung Chen
Guest Editors
Manuscript Submission Information
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Keywords
- disease and prognostic indicators
- physiological time series
- medical data analysis in healthcare
- bioengineering in healthcare
- cardiovascular relative disease diagnosis
- medical technology
- traditional chinese therapeutic approaches
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