About this Research Topic
Several hemodynamic parameters can be extracted from plethysmography (PPG), a peripheral and non-invasive method for measuring blood volume changes in microvasculature based on a low-cost optical technique. These parameters enable a rich category of cardiovascular assessments including cardiac function and arterial tree condition, which provide an extensive evaluation of patient health conditions. PPG can be accessed by wearables, providing a continuous monitoring solution that opens the door to early disease detection. On the other side, PPG is also an integral instrument ubiquitously applied in hospital care that measures critical information of blood oxygen levels.
The objective of this Research Topic is to spark research that can advance the use of PPG to better assess the cardiovascular condition and detect pathological events at early stage. Novel technologies will allow a reliable and continuous monitorization and a less noisy signal. More powerful algorithms will permit more accurate detection of pathological events, a better prediction of disease outcomes, and the risk stratification of the patients.
This Research Topic welcomes review papers and original research on the following themes but is not limited to them:
• Biomedical Signal Processing: development of novel algorithms to extract relevant physiological information and better predictions of pathological events.
• Continuous monitoring of cardiovascular parameters. through constant assessment of heart and respiration rate, which enables new techniques for early detection of heart and blood vessel disorders.
• AI-based models for hemodynamic parameters extraction. Novel parameters to extract additional health information by leveraging the the complexity of the PPG signal. The development of novel parameters can lead to new applications of PPG.
• Mitigating movement artifacts. Development of novel algorithms to identify noisy segments or recover the noisy segments in order to not lose this part of the signal and allow continuous monitorization.
The objective of this Research Topic is to spark research that can advance the use of PPG to better assess the cardiovascular condition and detect pathological events at early stage. Novel technologies will allow a reliable and continuous monitorization and a less noisy signal. More powerful algorithms will permit more accurate detection of pathological events, a better prediction of disease outcomes, and the risk stratification of the patients.
This Research Topic welcomes review papers and original research on the following themes but is not limited to them:
• Biomedical Signal Processing: development of novel algorithms to extract relevant physiological information and better predictions of pathological events.
• Continuous monitoring of cardiovascular parameters. through constant assessment of heart and respiration rate, which enables new techniques for early detection of heart and blood vessel disorders.
• AI-based models for hemodynamic parameters extraction. Novel parameters to extract additional health information by leveraging the the complexity of the PPG signal. The development of novel parameters can lead to new applications of PPG.
• Mitigating movement artifacts. Development of novel algorithms to identify noisy segments or recover the noisy segments in order to not lose this part of the signal and allow continuous monitorization.
Keywords: Biomedical Signal Processing, Non-invasive Cardiovascular Condition Assessment, Hemodynamic Parameters, Wearables, Photoplethysmography
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
