Methods for arterial stiffness detection

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Cardiovascular diseases are the leading cause of death in Germany, with conditions like atherosclerosis often remaining undetected until they result in serious events such as heart attacks or strokes. Early detection of arterial stiffness is crucial for preventing these complications. Current methods for identifying arterial stiffness are not suitable for widespread screening. We have developed non-invasive methods and algorithms to predict arterial stiffness. Our approach includes two methods for estimating key risk factors that determine arterial stiffness. These risk parameters are obtained using a piezoelectric sensor placed on the neck and photoplethysmography from the finger. By analyzing the rising edge of the signal from the piezoelectric sensor and the area under the catacrotic phase of the photoplethysmogram, we can assess cardiovascular disease risk. These parameters, combined with established risk factors, are processed through a neural network for individual classification. Our methods demonstrate promising performance, with high accuracy compared to existing techniques. They are cost-effective, reliable, and easy to use, making them suitable for large-scale population screening and long-term patient monitoring. We conclude that early screening for arterial stiffness can help prevent atherosclerosis, and simple devices can effectively facilitate this process.