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Title:
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BLOOD PRESSURE PREDICTION SYSTEM BASED ARTIFICIAL INTELLIGENCE |
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Author(s):
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Yonghee Lee and Hakjin Kim |
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ISBN:
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978-989-8704-50-4 |
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Editors:
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Piet Kommers, Mário Macedo, Guo Chao Peng and Ajith Abraham |
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Year:
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2023 |
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Edition:
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Single |
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Keywords:
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Blood Pressure, Artificial Intelligence, Photoplethysmograph, Prediction System, Continuous Monitoring |
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Type:
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Poster |
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First Page:
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391 |
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Last Page:
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392 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper is to implement the algorithm that estimates systolic and diastolic blood pressure through artificial intelligence learning by measuring optical blood flow signals. When the heart contracts, the blood that flows in through the pulmonary artery is supplied through the aorta to the peripheral blood vessels of organs and tissues that make up our body. Photo plethysmograph is obtained by measuring the amount of light absorbed according to the amount of blood supplied from the heart to ventricular contraction. It is a waveform that expresses the change in blood volume as a photoelectric signal and appears in proportion to the blood flow. PPG shows a close relationship with the activity of the heart. In proportion to the amount of oxygen in the blood, a photoelectric signal of red light according to the change in blood flow is detected. Based on the relationship between cardiac activity and PPG, blood pressure information can be obtained. The entire system consists of a PPG measurement module, signal processing, and artificial intelligence algorithm. |
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