Abstract ▼ AI-Helper

Recently, as wearable devices and ubiquitous healthcare have been developed, researches on methods of detecting biometric information without constraint, non-invasive and insensible have been continuously carried out. Breathing is one of the vital sings, it is important information for human life. T...

Recently, as wearable devices and ubiquitous healthcare have been developed, researches on methods of detecting biometric information without constraint, non-invasive and insensible have been continuously carried out. Breathing is one of the vital sings, it is important information for human life. To measure the respiration signal for human body, many studies have been performed by using photo-plethysmography (PPG) that can be embedded in a wearable devices are being actively researched. Recently researches for measuring exact respiration from PPG signal in various ways, but there have been few studies to detect respiratory rate using PPG signals measured during the exercise situation in real time. Because respiration rate is different during exercises and usual, it will be useful if we can measure respiration signal from PPG at anytime from human body.
In this paper, a real time respiration signal detection algorithm is proposed to extract respiratory information selectively from PPG data. The algorithm can effectively measure the respiration signal by controlling the number of FFT-channels according to the change of heart rate during normal situation and exercise situation.

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