A real-time physiological signal acquisition and analyzing method based on fractional calculus and stream computing

The physiological signal acquisition and analyzing are important for intelligent health services, human-computer interaction and other applications. Due to the computing power limitation of terminal devices, many analyzing methods of physiological signals are in offline mode. However, in many applications, physiological signal should be analyzed in real time. To overcome this problem, a real-time physiological signal acquisition and analysis method based on fractional calculus and stream computing is proposed. Mobile terminals read the physiological data from sensors and upload them to the stream computing platform. A fractal index is used to estimate the physiological status. Based on the stream computing platform, this index is calculated by distributed parallel computing. The experiment results show this method can distinguish the heart health status and reflect driver mental status to some extent.

Automated summary

The proposed method is a real-time physiological signal acquisition and analysis method based on fractional calculus and stream computing. It estimates physiological status using a fractal index, calculated by distributed parallel computing on a stream computing platform. Experimental results show its ability to distinguish heart health status and reflect driver mental status.