An adaptive Kalman filter technique for context-aware heart rate monitoring.
Traditional physiological monitoring systems convert a person's vital sign waveforms, such as heart rate, respiration rate and blood pressure, into meaningful information by comparing the instant reading with a preset threshold or a baseline without considering the contextual information of the person. It would be beneficial to incorporate the contextual data such as activity status of the person to the physiological data in order to obtain a more accurate representation of a person's physiological status. In this paper, we proposed an algorithm based on adaptive Kalman filter that describes the heart rate response with respect to different activity levels. It is towards our final goal of intelligent detection of any abnormality in the person's vital signs. Experimental results are provided to demonstrate the feasibility of the algorithm.
2-212 Center for Science and Technology, Syracuse, NY 13244, USA. mxu@blue-highway.com
Min
M
Xu
Albert
A
Goldfain
Jim
J
Dellostritto
Satish
S
Iyengar
D000465:Algorithms; D001794:Blood Pressure; D004562:Electrocardiography / Q000379:methods*; D001330:Electronic Data Processing; D006331:Heart Diseases / Q000503:physiopathology; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D015233:Models, Statistical; D008991:Monitoring, Physiologic / Q000379:methods*; D016011:Normal Distribution; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012119:Respiration; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors