An adaptive Cusum test based on a hidden semi-Markov model for change detection in non-invasive mean blood pressure trend.
A hidden semi-Markov model is proposed to describe a trend signal for non-invasive mean blood pressure. Based on the model, a Viterbi beam search algorithm working with an adaptive cumulative sum test is proposed to detect change points and recognize change patterns online. Testing results on the simulated signals and clinical signals demonstrate that the algorithm has improved performance over the standard cumulative sum test for change detection, and has the potential to provide a clinically relevant description of trend changes.
Yang
Ping
P
Dept. of Electr. & Comput. Eng., British Columbia Univ., Vancouver, BC, Canada.
Dumont
Guy
G
Ansermino
J Mark
JM
D000465:Algorithms; D001698:Biomedical Engineering; D001795:Blood Pressure Determination / Q000706:statistics & numerical data*; D006801:Humans; D008390:Markov Chains; D016343:Monitoring, Intraoperative / Q000706:statistics & numerical data; D008991:Monitoring, Physiologic / Q000706:statistics & numerical data*; D012815:Signal Processing, Computer-Assisted