title: Prediction model of sinoatrial node field potential using high order partial least squares.
abstract: High order partial least squares (HOPLS) is a novel data processing method. It is highly suitable for building prediction model which has tensor input and output. The objective of this study is to build a prediction model of the relationship between sinoatrial node field potential and high glucose using HOPLS. The three sub-signals of the sinoatrial node field potential made up the model's input. The concentration and the actuation duration of high glucose made up the model's output. The results showed that on the premise of predicting two dimensional variables, HOPLS had the same predictive ability and a lower dispersion degree compared with partial least squares (PLS).
authors.affiliation: State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Feng
authors.affiliation: State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Cao
authors.affiliation: State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
authors.forename: Yanbin
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D005947:Glucose / Q000378:metabolism*; D016018:Least-Squares Analysis; D051379:Mice; D008955:Models, Cardiovascular; D015233:Models, Statistical; D012849:Sinoatrial Node / Q000502:physiology*
chemical_list: D005947:Glucose
keywords: High order partial least squares; prediction model; signal decomposition; sinoatrial node field potential