Factorial switching linear dynamical systems applied to physiological condition monitoring

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 31, Issue 9, 2009, Pages 1537-1551

  Quinn, John A ^a   Williams, Christopher K I ^b   McIntosh, Neil ^c  

^a MAKERERE UNIVERSITY   (Uganda)

^b UNIVERSITY OF EDINBURGH   (United Kingdom)

^c UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Condition monitoring; Intensive care; Novelty detection; Switching Kalman filter; Switching linear dynamical system

Indexed keywords

COMMON FACTORS; DIFFERENT MODES; DOMAIN KNOWLEDGE; EXPLICIT KNOWLEDGE; INTENSIVE CARE; INTENSIVE CARE UNIT MONITORING; NOVEL PATTERNS; NOVELTY DETECTION; PHYSIOLOGICAL CONDITION; PHYSIOLOGICAL MEASUREMENT; PREMATURE BABY; STATE OF HEALTH; SWITCHING LINEAR DYNAMICAL SYSTEM; SWITCHING LINEAR DYNAMICAL SYSTEMS; TIME STEP; UNDERLYING FACTORS;

CONTROL THEORY; DYNAMICAL SYSTEMS; INTENSIVE CARE UNITS; KALMAN FILTERS; LINEAR CONTROL SYSTEMS; SWITCHING;

CONDITION MONITORING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; DECISION SUPPORT SYSTEM; FACTORIAL ANALYSIS; HUMAN; METHODOLOGY; MONITORING; NEWBORN; NEWBORN INTENSIVE CARE; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DECISION SUPPORT SYSTEMS, CLINICAL; DIAGNOSIS, COMPUTER-ASSISTED; FACTOR ANALYSIS, STATISTICAL; HUMANS; INFANT, NEWBORN; INTENSIVE CARE, NEONATAL; LINEAR MODELS; MONITORING, PHYSIOLOGIC; PATTERN RECOGNITION, AUTOMATED;

EID: 67650995767     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2008.191     Document Type: Article

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