Individualized apnea prediction in preterm infants using cardio-respiratory and movement signals

2013 IEEE International Conference on Body Sensor Networks, BSN 2013

Volumn , Issue , 2013, Pages

  Williamson, James R ^a   Bliss, Daniel W ^b   Browne, David W ^a   Indic, Premananda ^c   Bloch Salisbury, Elisabeth ^c   Paydarfar, David ^c,d  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b Arizona State University   (United States)

^c UNIVERSITY OF MASSACHUSETTS MEDICAL SCHOOL   (United States)

^d HARVARD UNIVERSITY   (United States)

Author keywords

algorithm; bradycardia; feature vector; hypoxia; machine learning; monitoring; prematurity

Indexed keywords

BRADYCARDIA; DEVELOPMENTAL DISORDERS; FEATURE VECTORS; HYPOXIA; PHYSIOLOGICAL SENSORS; PREMATURITY; STATISTICAL SIGNIFICANCE; STOCHASTIC RESONANCES;

BODY SENSOR NETWORKS; FORECASTING; LEARNING SYSTEMS; MAGNETIC RESONANCE; MONITORING;

ALGORITHMS;

EID: 84884630614     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BSN.2013.6575523     Document Type: Conference Paper

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