An SVM classifier for fatigue-detection using skin conductance for use in the BITS-lifeguard wearable computing system

2009 2nd International Conference on Emerging Trends in Engineering and Technology, ICETET 2009

Volumn , Issue , 2009, Pages 934-939

  Bundele, Mahesh M ^a   Banerjee, Rahul ^b  

^a SGBAU University   (India)

^b BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCE   (India)

Author keywords

Fatigue detection; Multilayer perceptron neural networks; Skin conductance; Support vector machine; Wearable computing

Indexed keywords

ARTIFICIAL NEURAL NETWORK APPROACH; BODY PARAMETERS; CLASSIFICATION ACCURACY; DRIVER FATIGUE; FATIGUE DETECTION; FATIGUE LEVEL; INPUT FEATURES; MULTI-LAYER PERCEPTRON NEURAL NETWORKS; OXIMETRY; PERFORMANCE MEASURE; PHYSIOLOGICAL PARAMETERS; RECEIVER OPERATING CHARACTERISTICS; SKIN CONDUCTANCE; SVM CLASSIFIERS; TWO-STATE; VEHICULAR ACCIDENTS; WEARABLE COMPUTING;

BEHAVIORAL RESEARCH; CLASSIFIERS; ELECTRIC LOADS; MEAN SQUARE ERROR; MULTILAYERS; NONINVASIVE MEDICAL PROCEDURES; PHYSIOLOGICAL MODELS; SUPPORT VECTOR MACHINES; WEARABLE COMPUTERS;

MULTILAYER NEURAL NETWORKS;

EID: 77949580622     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICETET.2009.29     Document Type: Conference Paper

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