FAST: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation

Proceedings of the 2015 IEEE International Conference on Networking, Architecture and Storage, NAS 2015

Volumn , Issue , 2015, Pages 2-11

  Cao, Yu ^a   Chen, Songqing ^b   Hou, Peng ^a   Brown, Donald ^a  

^a University of Massachusetts Lowell   (United States)

^b George Mason University   (United States)

Author keywords

Accelerometers; Brain models; Detection algorithms; Monitoring; Sensors; Smart phones

Indexed keywords

ACCELEROMETERS; BRAIN MODELS; DECISION MAKING; DESIGN; DIGITAL STORAGE; ENERGY UTILIZATION; FIRE FIGHTING EQUIPMENT; FOG; HEALTH; MONITORING; NETWORK ARCHITECTURE; SENSORS; SIGNAL DETECTION; SMARTPHONES; TIME SERIES ANALYSIS;

ACCELERATION MAGNITUDE; COMPUTING PARADIGM; DETECTION ALGORITHM; EDGE INTELLIGENCE; FILTERING TECHNIQUE; NONLINEAR TIME-SERIES ANALYSIS; PERVASIVE HEALTH MONITORING SYSTEMS; PERVASIVE HEALTHS;

DISTRIBUTED COMPUTER SYSTEMS;

EID: 84960857858     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NAS.2015.7255196     Document Type: Conference Paper

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