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- W2899449505 abstract "The increase in quality for wearable technologies has opened the door for an Internet of things (IoT) resolution to attention. One among the foremost current attention issues nowadays is that the poor survival rate of out-of-hospital abrupt internal organ arrests. The target of this study is to gift a multisensory system mistreatment IoT which will collect physical activity heart rates and vital sign. For this study, we have a tendency to enforce an embedded sensory system with an occasional Energy Bluetooth communication module to gather ECG and vital sign knowledge employing a smartphone in a very common setting. This study introduces the employment of signal process and machine learning techniques for detector knowledge analytics for abrupt a seize systole and or heart failure prediction. Big data analytics, legendary in the organization for its use in controlling and managing huge data sets, is applied with success to forecast, avoidance, management, and cure for disorder. Big data analytical visualization tools are useful for health care and forecasting heart attacks." @default.
- W2899449505 created "2018-11-09" @default.
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- W2899449505 date "2018-11-05" @default.
- W2899449505 modified "2023-09-23" @default.
- W2899449505 title "Smart Heartbeat Monitoring System Using Machine Learning" @default.
- W2899449505 cites W1482688465 @default.
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- W2899449505 doi "https://doi.org/10.1007/978-981-13-1580-0_35" @default.
- W2899449505 hasPublicationYear "2018" @default.
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