Abstract(s) :
(Anglais) Internet of Things is a new emerging technology by
which devices can communicate using the internet. The proposed
work, An Efficient Vital Signs Monitoring System for Elderly,
states that how to apply Internet of Things in Healthcare using
Machine Learning Techniques. Indeed, connecting the Internet of
Medical Things (IoMT) to the patient/elderly will be helping
Doctors and Caregivers to monitor him or her in real-time around
the globe. The IoMT devices will collect Vital Signs data such as
body temperature, pulse rate, heartbeats (signals), using ECG
(Electrocardiogram) sensor, Temperature sensor, etc. That will be
stored in the Cloud System and it will synchronize with the local
server. Machine Learning comes to analyze those data to identify
health risks and estimate severity in real-time by using its
Algorithms. The Proposed System, based on Deep Neural
Networks (DNN) and IoMT can differentiate between Normal and
Abnormal Heartbeats and classify different Abnormal Rhythms.
Such techniques will be very useful for physicians to detect
possible health problems and deliver appropriate medical
assistance on time to serve elderly in a better way.
Keywords
—Abnormal Rhythms, ECG, Raspberry Pi 3, IoMT,
Heartbeats, Electrocardiogram, Deep Neural Networks, Machine
Learning, TensorFlow GPU.