Abstract
Background: An electrocardiogram device monitors the cardiac status of a patient by
recording the heart’s electrical potential vs time. Such devices play a very important role to save
the life of patients who survive a heart attack or suffer from these patients. An early detection of
conditions that lead to the onset of cardiac arrest allows doctors to provide proper treatment on
time and prevents death or disability from cardiac arrest. Most developing countries have very
poor information about these health care issues.
Methods: An actual deployment of the system was used to evaluate key aspects of the system
architecture, in particular, the possibility to monitor the ECG signal of single patients in a large
area and for a long time the possibility to access ECG data through the web interface. The test
deployment consisted of ECG sensor AD8232, wi-fi module and IoT server. The IoT server was
installed on a Linux/ windows machine. The wifi has been configured to connect to the server,
through an ADSL router.
Conclusion: We have proposed a wireless wearable ECG monitoring system enabled with an IoT
platform that integrates heterogeneous nodes of ECG sensor and applications, has a long battery
life and provides a high-quality ECG signal. The system allows monitoring single/multiple
patients on a relatively large indoor area (home, building, nursing home, etc). As observed, this
result is obtained through a careful set of choices at the level of components, circuit solutions, and
algorithms. We would like to stress the fact that a dedicated overall output is not enough to
achieve an advantage in terms of overall sensor performance. The latter depends on the
optimization of the whole sensor. Indeed, this proposed ECG sensor, based on a high-performance
ADC and an arm processor, provides much better performance, in terms of power consumption
and noise, than many proposed system based on a purposely designed front-end chip.
Keywords:
Wearable sensors, monitoring, electrocardiogram, wireless sensor networks, bio-signal, photoplethysmography
(PPG).
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