The Cardiac Disease Predictor: IoT and ML Driven Healthcare System

Shaira Tabassum, Md. Ittahad Uz Zaman, Md. Sabbir Ullah, Ashikur Rahaman, Samsun Nahar, A.K.M. Muzahidul Islam

2019 4th International Conference on Electrical Information and Communication Technology (EICT) · 2019 · 20 citations · 13 references

Concepts

Abstract

Nowadays people suffering from diseases have dramatically shifted from communicable to non-communicable which is also quite significant in Bangladesh. Deaths due to such diseases are having a major impact on the lives of people. Among all non-communicable diseases, cardiovascular disease is highly prevalent in our country. Many people cant afford the cost of going through regular check-up. Our paper proposes a prototype which demonstrates a mechanism of identifying patients having cardiac disease. Our prototype consists of different sensor-modules to collect data e.g., Heart BPM, Cholesterol, ECG, etc. and uses a Machine Learning model to perform the classification based on the collected data. The prediction is visible to the patient instantly so that the patient can take necessary precautions beforehand. Till to date, we have managed to collect data from Heart Rate sensor, ECG sensor, Cholesterol sensor module, Blood Pressure module and currently we are working on the Glucose sensor module.

References

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