IoT based hypoglycemic early detection via ECG signals

Jefri, Muhammad Saiful (2021) IoT based hypoglycemic early detection via ECG signals. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Hypoglycemia is a common and dangerous side effect of insulin therapy in patients with diabetes. Hypoglycemia should be diagnosed and predicted early, which can help with treatment and prevention. Besides that, the discomfort of finger pricking will deter patients from routinely checking their blood glucose levels. This project aims to design an electrocardiogram (ECG) circuit for early detection of hypoglycemia using ECG signals. Specifically, it analyzes the ECG signal's activity when hypoglycemia exists. To determine the hypoglycemia behavior, a circuit is designed that consists of instrumentation amplifier, driven right leg, low pass filter and DC offset cancelation. Then, an Internet of Things (IoT) platform was built to display the ECG signals. Besides that, the ECG was analyzed from the data of 3 people. The results showed the hypoglycemia occurs when the ECG graph showed higher R-wave amplitude than normal. These results determine that hypoglycemia can be predicted early by ECG signals. An accident also can be prevented early by getting the notification. So, the family or doctor can take appropriate action to prevent accidents from happening.

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