EMEA 2021 https://www.tinyml.org/event/emea-2021
Manivannan S, Senior Software Developer, Zf Wabco
The existing IoT Medical device sends bulk ECG data to the mobile/server and analysis is done in high processor or mobile application .So all the ECG analyzing device has dependency on Internet or high processing computers. The proposed TinyML application using Edge Impulse software is to develop a mini-Diagnosis ECG analyzer device which can fit in a pocket and it can diagnose heart diseases independently without cloud connectivity. The proposed ECG Analyzer can detect atrial fibrillation, AV Block 1 and AV Block 2 with more than 90% accuracy.
This application will convert the human observations into datasets, that’s how the accuracy of TinyML model increased. The novelty of the device is decoding the raw ECG data into three different waveforms as Filtered ECG, R-R Interval, and P-R interval. This approach will clearly differentiate the different heart condition’s ECG.
As an application, the research work will be demonstrated using Arduino Nano Ble 33 and ECG sensor AD8232.The proposed research work will be using 3-lead ECG system and the generated TinyML model will have a size 15kB ROM.