Dr. P. Vijayalakshmi of Professor & Head, Dept. of ECE, SSN College of Engineering

Biography:

Address:Chennai, India

Azfar Adib of Ph.D. Candidate, Dept. of EE, Concordia University

In their ongoing research, they are pioneering an age classification framework utilizing Electrocardiogram (ECG) data. Their investigation involves leveraging datasets sourced from the PTB-XL ECG database, meticulously curated to mirror the age distribution of the Canadian population. Their focus lies specifically on analyzing the QRS segment of the ECG waveform as a potential age predictor. This approach integrates certain techniques including band-pass filtering, discrete wavelet decomposition-reconstruction, and a deep neural network architecture featuring 1D CNN, LSTM, and regression layers. Initially, they pursued age prediction using this methodology, but encountered a notable clustering of predicted ages around a specific range corresponding to early adulthood. This observation prompted a shift towards age classification. In the realm of age classification, differentiating between adults and non-adults, their method demonstrates a high level of classification accuracies, reaching up to 99%. They are particularly invested in pinpointing the threshold where predicted ages exhibit this saturation phenomenon. Identifying this critical threshold holds significant promise for facilitating the practical implementation of ECG-based anonymous age verification systems.

Biography:

Address:Montreal, Canada