Exhibition of Individual Achievements

As part of the DSPA-2024 conference, an exhibition of individual achievements of students, lecturers, scientists, developers and just interested persons is organized.

Everyone (after prior approval) will be provided with a place to demonstrate their achievements. This can be a course of laboratory work; a book; design and development skills; a master class on working with processors; a self-designed device; an idea and so on that are directly related to digital signal processing. The opportunity to demonstrate your achievements or ideas in front of colleagues and experts will allow you to get "feedback" from them, help in improvement and implementation.

To take part in the exhibition with your materials, please fill the following online form: https://forms.gle/uv76BG8zAQWZgGRC6

The Organizing Committee reviews the applications and approves or rejects them.

Participation is free of charge.

Hands-On Machine Learning in Biomedical Signal Processing: Insights from ECG and EEG Data
(The Tutorial. At the venue only)

This hands-on tutorial offers participants a practical exploration of machine learning (ML) applications in biomedical signal processing, specifically focusing on Electrocardiography (ECG) and Electroencephalography (EEG) data. Beginning with an introduction to the fundamental role of ECG and EEG in health diagnostics, the tutorial progresses to cover essential ML concepts, including supervised and unsupervised learning, with a focus on classification and regression algorithms relevant to physiological signal analysis. Real-world applications in ECG, such as arrhythmia detection, and EEG, including seizure prediction and Brain-Computer Interface (BCI) development, will be explored. The hands-on session allows participants to engage in exercises covering data preprocessing, feature extraction, and ML model implementation using popular libraries. The tutorial concludes with a discussion on the broader impact of ML in healthcare diagnostics, addressing ethical considerations and challenges associated with deploying ML models in a healthcare context.

To take part in the tutorial, please fill the following online form: https://forms.gle/KKESWFFRpfivYVu36

Attention! You should bring your laptop with you.

Participation is free of charge.