ADHDWare: A Software to Detect Attention Deficit Hyperactivity Disorder (ADHD) Using ECG

A novel approach to detect ADHD using Electrocardiogram (ECG) signals. The system integrates a Bio-Amp EXG Pill sensor, an Arduino microprocessor, and a user-friendly graphical user interface (GUI) to facilitate the recording, processing, and analysis of ECG data. The Bio-Amp EXG Pill sensor captures high-quality biopotential signals from the heart, which are recorded and stored as WAV (Waveform Audio Format) files using the Arduino microprocessor. These files are uploaded via the GUI, converted into matrix format, and preprocessed to remove noise and extract relevant features. The preprocessed data is then segmented and analyzed to identify patterns indicative of ADHD. A pre-trained machine learning (ML) algorithm classifies the data, and the results, including visualizations and critical segments, are displayed on the GUI. The system's structured workflow ensures accurate and efficient ADHD detection, with results stored in a MySQL database for further analysis. Performance metrics of K-Nearest Neighbour (KNN), Logistic Regression, and Support Vector Machine (SVM) classifiers are provided, demonstrating the system's effectiveness.