biosignal-processing

Elata SDK is the cross-platform biosignal toolkit for building neurotechnology and remote biosensing apps on web and native.

Real-time emotion recognition with 40-channel EEG, facial analysis & PPG fusion - PyQt6 interface with DEAP dataset, KNN/SVM classifiers

A flow matching framework for EMG generation

This repository offers a pipeline for classifying insomnia using EEG, EMG, EOG, and ECG signals, featuring early and late fusion, signal preprocessing, feature extraction, and machine learning models for accurate detection.

This project demonstrates how electromyographic (EMG) signals can be used to control a prosthetic hand. The software acquires raw EMG data from surface electrodes, processes it in real time using digital filters, and translates the extracted muscle activity into control commands for servo motors.

Production-grade ensemble framework combining XGBoost, PyTorch & Sklearn - 70%+ test coverage with Optuna optimization for time-series prediction

Implementation of the core Adaptive Chirplet Transform (ACT) algorithm using THRML (Thermodynamic sampling) to efficiently find the best matching atom in the continuous space

First‑year BTech Electrical Engineering project (2020–21): NI Multisim simulation of a wearable stress‑meter with sensor‑fusion analytics.

EEG/EMG biosignal classification pipeline for prosthetic arm intent recognition, combining Classic ML, CNN, and RNN/BRNN models with shared preprocessing and demo tools.

Review of 11 biometric sensors and 2 facial-analysis tools for anxiety detection, plus a sample dataset

Deterministic ECG codec — Python + Rust, CI parity-gated. Bounded clinical-mode contract: PRD ≤ 2.32% on MIT-BIH (48/48, mean PRD 1.12%); PTB-XL boundary disclosed (max PRD 5.29%). Cardiologist-equivalence and regulatory closure out of scope.

ECG preprocessing, R-peak detection and QRS analysis using MATLAB.

Real-time, privacy-first multimodal stress & drowsiness detection from a webcam: MediaPipe facial-AU + rPPG fusion, an 11-D RF+ExtraTrees ensemble (98.5% acc / 99.95% ROC-AUC, 5-fold CV), with a full ablation study and significance testing.

ECG signal processing pipeline for Atrial Fibrillation detection and Heart Rate Variability (HRV) analysis using the MIT-BIH Atrial Fibrillation Database.

Physiological stress detection using ECG, EDA, and respiration features from WESAD, evaluated with LOSO cross-validation.

R functions for processing pupillary light reflex (PLR) recordings — artifact removal, feature extraction, and batch analysis

Open-source desktop app for real-time BITalino biosignal acquisition over BLE. Currently supports EDA on A3 with Raw EDA, SCL, and SCR visualization and CSV recording, providing a foundation for feature extraction and future stress-classification workflows.

EMG signal classification for hand gesture recognition using machine learning for prosthetic control applications.

HeartVision is a real time Remote Photoplethysmography (rPPG) system for contactless heart rate estimation using the Plane-Orthogonal-to-Skin (POS) algorithm. Features OpenFace/Haar Cascade face detection, spectral SNR-based signal quality assessment, quasi-periodicity detection, and automatic HTML report generation with rPPg signal visuals.

Machine learning pipeline for detecting cognitive fatigue from EEG biosignals with 85%+ F1-score using ensemble methods