biosignal-processing

Time Series Feature Extraction Library (TSFEL): 60+ statistical, temporal, spectral and fractal features for time series classification, regression and signal processing in Python

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

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

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.

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

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.

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

Fail-closed health intelligence for wearable time series — PPG denoising, grounded synthesis, safety gates, and auditable evaluation.

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.

Cross-platform biosignal control interface that turns trained body signals into computer actions through a visual node graph.

Laptop-first responsive web AAC prototype using edge EOG/EMG gesture detection with Arduino UNO R4 WiFi, BioAmp EXG Pill, BLE telemetry, and neural speech.

Exploratory multimodal ML research with SciPy statistics and scikit-learn PCA/K-means on eye, cardiac and questionnaire data.

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.

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