Notes on Scientific Computing for Biomechanics and Motor Control
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Updated
Mar 28, 2024 - Jupyter Notebook
Notes on Scientific Computing for Biomechanics and Motor Control
A Numerical Magnetic Resonance Imaging (MRI) Simulation Platform
Codes for paper: Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach
This project is for Electrocardiogram(ECG) signal algorithms design and validation, include preprocessing, QRS-Complex detection, embedded system validation, ECG segmentation, label your machine learning dataset, and clinical trial...etc.
Atrial Fibrillation Detection Blood Pressure Monitor (Oscillometric Method)
Website for Biomedical and Data (Bio-Dat) lab at Mahidol University, Thailand
BRAPH 2.0 is a comprehensive software package for the analysis and visualization of brain connectivity data, offering flexible customization, rich visualization capabilities, and a platform for collaboration in neuroscience research.
This project is MAX3010x library for STM32F4
Tutorial and framework code for deep learning in biomedical applications with PyTorch and (if necessary) Google Cloud Platform.
Implementation of surface EMG decomposition as proposed on Francesco Negro et al 2016 J. Neural Eng. 13 026027.
USB-DUX boards are open source/hardware data acquisition devices for Linux with full Linux kernel & debian/Ubuntu support.
Portable WiFi Connected IoT ECG Monitor 📈💕
Repositorio del grupo 3 del curso de Introducción a Señales Biomédicas.
This project was completed in 2018 as a part of my postgraduate studies in Biomedical Engineering
Respiration-rate-and-heart-rate-detection is a project developed for the Biomedical Signal Processing exam at the University of Milan (academic year 2020-2021). It implements an algorithm to analyze accelerometric signals collected with a smartphone positioned on the thorax while supine.
Tanks used in EIT experiments. Adult and Neonate Head Tanks
Processing and directory structure for Stroke EIT Dataset
Source code for multiple parameter modelling of synthetic electromyography data.
Studying facial muscle activation and their relationship with facial kinematics via facial landmarks. Utilizes an Arduino to generate a square wave with a specific duty cycle and frequency and synchronously trigger EMG and image acquisition.
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