valenio

actinet

An activity classification model based on self-supervised learning for wrist-worn accelerometer data.

rppg

Benchmark Framework for fair evaluation of rPPG

pd_walking

Detect walking in the PD population

orientation_tracking-unscented_kalman_filter

Implemented Unscented Kalman Filter (UKF) for orientation tracking. Sensors fusion of accelerometer, and gyroscope

Unscented-Kalman-Filter

A Python implementation of an Unscented Kalman Filter for estimating the orientation of a quadcopter given gyroscope and accelerometer data.

Made-With-ML

Learn how to design, develop, deploy and iterate on production-grade ML applications.

beiwe-android

Beiwe is a smartphone-based digital phenotyping research platform. This is the Beiwe Android app code. The Beiwe2 app is also available on the Google Play store to use with open source builds of the Beiwe backend.

GaitPy

elevateMS_data_release

gait-cycle-transfer

neural style tranfer from one walking/gait cycle to another; ArXiv:1606.03238 & ArXiv:1508.06576

MS-GAIT_feature_extraction

Software detailing the extraction of smartphone and smartwatch-based ambulatory features to accompany the publication: Creagh et al. (2020), "Smartphone- and Smartwatch-Based Remote Characterisation of Ambulation in Multiple Sclerosis During the Two-Minute Walk Test", IEEE J-BHI, 10.1109/JBHI.2020.2998187 https://ieeexplore.ieee.org/abstract/document/9103259 The codebase demonstrates how to perform modular, scalable and parallelizable gait feature extraction from triaxial inertial sensor data.

find_walking

A “one-size-fits-most” walking recognition method for smartphones, smartwatches, and wearable accelerometers

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

life2vec

ExtraSensory

openmovement

Open Movement devices are miniature, embeddable, open source sensors developed at Newcastle University, UK. The source code for the firmware and software is available under a BSD 2-clause license, and the hardware (PCB designs, layouts and schematics), enclosure designs and documentation are available under a Creative Commons 3.0 BY Attribution License.

ssl-wearables

Self-supervised learning for wearables using the UK-Biobank (>700,000 person-days)

HAR-stacked-residual-bidir-LSTMs

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

motion-sense

MotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and gyroscope) (PMC Journal) (IoTDI'19)

LSTM-Human-Activity-Recognition

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

Oxford_Wearables_Activity_Recognition

Notebooks for Oxford CDT Wearables Data Challenge

pytorch-deep-learning

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

biobankAccelerometerAnalysis

Extracting meaningful health information from large accelerometer datasets

tutorials

MONAI Tutorials

MONAI

AI Toolkit for Healthcare Imaging

MA-rPPG-Video-Toolbox

The source code and pre-trained models for Motion Matters: Neural Motion Transfer for Better Camera Physiological Sensing (WACV 2024, Oral).

MMPD_rPPG_dataset

MMPD: Multi-Domain Mobile Video Physiology Dataset(EMBC2023 Oral)

kymatio

Wavelet scattering transforms in Python with GPU acceleration

review_object_detection_metrics

Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.

resnet3D_pulse

pulse measurement from face videos using ResNet3D