mmalekzadeh/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)
This dataset provides time-series data from smartphone accelerometers and gyroscopes, collected from 24 participants performing six common activities like walking and jogging. It includes raw sensor readings and associated demographic data (age, gender, height, weight). Researchers and data scientists can use this to develop and test models for human activity recognition or to infer personal attributes from motion patterns.
363 stars. No commits in the last 6 months.
Use this if you need a pre-collected, labeled dataset of smartphone sensor data for research into human activity recognition or attribute inference.
Not ideal if you require real-time data collection or a dataset with different sensor types, activities, or demographic diversity than what is provided.
Stars
363
Forks
108
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 19, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mmalekzadeh/motion-sense"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
OxWearables/stepcount
Improved Step Counting via Foundation Models for Wrist-Worn Accelerometers
OxWearables/actinet
An activity classification model based on self-supervised learning for wrist-worn accelerometer data.
aqibsaeed/Human-Activity-Recognition-using-CNN
Convolutional Neural Network for Human Activity Recognition in Tensorflow
felixchenfy/Realtime-Action-Recognition
Apply ML to the skeletons from OpenPose; 9 actions; multiple people. (WARNING: I'm sorry that...
guillaume-chevalier/LSTM-Human-Activity-Recognition
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM...