57 datasets found

The dataset used in this paper for Nordic Walking activity recognition.

Panoramic human activity recognition.

Human Activity Recognition using Continuous Wavelet Transform and Convolutional Neural Networks

The dataset used for the initial movement detection of cyclists using Convolutional Neural Networks.

Human Activity Recognition (HAR) from wearable sensor data identifies movements or activities in unconstrained environments.

The dataset used for activity recognition using wearable sensors.

A dataset of videos of human activities captured by calibrated cameras.

The UCI HAR dataset contains data collected from multiple sensors during different activities such as sitting, walking, etc.

Sensor-based human activity recognition (HAR) aims to recognize human activities based on the availability of rich time-series data collected from multi-modal sensors such as...

Human Activity Recognition (HAR), Gas sensor array drift, Isolet, Internet advertisements, Spambase

HHAR: Heterogeneous Human Activity Recognition Dataset

The UniMiB SHAR dataset was created based on collected data from 30 participants using smartphone accelerometer.

The dataset is used for human activity recognition on mobile devices. It consists of accelerometer and gyroscope data from a Samsung Galaxy S3 smartphone.

The WISDM dataset was collected using Android based smartphones. The data captured with the embedded tri-axial accelerometer was recorded while the users performed 6 different...

Human Activity Recognition (HAR) has broad applications in various domains such as healthcare, athletic competitions, smart cities, and smart home. While researchers focus on...

The EmoPain dataset consists of sequential data from multiple modalities and in unconstrained settings where there are bound to be uncertainties (e.g. in form of sensor noise)...

A new public dataset for early recognition of human activities from first-person videos.

Human activity recognition has wide applications in medical research and human survey system. In this project, we design a robust activity recognition system based on a smartphone.

The HARUS dataset is a human activity recognition dataset, containing 10,299 signals w.r.t. 6 activities.

Human Activity Recognition Using Smartphones Dataset (UCI HAR) includes 3-axial linear acceleration, 3-axial angular velocity, and gyroscope sensor data.