37 datasets found

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

Human Activity Recognition using Continuous Wavelet Transform and Convolutional Neural Networks

Passively recognising human activities through lifelogging.

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

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

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)...

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.

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

The MobiAct dataset contains data collected from 61 subjects performing 11 daily activities.

The HAR dataset is a collection of physiological signals from human subjects.

The dataset used in the paper is a spatio-temporal graph representing human activity detection and anticipation.

The dataset is used for human activity recognition using radar signal.

The dataset is used for human activity recognition using smartphone sensor data.

The UCI machine learning repository contains a dataset of human activity recognition from inertial sensors.

The dataset consists of six activities performed by 29 subjects. These activities include walking, upstairs, downstairs, jogging, upstairs, and standing.