READ ME File For 'Dataset supporting the University of Southampton MPhil Thesis "Efficient Teacher-Student Architectures for Human Activity Recognition via Soft  Labels and Binarization"'

Dataset DOI: 10.5258/SOTON/D3007

ReadMe Author: YIPENG SHEN, University of Southampton ORCID: orcid.org/0009-0007-4363-9460

This dataset supports the thesis entitled Efficient Teacher-Student Architectures for Human Activity Recognition via Soft  Labels and Binarization"
AWARDED BY: Univeristy of Southampton
DATE OF AWARD: [2024]


DESCRIPTION OF THE DATA


Three public datasets for Human Activity Recognition (HAR), with the original data directly downloadable from the Internet. The descriptions below include corresponding links and some brief explanations.

The datasets have been preprocessed with Python, including sliding window cropping, removal of NaN rows, removal of time(ms), normalization, etc. They have been divided into Test, Train, and Validation datasets using mainstream methods and finally saved with Numpy for the convenience of users for quick deployment.

Daphnet Gait Dataset(Frozen of Gait):
https://archive.ics.uci.edu/dataset/245/daphnet+freezing+of+gait

This dataset is a binary classification dataset consisting of recordings from 10 participants diagnosed with Parkinson’s disease (PD). Dataset activities correspond to recognizing whether or not gait freeze occurs based on wearable acceleration sensors. The dataset was recorded in a lab environment with the subjects were instructed to carry out activities with a high likelihood of inducing freezing of gait, which is a common motor complication in PD.

Opportunity Dataset:
https://archive.ics.uci.edu/dataset/226/opportunity+activity+recognition

This dataset  contains recordings from various wearables and environment sensors from four participants who carry out common kitchen activities, such as Open/Close Door, Dishwasher, and Fridge, via Inertial Measurement Units (IMUs) at 30Hz. Each participant is recorded in five different runs. 

PAMAP2 Dataset:
https://archive.ics.uci.edu/dataset/231/pamap2+physical+activity+monitoring
The physical activity monitoring dataset is similar to the opportunity dataset, consisting of nine participants performing 12 kinds of daily physical activities, such as cycling, walking, sitting. The sensors used in the inertial measurement units (IMUs) include accelerometers, gyroscopes, magnetometers, temperature, and heart rate.

This dataset contains:
preprocessed datasets: Daphnet Gait, Opportunity and PAMAP2.


Date of data collection: 01/09/2019-28/12/2023


Licence:
CC BY



Date that the file was created: March, 2024