User Identification From Walking Activity

Donated on 3/1/2014

The dataset collects data from an Android smartphone positioned in the chest pocket from 22 participants walking in the wild over a predefined path.

Dataset Characteristics

Univariate, Sequential, Time-Series

Subject Area

Other

Associated Tasks

Classification, Clustering

Feature Type

Real

# Instances

-

# Features

-

Dataset Information

Additional Information

The dataset collects data from an Android smartphone positioned in the chest pocket. Accelerometer Data are collected from 22 participants walking in the wild over a predefined path. The dataset is intended for Activity Recognition research purposes. It provides challenges for identification and authentication of people using motion patterns. --- Sampling frequency of the accelerometer: DELAY_FASTEST with network connections disabled --- Number of Participants: 22 --- Data Format: CSV

Has Missing Values?

No

Variable Information

--- Data are separated by participant --- Each file contains the following information ---- time-step, x acceleration, y acceleration, z acceleration

Reviews

There are no reviews for this dataset yet.

Login to Write a Review
Download
0 citations
3551 views

Creators

Pierluigi Casale

License

By using the UCI Machine Learning Repository, you acknowledge and accept the cookies and privacy practices used by the UCI Machine Learning Repository.

Read Policy