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Activities of Daily Living (ADLs) Recognition Using Binary Sensors Data Set
Download: Data Folder, Data Set Description

Abstract: This dataset comprises information regarding the ADLs performed by two users on a daily basis in their own homes.

Data Set Characteristics:  

Multivariate, Sequential, Time-Series

Number of Instances:

2747

Area:

Computer

Attribute Characteristics:

N/A

Number of Attributes:

N/A

Date Donated

2013-10-28

Associated Tasks:

Classification, Clustering

Missing Values?

N/A

Number of Web Hits:

98485


Source:

Francisco Javier Ordóñez, Carlos III University of Madrid, fordonez '@' inf.uc3m.es


Data Set Information:

This dataset comprises information regarding the ADLs performed by two users on a daily basis in their
own homes. This dataset is composed by two instances of data, each one corresponding to a different
user and summing up to 35 days of fully labelled data. Each instance of the dataset is described by
three text files, namely: description, sensors events (features), activities of the daily living (labels).
Sensor events were recorded using a wireless sensor network and data were labelled manually.


Attribute Information:

The features are the sensor events captured for the corresponding Wireless Sensor Network.


Relevant Papers:

N/A



Citation Request:

Ordóñez, F.J.; de Toledo, P.; Sanchis, A. Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors. Sensors 2013, 13, 5460-5477.


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 In Collaboration With:

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