A Home-Tasks Activities Dataset with Wrist-accelerometer and Audio Features.

The dataset contains wrist-accelerometer and audio data from people performing at-home tasks such as sweeping, brushing teeth, washing hands, or watching TV. These activities represent a subset of activities that are needed to be able to live independently. Being able to detect activities with wearable devices in real-time has the potential for the realization of assistive technologies with applications in different domains such as elderly care and mental health monitoring. Preliminary results show that using machine learning with the dataset leads to promising results, but also that there is still improvement potential. By making this dataset public, researchers can test different machine learning algorithms for activity recognition, especially, sensor data fusion methods.


File Description Size Download The archive containing the dataset. 1.75MB

All files can be viewed and downloaded in our OSF repository available here:


    title = {HTAD: A Home-Tasks Activities Dataset with
        Wrist-Accelerometer and Audio Features},
    author = {
        Garcia-Ceja, Enrique and Thambawita, Vajira and Hicks, Steven A. and
        Jha, Debesh and Jakobsen, Petter and Hammer, Hugo L. and
        Halvorsen, P{\aa}l and Riegler, Michael A.
    booktitle = {MultiMedia Modeling},
    year = {2021},
    publisher = {Springer International Publishing},
    address = {Cham},
    pages = {196--205},

Terms of use

The data is released fully open for research and educational purposes. The use of the dataset for purposes such as competitions and commercial purposes needs prior written permission. In all documents and papers that use or refer to the dataset or report experimental results based on the HTAD, a reference to the related article needs to be added:


Email michael (at) simula (dot) no if you have any questions about the dataset and our research activities. We always welcome collaboration and joint research!