ASSIST-IoT Multimodal Fall Detection Dataset

Multimodal dataset for fall detection. Includes acceleration data collected from a tag and two smartwatches, and location reported by the tag. More details about the data collection procedure can be found in notes.md.

Contents

The repository contains:

data/location_data.csv and data/full_acceleration – preprocessed acceleration and location data from 10 participants and mannequin simulated falls with target variable identified

data/subsampled_acceleration_data.csv – subsampled acceleration dataset used for training the AI model

notes.md – description of activities performed and notes from data collection

videos – reference videos for performed activities

Authors

Piotr Sowiński – research methodology, data collection and processing

Monika Kobus – research methodology, data collection

Anna Dąbrowska – research methodology, methodological supervision

Kajetan Rachwał – data collection

Karolina Bogacka – research methodology

Krzysztof Baszczyński – research methodology, data collection

Anastasiya Danilenka – research methodology, data collection and processing

Acknowledgements

This work is part of the ASSIST-IoT project that has received funding from the EU’s Horizon 2020 research and innovation programme under grant agreement No 957258.

The Central Institute for Labour Protection – National Research Institute provided facilities and equipment for data collection.

License

The dataset is licensed under the Creative Commons Attribution 4.0 International License.