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.

The dataset is archived in Zenodo.

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

• Anastasiya Danilenka – research methodology, data collection and processing
• 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

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.