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 <code>notes.md</code>. <strong>Contents</strong> The repository contains: <code>data/location_data.csv</code> and <code>data/full_acceleration</code> – preprocessed acceleration and location data from 10 participants and mannequin simulated falls with target variable identified <code>data/subsampled_acceleration_data.csv</code> – subsampled acceleration dataset used for training the AI model <code>notes.md</code> – description of activities performed and notes from data collection <code>videos</code> – reference videos for performed activities <strong>Authors</strong> 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 <strong>Acknowledgements</strong> 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. <strong>License</strong> The dataset is licensed under the Creative Commons Attribution 4.0 International License.