ASSIST-IoT Multimodal Fall Detection Dataset
Description
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.
Resources
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http://data.europa.eu/88u/dataset/oai-zenodo-org-8340379 |
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http://data.europa.eu/88u/dataset/oai-zenodo-org-8340379 |
Tags
- uwb-localization
- assist-iot
- iot
- fall-detection
- accelerometer
- multimodal