Skip to content

teco-kit/whar-datasets

Repository files navigation

WHAR Datasets

This library provides support for popular WHAR (Wearable Human Activity Recognition) datasets including

  • downloading from original source
  • parsing into a standardized data format
  • configuration-driven preprocessing, splitting, normalization, and more
  • integration with pytorch and tensorflow

How to Install

pip install "git+https://github.com/teco-kit/whar-datasets.git"

This installs the library into the active environment.

How To Use With PyTorch

from whar_datasets import (
    Loader,
    LOSOSplitter,
    PostProcessingPipeline,
    PreProcessingPipeline,
    TorchAdapter,
    WHARDatasetID,
    get_dataset_cfg,
)

# create cfg for WISDM dataset
cfg = get_dataset_cfg(WHARDatasetID.WISDM)

# create and run pre-processing pipeline
pre_pipeline = PreProcessingPipeline(cfg)
activity_df, session_df, window_df = pre_pipeline.run()

# create LOSO splits
splitter = LOSOSplitter(cfg)
splits = splitter.get_splits(session_df, window_df)
split = splits[0]

# create and run post-processing pipeline for the specific split
post_pipeline = PostProcessingPipeline(cfg, pre_pipeline, window_df, split.train_indices)
samples = post_pipeline.run()

# create dataloaders for the specific split
loader = Loader(session_df, window_df, post_pipeline.samples_dir, samples)
adapter = TorchAdapter(cfg, loader, split)
dataloaders = adapter.get_dataloaders(batch_size=64)

Not yet natively supported WHAR datasets can be integrated via a custom configuration (with parser).

Currently Supported Datasets

Supported Name Year Paper Citations
WISDM 2010 Activity Recognition using Cell Phone Accelerometers 3862
UCI-HAR 2013 A Public Domain Dataset for Human Activity Recognition using Smartphones 3372
PAMAP2 2012 Introducing a New Benchmarked Dataset for Activity Monitoring 1758
OPPORTUNITY 2010 Collecting complex activity datasets in highly rich networked sensor environments 1024
HHAR 2015 Smart Devices are Different: Assessing and Mitigating Mobile Sensing Heterogeneities for Activity Recognition 1019
UTD-MHAD 2015 UTD-MHAD: A Multimodal Dataset for Human Action Recognition Utilizing a Depth Camera and a Wearable Inertial Sensor 997
MHEALTH 2014 mHealthDroid: A Novel Framework for Agile Development of Mobile Health Applications 887
DSADS 2010 Comparative study on classifying human activities with miniature inertial and magnetic sensors 780
USC-HAD 2012 USC-HAD: A Daily Activity Dataset for Ubiquitous Activity Recognition Using Wearable Sensors 753
SAD 2014 Fusion of Smartphone Motion Sensors for Physical Activity Recognition 752
UniMiB-SHAR 2017 Unimib shar: a dataset for human activity recognition using acceleration data from smartphones 712
Daphnet 2009 Ambulatory monitoring of freezing of gait in Parkinson’s disease 652
CHAD 2016 Complex human activity recognition using smartphone and wrist-worn motion sensors 554
DIP 2018 Deep inertial poser: Learning to reconstruct human pose from sparse inertial measurements in real time 495
RealWorld 2016 On-body Localization of Wearable Devices: An Investigation of Position-Aware Activity Recognition 482
TotalCapture 2017 Total capture: 3d human pose estimation fusing video and inertial sensors 437
ExtraSensory 2016 Recognizing Detailed Human Context In-the-Wild from Smartphones and Smartwatches 402
MobiAct 2016 The MobiAct dataset: recognition of activities of daily living using smartphones 364
MotionSense 2019 Mobile Sensor Data Anonymization 345
PARDUSS 2013 Towards physical activity recognition using smartphone sensors 345
SWELL-KW 2014 The SWELL Knowledge Work Dataset for Stress and User Modeling Research 339
SHL 2018 The University of Sussex-Huawei Locomotion and Transportation Dataset for Multimodal Analytics with Mobile Devices 317
DA 2012 Recognizing Human Activities User-independently on Smartphones Based on Accelerometer Data 302
UMAFall 2017 Umafall: A multisensor dataset for the research on automatic fall detection 243
REALDISP 2014 Dealing with the Effects of Sensor Displacement in Wearable Activity Recognition 216
RealLifeHAR 2020 A Public Domain Dataset for Real-Life Human Activity Recognition Using Smartphone Sensors 208
WISDM-19 2019 WISDM: Smartphone and Smartwatch Activity and Biometrics Dataset 198
KU-HAR 2021 KU-HAR: An open dataset for heterogeneous human activity recognition 187
HASC-Challenge 2011 Hasc challenge: gathering large scale human activity corpus for the real-world activity understandings 157
HuGaDB 2018 HuGaDB: Human Gait Database for Activity Recognition from Wearable Inertial Sensor Networks 154
Mmact 2019 Mmact: A large-scale dataset for cross modal human action understanding 145
HARTH 2021 HARTH: A Human Activity Recognition Dataset for Machine Learning 132
MobiFall 2014 The MobiFall Dataset: Fall Detection and Classification with a Smartphone 128
LARa 2020 Lara: Creating a dataset for human activity recognition in logistics using semantic attributes 119
FallAllD 2020 FallAllD: An Open Dataset of Human Falls and Activities of Daily Living for Classical and Deep Learning Applications 115
w-HAR 2020 w-HAR: An Activity Recognition Dataset and Framework Using Low-Power Wearable Devices 98
HAR70+ 2021 A machine learning classifier for detection of physical activity types and postures during free-living 55
TNDA-HAR 2022 Deep transfer learning with graph neural network for sensor-based human activity recognition 48
CAPTURE-24 2024 CAPTURE-24: A large dataset of wrist-worn activity tracker data collected in the wild for human activity recognition 45
GOTOV 2022 A recurrent neural network architecture to model physical activity energy expenditure in older people 33
PAR 2021 Context-aware support for cardiac health monitoring using federated machine learning 12
iSPL 2022 An Investigation on Deep Learning-Based Activity Recognition Using IMUs and Stretch Sensors 11
AReM 2016 Activity Recognition system based on Multisensor data fusion (AReM) dataset 7
HARSense 2021 Harsense: statistical human activity recognition dataset 5
CHARM 2021 A recommendation specific human activity recognition dataset with mobile device's sensor data 5
HIP 2022 Complete Inertial Pose Dataset: from raw measurements to pose with low-cost and high-end MARG sensors 3

Citation

If you use the WHAR Datasets library in your research, please cite our paper:

@inproceedings{burzer2025whar,
  title={WHAR Datasets: An Open Source Library for Wearable Human Activity Recognition},
  author={Burzer, Maximilian and King, Tobias and Riedel, Till and Beigl, Michael and R{\"o}ddiger, Tobias},
  booktitle={Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing},
  pages={1315--1322},
  year={2025}
}

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 2

  •  
  •  

Languages