Datasets
Standard Dataset
Motion-Print Control Task Movements (38 subjects)
- Citation Author(s):
- Submitted by:
- Sam Heiserman
- Last updated:
- Fri, 05/29/2020 - 16:24
- DOI:
- 10.21227/wpyf-r927
- Data Format:
- License:
300 Views- Categories:
- Keywords:
Abstract
This dataset is composed of 4-Dimensional time series files, representing the movements of all 38 participants during a novel control task. In the ‘5D_Data_Extractor.py’ file this can be set up to 6-Dimension, by the ‘fields_included’ variable. Two folders are included, one ready for preprocessing (‘subjects raw’) and the other already preprocessed ‘subjects preprocessed’.
In the 'subjects raw' folder there is 1 file per subject, with all 15 runs of the task contained. Each run is separated by a line of all zeros. The raw data is sampled at 100 HZ, meaning 100 samples per second. Given this high sampling rate aggregation is done in preprocessing, to produce the files in the 'subjects preprocessed' folder. Depending on the ‘agg_rate’ given in the ‘5D_Data_Extractor.py’ file, each run at 100 HZ is sampled down by combining every ‘agg_rate’ data points (such as 100, 50 or 20) into one.
In the 'subjects preprocessed' folder there are 2 files per subject, one 'TRAIN' and one 'TEST', which have been aggregated and split from the 'subjects raw' folder. These were made using ‘agg_rate’ of 100 (converting them to 1 HZ), ‘fields_included’ of ‘Ys’ and ‘Zs’, and ‘Dists’ and ‘test_runvals’ of 13, 14, 15. This means that of the 15 total runs, those three runs composed the TEST for each subject. The 'TRAIN' files are therefore larger, containing the subjects' movements on runs 1-12 of the task. The 'TRAIN' files were used to fit machine learning models for each subject, and the 'TEST' files were used to validate these models.
Terms of Use for Motion-Print Dataset
1. Definitions
The following terms, unless the context requires otherwise, have the following meanings:
“Data Team”: means Sam Heiserman, Dr Kirill Zaychik, Dr Tim Miller and the Man-Machine Systems Lab in the Watson School at Binghamton University.
“Motion-Print Dataset”: means the data set provided herein, developed in Man-Machine Systems Lab in the Watson School of Engineering at Binghamton University -- supported by NASA/New York Space Grant Consortium National Space College and Fellowship Program,
“Licensee”, “You”, “Your”, “Yours”: means the person or entity acquiring a license hereunder for access to and use of the Motion-Print Dataset.
2. Grant of License
Sam Heiserman of the Data Team hereby grants to You a non-exclusive, non-transferable, revocable license to use the Motion-Print Dataset solely for Your non-commercial, educational, and research purposes only, but without any right to copy or reproduce, publish or otherwise make available to the public or communicate to the public, sell, rent or lend the whole or any constituent part of the Motion-Print Dataset thereof. The Motion-Print Dataset shall not be redistributed without the express written prior approval of Sam Heiserman. You agree to respect the privacy of those human subjects whose control behavior data are included in the Motion-Print Dataset.
You agree to acknowledge the source of the Motion-Print Dataset in all of Your publications and presentations based wholly or in part on the Motion-Print Dataset. You agree to provide a disclaimer in any publication or presentation to the effect that Sam Heiserman and the Data Team do not bear any responsibility for Your analysis or interpretation of Motion-Print Dataset.
You agree and acknowledge that Sam Heiserman and the Data Team may hold, process, and store any personal data submitted by You for validation and statistical purposes and for the purposes of the administration and management of Motion-Print Dataset. You agree that any personal data submitted by You is accurate to the best of his or her knowledge.
Sam Heiserman and the Data Team provide the Motion-Print Dataset "AS IS," without any warranty or promise of technical support, and disclaims any liability of any kind for any damages whatsoever resulting from use of the Motion-Print Dataset.
After acquiring the license of the Motion-Print database, user is requested to delete the database after 2 years. If a user wishes to use it after 2 years, he/she will need to acquire the license again.
Sam Heiserman MAKES NO WARRANTIES, EXPRESS OR IMPLIED WITH RESPECT TO THE Motion-Print DATASET, INCLUDING ANY IMPLIED WARRANTY OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE, WHICH ARE HEREBY EXPRESSLY DISCLAIMED.
Your acceptance and use of the Motion-Print Dataset binds you to the terms and conditions of this License as stated herein.
Dataset Files
- This is the preprocessed data, with a TRAIN and TEST file for each subject. subjects preprocessed.zip (284.06 kB)
- This is the raw data. Each subject's files contains 15 task runs, with each run separated by a row of zeros. subjects raw.zip (12.09 MB)
- This script can generate new preprocessed files from the raw, with other 'agg_rate', 'test_runvals' & 'fields_included' values. 5D_Data_Extractor.py (5.87 kB)
Documentation
| Attachment | Size |
|---|---|
 Motion-Print Data Readme.docx | 6.83 KB |
Comments
hi
where can i find the download file's dataset?
Hi Elahe,
It should be there under 'Dataset Files' on the right side of the page.
There should be two links.
I just clicked them and downloaded, so I imagine you can too?
Hello,
This dataset has included the keyword "Anomaly Detection" in it, but it seems like that's not a main point of this dataset. As my main interest is in obtaining a dataset for anomaly detection, could I get some clarification on this?