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Title:

Time Series Dataset for AI-driven Identification of Early Warning Patterns of Pressure Ulcers

Document type:
Forschungsdaten
Publication date:
16.10.2023
Responsible:
Heinrich, Ferdinand
Authors:
Gruenerbel, Lorenz (1); Heinrich, Ferdinand (1); Böhlhoff-Martin, Jonathan (2); Röper, Lynn (2); Machens, Hans-Günther (2); Gruenerbel, Arthur (3); Schillinger, Moritz (4); Kist, Andreas (4); Wenninger, Franz (1); Richter, Martin (1); Steinbacher, Leonhard (2)
Author affiliation:
1) Fraunhofer Institute for Electronic Microsystems and Solid State Technologies EMFT;
2) Department for Plastic Surgery and Hand Surgery, Technical University Munich;
3) Bavarian Foot Network;
4) Artificial Intelligence in Communication Disorders, Friedrich-Alexander-University Erlangen-Nürnberg.
Publisher:
TUM
Identifier:
doi:10.14459/2023mp1717646
End date of data production:
31.12.2022
Subject area:
DAT Datenverarbeitung, Informatik; ELT Elektrotechnik; MED Medizin
Resource type:
Sonstiges / other
Other resource types:
Clinical Study
Data type:
Tabellen / tables
Other data type:
Time Series Data, Sensor Data
Description:
This dataset contains data of a healthy control group that used the wearable sensor device at home and a bedridden patient group that used the wearable sensor device during a clinical study at the Department for Plastic Surgery and Hand Surgery of the University Hospital Klinikum rechts der Isar.
For each patient the reflective SpO2, the skin temperature and the pressure applied on the skin at pressure ulcers risk areas is recorded time continuously with the wearable sensor system. Additionally, the heart rate and accelerometer data of the main electronics is also time continuously acquired.
Physical data and relevant preconditions are saved in the meta data.
The screening data contains the date of the positive Phillips finger tests and vital signs recorded by the medical staff (blood pressure; finger clip oximeter: heart rate, SpO2; ear thermometer: tympanic temperature)
Method of data assessment:
The data of the bedridden patient group was acquired with the wearable sensor device during a clinical study at the Department for Plastic Surgery and Hand Surgery of the University Hospital Klinikum rechts der Isar. The ethics commission of the TU Munich accepted this clinical study (687/21 S-SR). The data was transferred via a telemedicine server provided by our partner Monks that holds certificates of secure data transfer. At the Fraunhofer EMFT the anonymised data was analysed with python: h...     »
Links:

Access to this research data is restricted. Please contact Mr. Ferdinand Heinrich  for the password:  ferdinand.heinrich@tum.de  Check " Other rights" for the terms of use of the data. 

Related Software : https://gitlab.cc-asp.fraunhofer.de/MLS-public/kiprode

This dataset relates to the publication: https://www.mdpi.com/2306-5354/10/10/1125

Key words:
Pressure Ulcers; Decubitus; Bedsore; Foot Ulcer; Prophylaxis; Time Series; Machine Learning; AI
Technical remarks:
View and download (123 MB total, 78 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1717646):
rsync rsync://m1717646@dataserv.ub.tum.de/m1717646/
Language:
en
Other rights:
THIS DATA IS AVAILABLE THROUGH THIS REPOSITORY FOR LAWFUL ACADEMIC NON-COMMERCIAL USE ONLY.
IF YOU ARE AN ACADEMIC LOOKING TO ACCESS THE DATA PLEASE CONTACT FERDINAND.HEINRICH@TUM.DE.
YOU MUST SUBMIT AN APPLICATION DETAILING YOUR ACADEMIC STATUS AND PROVIDING AN OVERVIEW OF YOUR INTENDED USE OF THE DATA.
THIS WILL BE REVIEWED AND ACCESS WILL BE GRANTED ON THE BASIS OF THE REVIEW.
THE DATA CAN ONLY BE USED BY THE APPLICANTS NAMED ON THE APPLICATION AND FOR THE INTENDED USE SPECIFIED IN THE APPLICATION.
COPY OR DISTRIBUTION OF THIS DATASET IS STRICTLY PROHIBITED.
THE DATA ARE PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE DATA OR THE USE OR OTHER DEALINGS IN THE DATA.
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