SEMG signal database for the automated upper limb rehabilitation process - Open Research Data - Bridge of Knowledge

Search

SEMG signal database for the automated upper limb rehabilitation process

Description

An automated rehabilitation device control system requires information about the patient's physiological condition. This is possible thanks to the use of biological feedback in the form of electromyography and surface signals (Surface Electromyography, SEMG).

The popularity of SEMG signals is due to the non-invasive method and the ability to quickly and precisely identify muscle function. The biosignal database was created during a series of upper limb rehabilitation exercises using specialized equipment. During the exercise, bioelectric activity of four muscles responsible for the movements and located in the surface layer were examined: elbow flexor of the wrist, radial flexor of the wrist, short palmar and long palmar.

Illustration of the publication

Tools used to collect measurements

Dataset file

SEMG signal database.rar
968.7 kB, S3 ETag ae9c29e5e2e3ab63f884240278085c65-1, downloads: 62
The file hash is calculated from the formula
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
https://github.com/antespi/s3md5

File details

License:
Creative Commons: by 4.0 open in new tab
CC BY
Attribution
Raw data:
Data contained in dataset was not processed.

Details

Year of publication:
2020
Verification date:
2020-12-17
Creation date:
2017
Dataset language:
English
Fields of science:
  • Automation, electronic and electrical engineering (Engineering and Technology)
DOI:
DOI ID 10.34808/9cz0-3837 open in new tab
Verified by:
Gdańsk University of Technology

Keywords

References

Cite as

seen 171 times