When using this data, please cite:
Please also include the standard citation for PhysioNet:
Introduction
The Complex Upper-Limb Movements database contains hand trajectory data collected from ten subjects as they performed various upper-limb motor tasks. The data was used in the above-referenced manuscript to identify the motor primitives contributing to the observed motor patterns.
Background
The hand trajectory of motion during the performance of one-dimensional point-to-point movements has been shown to be marked by motor primitives with a bell-shaped velocity profile. Researchers have investigated if motor primitives with the same shape mark also complex upper-limb movements. They have done so by analyzing the magnitude of the hand trajectory velocity vector. This approach has failed to identify motor primitives with a bell-shaped velocity profile as the basic elements underlying the generation of complex upper-limb movements. In this study, we examined upper-limb movements by analyzing instead the movement components defined according to a Cartesian coordinate system with axes oriented in the medio-lateral, antero-posterior, and vertical directions.
Ten healthy subjects (7 males; 26.4±4.52 years of age; 9 right-handed) with no known neurological or orthopedic conditions affecting the control of motion were recruited to participate in the study. Written informed consent was obtained from all subjects. The protocol was approved by the Institutional Review Board of Spaulding Rehabilitation Hospital. The dataset was collected in the Motion Analysis Lab (http://srh-mal.net/) at Spaulding Rehabilitation Hospital.
Data Collection
To explore the validity of the theoretical model proposed in the above-referenced manuscript, we asked a group of ten healthy subjects to perform a battery of upper-limb motor tasks. Data collected using a camera-based motion capture system (VICON, Oxford UK) was preprocessed using the system’s software to reconstruct the three-dimensional position of a reflective marker representing the hand trajectory of motion.
Files
The csv data files contain four columns. The data in the first column is the time axis in seconds. The data samples in the other three columns are the x-, y-, and z-coordinates of the reflective marker utilized in each experiment to represent the hand trajectory of movement. The data is reported in meters. Different files contain data pertaining to different subjects for different motor tasks. Different filenames are used for different tasks as follows:
- BostonCA --> Writing the word Boston in Capital letters
- BostonCU --> Writing the word Boston in cursive letters
- HarvardCA --> Writing the word Harvard in Capital letters
- HarvardCU --> Writing the word Harvard in cursive letters
- Can --> 3D arm movements to reach for and transport a can of soda positioned on a table
- Circle --> Drawing circles
- Ellipse --> Drawing ellipses
- Flower --> Drawing a pure frequency curve with v=4/3
- Spiral --> Drawing a pure frequency curve with v=0
- SuperMegaCloud --> Drawing a pure frequency curve with v=4/5
- Triangle --> Drawing a pure frequency curve with v=3
- Planned --> series of 2D planned (i.e. with target) movements of the arm
- Unplanned --> series of 2D unplanned (i.e. without target) movements of the arm
- Randomness --> 3D random movements
Contact
More information about the experimental protocol can be obtained from José Miranda (vivasm@gmail.com) or Paolo Bonato (pbonato@mgh.harvard.edu).
Name Last modified Size Description
Parent Directory - DOI 2018-09-04 09:17 19 S010/ 2018-08-30 13:48 - S011/ 2018-08-30 13:48 - S02/ 2018-08-30 13:48 - S03/ 2018-08-30 13:48 - S04/ 2018-08-30 13:48 - S05/ 2018-08-30 13:48 - S06/ 2018-08-30 13:48 - S07/ 2018-08-30 13:48 - S08/ 2018-08-30 13:48 - S09/ 2018-08-30 13:48 - csvFiles.zip 2018-08-30 13:48 12M
If you would like help understanding, using, or downloading content, please see our Frequently Asked Questions. If you have any comments, feedback, or particular questions regarding this page, please send them to the webmaster. Comments and issues can also be raised on PhysioNet's GitHub page. Updated Friday, 28 October 2016 at 16:58 EDT |
PhysioNet is supported by the National Institute of General Medical Sciences (NIGMS) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under NIH grant number 2R01GM104987-09.
|