Paper
14 June 2011 Robot-assisted motor activation monitored by time-domain optical brain imaging
O. Steinkellner, H. Wabnitz, S. Schmid, R. Steingräber, H. Schmidt, J. Krüger, R. Macdonald
Author Affiliations +
Abstract
Robot-assisted motor rehabilitation proved to be an effective supplement to conventional hand-to-hand therapy in stroke patients. In order to analyze and understand motor learning and performance during rehabilitation it is desirable to develop a monitor to provide objective measures of the corresponding brain activity at the rehabilitation progress. We used a portable time-domain near-infrared reflectometer to monitor the hemodynamic brain response to distal upper extremity activities. Four healthy volunteers performed two different robot-assisted wrist/forearm movements, flexion-extension and pronation-supination in comparison with an unassisted squeeze ball exercise. A special headgear with four optical measurement positions to include parts of the pre- and postcentral gyrus provided a good overlap with the expected activation areas. Data analysis based on variance of time-of-flight distributions of photons through tissue was chosen to provide a suitable representation of intracerebral signals. In all subjects several of the four detection channels showed a response. In some cases indications were found of differences in localization of the activated areas for the various tasks.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
O. Steinkellner, H. Wabnitz, S. Schmid, R. Steingräber, H. Schmidt, J. Krüger, and R. Macdonald "Robot-assisted motor activation monitored by time-domain optical brain imaging", Proc. SPIE 8088, Diffuse Optical Imaging III, 808807 (14 June 2011); https://doi.org/10.1117/12.889505
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Brain

Near infrared spectroscopy

Photons

Tissue optics

Brain imaging

Data analysis

Hemodynamics

Back to Top