Quantitative assessment of hand function by hand motion analysis usingcyberglove

Abstract

Hand motion analysis methods have been providing researchers with motion

investigation initiatives, revealing motion features and mechanisms in both

healthy subjects and patients suffering from hand dysfunctions. Technical

advancements have led to the maturation of motion capturing methods such as

goniometric gloves. In this project, the CyberGlove as a manufactured product

was chosen as a potential tool for the development of a hand function assessment

system that would ultimately distinguish between healthy subjects and patients

suffering from hand dysfunctions.

In this study, the evaluation of the CyberGlove as a feasible clinical tool and its

technical adaptations were done in parallel. The sensor output characteristics were

investigated using X-ray photography as a spatial golden standard and the sensors

were shown to exhibit linear qualities with optimal nonlinearities at 0.6%. The

measurement sensitivity and accuracy by the CyberGlove was improved by

establishing a calibration protocol suiting the sensor characteristics. Through a

calibration protocol using calibration tools made by thermoplastics, the angular

measurement error was found to decrease from 7.2% to 1.2%.

The technical development of the software part of the project involved the

inclusion of data preprocessing, display and analysis modules. To investigate the

motion exhibited by healthy subjects, 32 healthy subjects were recruited and they

were asked to complete a series of motion according to a designed motion

protocol involving a static trial, a timed-grip trial and a rapid-grip trial. Motion

features were extracted from recorded motion data by identification and

quantification of temporal or spatial characteristics in motion such as joint

sequence of events, angular kinematics, finger tip path features and phase diagram

features. Some features were evaluated by pattern correlation analysis by linear

regression, and healthy subjects all shared similar patterns resulting in high levels

of regression coefficients R2 and low levels of slope deviations m.

The establishment of motion features along with a prototype motion measurement

system allows the continuous development on the CyberGlove as a hand function

assessment tool when supported by later clinical adaptations or studies.