Automated measurement of proprioception following stroke.
BACKGROUND
Proprioception provides feedback which is essential for adequate motor control. Despite having detrimental functional implications, the assessment of proprioception deficits in current clinical practice is mostly qualitative and inadequate for diagnosis and longitudinal monitoring of subtle impairments and their effect on motor function.


PURPOSE
To evaluate a novel quantitative approach to the assessment of proprioception deficits in stroke patients.


METHOD
We designed and implemented an automated protocol where a magnetic motion tracking system and a sensor attached to each of the patient's hands, enables registration of trajectories in 3D coordinates. In this protocol the patient's affected and healthy hands are placed respectively below and above a square board. With vision blocked, the subject's affected hand is passively moved to one of four locations, and then the patient is instructed to actively position the healthy hand directly above his/her perceived location of the affected hand. The positional difference between the two hands is automatically recorded by the system. This procedure is repeated several times and the magnitude and direction of errors are used to quantify the proprioception deficit. The data for this pilot study was collected in a sample of 22 stroke patients and an age-matched group of neurologically intact subjects.


RESULTS
Stroke patients had significantly higher mean distance error compared with the control group (average values of 7.9 and 5.3 cm, respectively), and showed higher instability (variance) in repeated performance (average values of the standard deviation of errors 3.4 and 1.8 cm, respectively). Significant correlation was found between the mean distance error and the results of semi-quantitative clinical tests of proprioception.


CONCLUSION
The system provides a reliable quantitative measure of upper limb proprioception, offering considerable advantage over the traditional means applied in the clinic.