1436 - Investigating the Impact of Proprioception Changes after Stroke: Relationship Between Perceived and Actual Deficits

Objectives: Proprioceptive impairment plays a key role in upper extremity movement recovery post-stroke. The objective of this study was to explore the subjective perception of proprioceptive impairment compared to an objective measure obtained with a robotic device.

Design: 18 individuals greater than six months post-stroke received three weeks of robot-assisted finger movement training that included a robotic finger proprioception assessment called Crisscross. For Crisscross, participants must indicate when their index and middle fingers pass by each as the robot moves their fingers passively. We quantified proprioception error as the average magnitude of separation between the fingers at perceived crossings. We also assessed motor impairment using the Upper Extremity Fugl-Meyer (UEFM) scale. Following robotic training, we asked the participants to rate the extent to which they noticed changes or difficulties with proprioception (“overall perceived proprioception change”), their level of awareness of their index and middle finger (“finger awareness”), the quality of using their affected hand for 15 activities of daily living (“limb use”), and their Crisscross performance.

Results: Neither overall perceived proprioception change nor finger awareness was significantly correlated with Crisscross error (p > 0.4). However, finger awareness was significantly correlated with self-rated Crisscross performance (middle finger, ρ = 0.48, p = 0.045; index finger, ρ = 0.46, p = 0.058). Participants with more severely impaired proprioception also stated that they relied more on their unaffected hand (ρ = 0.821, p = 0.023), even though motor impairment, quantified with UEFM score, was not correlated with Crisscross error (p > 0.09).

Conclusions: These results challenge the assumption that self-reporting of proprioception reflects actual ability, although, within the specific context of a robotic proprioception test, individuals did accurately estimate their finger-sensing ability. Further, self-assessment of decreased limb use is related to actual finger proprioception deficit, independent of motor ability.

Scientific Paper Best Paper Award Abstract:

Objective: Stroke recovery is a complex process that can significantly impact an individual's quality of life. Over half of persons with a stroke experience proprioception deficits. Proprioception enables us to sense our body's position in space and the relative movements of its parts, making it a pivotal factor in motor control and learning. While proprioception deficits are common and impactful after a stroke, little is known about how individuals with a stroke perceive their proprioception impairment. The objective of this study was to explore the subjective perception of proprioceptive impairment compared to an objective measure obtained with a robotic device.



Design: 18 individuals who were at least six months post-stroke and received three weeks of robot-assisted finger movement training that included a finger proprioception assessment. Following training, we asked participants 37 questions to identify any body parts they noticed changes in proprioception (“noticeable proprioception change”), and they were also asked to rate the extent to which they noticed change or difficulties with proprioception (“overall perceived proprioception change”), their level of awareness of their index and middle finger (“finger awareness”), the quality of using their affected hand for 15 activities of daily living (“limb use”), and their performance at a robotic finger proprioception test (“Crisscross”). The 15 activities of daily living (ADL) were selected from the Motor Activity Log (MAL), which is a clinical assessment for both the amount and quality of spontaneous upper limb use during daily tasks.

We compared the relationship between these subjective survey responses to an objective measure of finger proprioception called Crisscross. Crisscross is a robotic proprioception assessment where participants must indicate when their index and middle fingers pass by each other as the robot moves their fingers passively in a crossing pattern with the vision of the hand occluded. We quantified proprioception error as the average magnitude of separation between the fingers at perceived crossing indicated by the button press, measured across 20 crossings. This assessment combines components of movement discrimination, direction sense, and comparison between relative limb positions in space. A key advantage of this assessment is that it does not require the participant to be able to move the limb being tested, nor does it include a memory component such that even severely impaired individuals can participate in the test.

Motor impairment was also evaluated using the Upper Extremity Fugl-Meyer (UEFM) scale. The UEFM is a well-established clinical assessment tool with a maximum score of 66 points. It evaluates different aspects of motor function, such as muscle strength, coordination, reflexes, and movement quality in individuals affected by stroke.

The robot-assisted finger movement training protocol included 3 weeks of training, with proprioceptive and clinical assessments of hand function, including the UEFM scale, taken at three different time points: 1 week before, 1 week after, and 1 month after training. The UEFM measurement used for each participant was taken at the post-training time point when participants completed the survey. Training included assisted flexion and extension movements of the fingers. We compared survey responses to proprioception and clinical measures assessed at the end of therapy.



Results: Neither overall perceived proprioception change nor finger awareness was significantly correlated with Crisscross error (p > 0.4). However, finger awareness was significantly correlated with self-rated Crisscross performance (middle finger, ρ = 0.48, p = 0.045; index finger, ρ = 0.46, p = 0.058).

Furthermore, participants with more severely impaired proprioception stated that they relied more on their unaffected hand (ρ = 0.821, p = 0.023), even though motor impairment, quantified with UEFM score, was not correlated with Crisscross error (p > 0.09).

Higher UEFM scores, signaling better motor function, significantly correlated with noticeable proprioception changes to the arms and lower legs (arms: ρ = -.497, p = 0.036; lower legs: ρ = -.498, p = .035).



Conclusion:

After a stroke, people did not rate their overall proprioceptive change and finger awareness in a way consistent with an objective measure of finger proprioception, emphasizing the need for objective evaluations to evaluate proprioceptive impairments, and challenging the assumption that self-reporting accurately reflects one’s proprioceptive abilities. However, within the specific context of a robotic proprioception test, individuals did accurately estimate their finger-sensing ability. This suggests that, while individuals have difficulty assessing the effect of proprioceptive loss in daily life, they can accurately assess it when it is specifically challenged.

Perception of decreased limb use was related to actual finger proprioception deficit, independent of motor ability. However, people who exhibited better motor ability were less likely to experience noticeable proprioception changes to their upper and lower extremities, suggesting that preservation of proprioception in these body parts may contribute to better motor ability.

Further research with larger sample sizes is necessary to validate and expand our understanding of post-stroke patient perception of proprioception changes in relation to upper extremity movement recovery after stroke.