Using a tablet to understand the spatial and temporal characteristics of complex upper limb movements in chronic stroke

Abstract

Robotic devices are commonly used to quantify sensorimotor function of the upper limb after stroke; however, the availability and cost of such devices make it difficult to facilitate implementation in clinical environments. Tablets (e.g. iPad) can be used as devices to facilitate rehabilitation but are rarely used as assessment tools for the upper limb. The current study aimed to implement a tablet-based Maze Navigation Task to examine complex upper-limb movement in individuals with chronic stroke. We define complex upper-limb movement as reaching movements that require multi-joint coordination in a dynamic environment. We predicted that individuals with stroke would have more significant spatial errors, longer movement times, and slower speeds compared to controls with increasing task complexity. Twenty individuals with chronic stroke who had a variety of arm and hand function (Upper extremity Fugl-Myer 52.8 ± 18.3) and twenty controls navigated eight pseudorandomized mazes on an iPad using a digitizing stylus. The task was designed to elicit reaching movements engaging both the shoulder and elbow joints. Each maze became increasingly complex by increasing the number of 90° turns. We instructed participants to navigate each maze as quickly and accurately as possible while avoiding the maze's boundaries. Sensorimotor behavior was quantified using the following metrics: Error Time (time spent hitting or outside boundaries), Peak Speed, Average Speed, and Movement Time, Number of Speed Peaks. We found that individuals with stroke had significantly greater Error Time for all maze levels (all, p < 0.01), while both speed metrics, Movement Time and Number of Speed Peaks were significantly lower for several levels (all, p < 0.05). As maze complexity increased, the performance of individuals with stroke worsened only for Error Time while control performance remained consistent (p < 0.001). Our results indicate that a complex movement task on a tablet can capture temporal and spatial impairments in individuals with stroke, as well as how task complexity impacts movement quality. This work demonstrates that a tablet is a suitable tool for the assessment of complex movement after stroke and can serve to inform rehabilitation after stroke.

Fig 1

(A) Experimental setup depicting the Apple iPad Pro (10^th generation) and Apple 2^nd generation digitizing pen. (B) Overhead view of the tablet screen with example tracing movement for Level 1 of the Maze Navigation Task. Using an Apple pencil, participants drag the orange cursor through the maze while avoiding the white walls. Movement is recorded between the start and end positional thresholds noted by the borders of the green and grey regions, respectively. The time the orange cursor is in contact with or goes outside the white maze boundary is recorded and noted as Error Time.

Fig 2. Exemplar kinematic hand traces on the Maze Navigation Task for Levels 2, 4, 6, and 8.

Data is averaged across five trials, with the shaded region indicating standard deviation for hand position (A) and hand speed (B) for an exemplar control (purple) and an individual with stroke (cyan). A) Hand position as a function of level performance shows that the individual with stroke made more errors and had more difficulty maintaining their hand path within the borders of the maze. B) Hand speed as a function of level performance shows that the individual with stroke took consistently longer and had overall reduced hand speed compared to the control participant.

Fig 3

We compared the overall performance Peak Speed (A), Error Time (B), Average Speed (C), Movement Time (D) and Number of Speed Peaks (E) across eight levels. We found significant differences between groups for each measure, indicating that individuals with chronic stroke moved slower, spent more time in contact with the maze boundaries, made more corrective movements, and took more time to navigate the workspace as controls.

Fig 4. Temporal and spatial accuracy measures for performance across the Maze Navigation Task levels 1–8.

We found that individuals with stroke had significantly reduced Average Speed (C) and Peak Speed (A) while having increased Movement Time (D) and Number of Speed Peaks (E) when compared to controls at several levels. While the median Error Time (B) for each level was relatively low for both groups; the individuals with stroke spent significantly more time against or outside the walls of the maze than the controls. (*p<0.05, **p<0.01, ***p<0.001).

Fig 5. Ordinary Least Squares (OLS) was used to determine the relationship between groups as the level of task complexity increased.

β₀ (y intercept) and β₁ (slope) were obtained by taking the average of bootstrapped distributions of β₀’s and β₁’s after 1,000,000 permutations. Insets in each panel show comparisons between groups of each participants averaged β₀ and β₁. Permutation tests between group distributions of β₀ and β₁ were used to determine differences between groups. We found that individuals with stroke were significantly impaired in all parameters as indicated by higher β₀ values. Furthermore, we found that sensorimotor performance diminished as level complexity increased for both individuals with stroke and controls for Peak Speed (A), Average Speed (C), and Movement Time (D) as indicated by similar β₁ values. Interestingly, we found that as task difficulty increased, Error Time (B) only increased for the stroke group, where Error Time increased as a function of level for individuals with stroke, but remained flat for control participants.

Fig 6. We compared the Fugl-Meyer (FMA) clinical assessment scores for individuals with stroke with their performance for each outcome measure.

FMA scores range from 0 (severe hemiparesis) to 66 (normal motor performance). We divided our individuals with stroke into subgroups based on a previously conducted cluster analysis that defined FMA > 53 as mild impairments (N = 13) and FMA < 53 as moderate to severe impairment (N = 7). We found that individuals with stroke with more severe levels of hemiparesis had decreased performance in Peak Speed (A), Average Speed (B), Error Time (C), Movement Time (D), and Number of Speed Peaks (E) when compared to both mild and control groups (***p < 0.001).