Robotic Identification of Kinesthetic Deficits After Stroke

Abstract

Background and Purpose-Kinesthesia, the sense of body motion, is essential to proper control and execution of movement.Despite its importance for activities of daily living, no current clinical measures can objectively measure kinesthetic deficits. The goal of this study was to use robotic technology to quantify prevalence and severity of kinesthetic deficits of the upper limb poststroke. Methods-Seventy-four neurologically intact subjects and 113 subjects with stroke (62 left-affected, 51 right-affected) performed a robot-based kinesthetic matching task with vision occluded. The robot moved the most affected arm at a preset speed, direction, and magnitude. Subjects were instructed to mirror-match the movement with their opposite arm (active arm). Results-A large number of subjects with stroke were significantly impaired on measures of kinesthesia. We observed impairments in ability to match movement direction (69% and 49% impaired for left-and right-affected subjects, respectively) and movement magnitude (42% and 31%). We observed impairments to match movement speed (32% and 27%) and increased response latencies (48% and 20%). Movement direction errors and response latencies were related to clinical measures of function, motor recovery, and dexterity. Conclusions-Using a robotic approach, we found that 61% of acute stroke survivors (n=69) had kinesthetic deficits.Additionally, these deficits were highly related to existing clinical measures, suggesting the importance of kinesthesia in day-to-day function. Our methods allow for more sensitive, accurate, and objective identification of kinesthetic deficits after stroke. With this information, we can better inform clinical treatment strategies to improve poststroke rehabilitative care and outcomes.

Examining Differences in Patterns of Sensory and Motor Recovery After Stroke With Robotics

“…Subjects performed 4 individual robotic tasks assessing position sense 14 ( Figure 1A), kinesthesia 15 ( Figure 1B), motor function of the affected arm 21 ( Figure 1C), and simultaneous motor function of both arms 25 ( Figure 1D). For all tasks, subjects sat in the wheelchair base of the robotic exoskeleton (KINARM; BKIN Technologies Ltd, Kingston, Ontario, Canada) with their arms supported against gravity.…”

“…In the kinesthetic matching task (KIN) 15 ( Figure 1B), without vision, the robot moved the subjects' stroke-affected arm (passive arm) to 1 of the 3 locations at a preset speed, direction, and magnitude of movement. Subjects then mirror-matched the robotic movement with the less-affected arm (active arm) as soon as they felt the passive arm begin to move.…”

“…Subjects then mirror-matched the robotic movement with the less-affected arm (active arm) as soon as they felt the passive arm begin to move. We measured 8 parameters known to quantify kinesthesia 15 : (1) initial direction error (IDE), (2) initial direction error variability, (3) path length ratio (PLR), (4) path length ratio variability, (5) response latency, (6) response latency variability, (7) peak speed ratio, and (8) peak speed ratio variability.…”

“…1,2,9 Yet, somatosensory deficits contribute to poor function after stroke, [10][11][12][13] with >50% of stroke survivors having proprioceptive impairments. 14,15 Although these deficits are thought to significantly affect stroke recovery, 10,16 few studies have examined the effect of somatosensory impairments on recovery. 12,17 Most studies examining motor or sensory recovery have relied on observer-based ordinal scales.…”

“…1,2,9,12 These have been criticized for problems with ceiling effects 18 or issues with reliability. 19 However, more recently, robotics have shown to be a powerful measurement tool 14,15,[20][21][22][23] for determining when impairment returns to normal using continuous performance metrics that allow for comparison of poststroke performance with neurologically intact humans.…”