Robotic Outcome Assessment in a Non-Human Primate Model of Middle Cerebral Artery Stroke

Stroke is a prevalent disorder with immense socioeconomic impact. A variety of chronic neurological deficits result from stroke. In particular, sensorimotor deficits are a significant barrier to achieving post-stroke independence. Unfortunately, the majority of pre-clinical studies that show improved outcomes in animal stroke models have failed in clinical trials. Pre-clinical studies using non-human primate (NHP) stroke models prior to initiating human trials are a potential step to improving translation from animal studies to clinical trials. Robotic assessment tools represent a quantitative, reliable, and reproducible means to assess reaching behaviour following stroke in both humans and NHPs. We investigated the use of robotic technology to assess sensorimotor impairments in NHPs following middle cerebral artery occlusion (MCAO). Two cynomolgus macaques underwent transient MCAO for 90 minutes. Approximately 1.5 years following the procedure these NHPs and two non-stroke control monkeys were trained in a reaching task with both arms in the KINARM exoskeleton. This robot permits elbow and shoulder movements in the horizontal plane. The task required NHPs to make reaching movements from a centrally positioned start target to 1 of 8 peripheral targets uniformly distributed around the first target. We analyzed four movement parameters: reaction time, movement time (MT), initial direction error (IDE), and number of speed maxima to characterize sensorimotor deficiencies. We hypothesized reduced performance in these attributes during a neurobehavioural task with the paretic limb of NHPs following MCAO compared to controls. Reaching movements in the non-affected limbs of control and experimental NHPs showed bell-shaped velocity profiles. In contrast, the reaching movements with the affected limbs were highly variable. We found distinctive patterns in MT, IDE, and number of speed peaks between control and experimental monkeys and between limbs of NHPs with MCAO. NHPs with MCAO demonstrated more speed peaks, longer MTs, and greater IDE in their paretic limb compared to controls. These initial results qualitatively match human stroke subjects’ performance, suggesting that robotic neurobehavioural assessment in NHPs with stroke is feasible and could have translational relevance in subsequent human studies. Further studies will be necessary to replicate and expand on these preliminary findings.

Admittance Control for Robotic Loading: Design and Experiments with a 1-Tonne Loader and a 14-Tonne LHD

This paper describes the design, tuning, and extensive field testing of an admittance-based Autonomous Loading Controller (ALC) for robotic excavation. Several iterations of the ALC were tuned and tested in fragmented rock piles—similar to those found in operating mines—by using both a robotic 1-tonne capacity Kubota R520S diesel-hydraulic surface loader and a 14-tonne capacity Atlas Copco ST14 underground load-haul-dump (LHD) machine. On the R520S loader, the ALC increased payload by 18 % with greater consistency, although with more energy expended and longer dig times when compared with digging at maximum actuator velocity. On the ST14 LHD, the ALC took 61 % less time to load 39 % more payload when compared to a single manual operator. The manual operator made 28 dig attempts by using three different digging strategies, and had one failed dig. The tuned ALC made 26 dig attempts at 10 and 11 MN target force levels. All 10 11 MN digs succeeded while 6 of the 16 10 MN digs failed. The results presented in this paper suggest that the admittance-based ALC is more productive and consistent than manual operators, but that care should be taken when detecting entry into the muck pile

COGNITIVE ASSESSMENT USING THE KINARM EXOSKELETON ROBOT IN PATIENTS WITH TRANSIENT ISCHEMIC ATTACK

Background: Transient ischemic attack (TIA) is a condition causing focal neurological deficits lasting less than 24hrs. TIA patients present similarly to other conditions with rapid onset of neurological symptoms such as migraine. The accurate diagnosis of TIA is critical because it serves as a warning for subsequent stroke. Furthermore, cognitive deficit associated with TIA may predict the development of dementia. Therefore, characterizing the cognitive symptoms of TIA patients and discriminating these patients from those with similar symptoms is important for proper diagnosis and treatment. Currently the diagnosis of TIA is made on clinical and radiographic evidence. Robotic assessment, with instruments such as the KINARM, may improve the identification of cognitive impairment in TIA patients. Methods: In this prospective cohort study, two KINARM tests, trail making task (TMT) and spatial span task (SST), were used to detect cognitive deficits. Two study groups were made. The TIA group was tested at 5 time points over the span of a year. The migraine active control group had one initial visit and another a year later. Both of these groups were compared to a normative database of approximately 400 healthy volunteers. From this database age and sex matched normative data was used to calculate Z-scores for the TMT. The Montreal Cognitive Assessment (MoCA) was also administered to both groups. Results: 31 participants were recruited, 20 TIA group and 11 active controls (mean ± SD age= 66 ± 11.3 and 62 ± 14.5). There was no significant difference in TIA and active control group MoCA scores. The TMT was able to detect cognitive impairment in TIA and migraine group. Also, both KINARM tasks could detect significant differences in performance between TIA and migraine patients while the MoCA could not. Changes in TIA and migraine performance on the MoCA, TMT, and SST were observed. Conclusions: The robotic KINARM exoskeleton can be used to assess cognitive deficits in TIA patients.