AUTHOR=Cerasa Antonio , Pignolo Loris , Gramigna Vera , Serra Sebastiano , Olivadese Giuseppe , Rocca Federico , Perrotta Paolo , Dolce Giuliano , Quattrone Aldo , Tonin Paolo
TITLE=Exoskeleton-Robot Assisted Therapy in Stroke Patients: A Lesion Mapping Study
JOURNAL=Frontiers in Neuroinformatics
VOLUME=12
YEAR=2018
URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2018.00044
DOI=10.3389/fninf.2018.00044
ISSN=1662-5196
ABSTRACT=Background: Technology-supported rehabilitation is emerging as a solution to support therapists in providing a high-intensity, repetitive and task-specific treatment, aimed at improving stroke recovery. End-effector robotic devices are known to positively affect the recovery of arm functions, however there is a lack of evidence regarding exoskeletons. This paper evaluates the impact of cerebral lesion load on the response to a validated robotic-assisted rehabilitation protocol.
Methods: Fourteen hemiparetic patients were assessed in a within-subject design (age 66.9 ± 11.3 years; 10 men and 4 women). Patients, in post-acute phase, underwent 7 weeks of bilateral arm training assisted by an exoskeleton robot combined with a conventional treatment (consisting of simple physical activity together with occupational therapy). Clinical and neuroimaging evaluations were performed immediately before and after rehabilitation treatments. Fugl-Meyer (FM) and Motricity Index (MI) were selected to measure primary outcomes, i.e., motor function and strength. Functional independance measure (FIM) and Barthel Index were selected to measure secondary outcomes, i.e., daily living activities. Voxel-based lesion symptom mapping (VLSM) was used to determine the degree of cerebral lesions associated with motor recovery.
Results: Robot-assisted rehabilitation was effective in improving upper limb motor function recovery, considering both primary and secondary outcomes. VLSM detected that lesion load in the superior region of the corona radiata, internal capsule and putamen were significantly associated with recovery of the upper limb as defined by the FM scores (p-level < 0.01).
Conclusions: The probability of functional recovery from stroke by means of exoskeleton robotic rehabilitation relies on the integrity of specific subcortical regions involved in the primary motor pathway. This is consistent with previous evidence obtained with conventional neurorehabilitation approaches.