Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study.
BACKGROUND
The ability to walk independently is a primary goal for rehabilitation after stroke. Gait analysis provides a great amount of valuable information, while functional magnetic resonance imaging (fMRI) offers a powerful approach to define networks involved in motor control. The present study reports a new methodology based on both fMRI and gait analysis outcomes in order to investigate the ability of fMRI to reflect the phases of motor learning before/after electromyographic biofeedback treatment: the preliminary fMRI results of a post stroke subject's brain activation, during passive and active ankle dorsal/plantarflexion, before and after biofeedback (BFB) rehabilitation are reported and their correlation with gait analysis data investigated.


METHODS
A control subject and a post-stroke patient with chronic hemiparesis were studied. Functional magnetic resonance images were acquired during a block-design protocol on both subjects while performing passive and active ankle dorsal/plantarflexion. fMRI and gait analysis were assessed on the patient before and after electromyographic biofeedback rehabilitation treatment during gait activities. Lower limb three-dimensional kinematics, kinetics and surface electromyography were evaluated. Correlation between fMRI and gait analysis categorical variables was assessed: agreement/disagreement was assigned to each variable if the value was in/outside the normative range (gait analysis), or for presence of normal/diffuse/no activation of motor area (fMRI).


RESULTS
Altered fMRI activity was found on the post-stroke patient before biofeedback rehabilitation with respect to the control one. Meanwhile the patient showed a diffuse, but more limited brain activation after treatment (less voxels). The post-stroke gait data showed a trend towards the normal range: speed, stride length, ankle power, and ankle positive work increased. Preliminary correlation analysis revealed that consistent changes were observed both for the fMRI data, and the gait analysis data after treatment (R > 0.89): this could be related to the possible effects BFB might have on the central as well as on the peripheral nervous system.


CONCLUSIONS
Our findings showed that this methodology allows evaluation of the relationship between alterations in gait and brain activation of a post-stroke patient. Such methodology, if applied on a larger sample subjects, could provide information about the specific motor area involved in a rehabilitation treatment.
Silvia
S
Del Din
Alessandra
A
Bertoldo
Department of Information Engineering, University of Padova, Padova, Italy. zimi.sawacha@dei.unipd.it.
Zimi
Z
Sawacha
Johanna
J
Jonsdottir
Marco
M
Rabuffetti
Claudio
C
Cobelli
Maurizio
M
Ferrarin
D001676:Biofeedback, Psychology / Q000379:methods*; D001696:Biomechanical Phenomena; D004576:Electromyography; D005684:Gait; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009044:Motor Cortex / Q000503:physiopathology; D020127:Recovery of Function; D020521:Stroke / Q000503:physiopathology; D000071939:Stroke Rehabilitation