Gait-combined closed-loop brain stimulation can improve walking dynamics in Parkinsonian gait disturbances: a randomised-control trial

Author:

Nojima IppeiORCID,Horiba Mitsuya,Sahashi Kento,Koganemaru Satoko,Murakami Satona,Aoyama Kiminori,Matsukawa Noriyuki,Ono Yumie,Mima TatsuyaORCID,Ueki Yoshino

Abstract

ObjectiveGait disturbance lowers activities of daily living in patients with Parkinson’s disease (PD) and related disorders. However, the effectiveness of pharmacological, surgical and rehabilitative treatments is limited. We recently developed a novel neuromodulation approach using gait-combined closed-loop transcranial electrical stimulation (tES) for healthy volunteers and patients who are post-stroke, and achieved significant entrainment of gait rhythm and an increase in gait speed. Here, we tested the efficacy of this intervention in patients with Parkinsonian gait disturbances.MethodsTwenty-three patients were randomly assigned to a real intervention group using gait-combined closed-loop oscillatory tES over the cerebellum at the frequency of individualised comfortable gait rhythm, and to a sham control group.ResultsTen intervention sessions were completed for all patients and showed that the gait speed (F(1, 21)=13.0, p=0.002) and stride length (F(1, 21)=8.9, p=0.007) were significantly increased after tES, but not after sham stimulation. Moreover, gait symmetry measured by swing phase time (F(1, 21)=11.9, p=0.002) and subjective feelings about freezing (F(1, 21)=14.9, p=0.001) were significantly improved during gait.ConclusionsThese findings showed that gait-combined closed-loop tES over the cerebellum improved Parkinsonian gait disturbances, possibly through the modulation of brain networks generating gait rhythms. This new non-pharmacological and non-invasive intervention could be a breakthrough in restoring gait function in patients with PD and related disorders.

Funder

Japan Society for the Promotion of Science

Publisher

BMJ

Subject

Psychiatry and Mental health,Neurology (clinical),Surgery

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