In addition to generating functional limb movement via electrical stimulation, other research proposed lower intensity stimulation for stroke patients from proprioceptive and neuro-biofeedback aspects. This paper investigates the effects of different intensity levels of electrical stimulation during passive cycling on cortical activation using multichannel near infrared spectroscopy (NIRS) covering premotor cortex, supplementary motor area, sensorimotor cortex (SMC), and secondary sensory cortex (S2) regions. Sixteen subjects, including nine stroke patients and seven normal subjects, were instructed to perform passive cycling driven by an ergometer at a pace of 50 rpm under conditions without electrical stimulation (NES) and with low-intensity electrical stimulation (LES) at 10 mA and high-intensity electrical stimulation (HES) at 30 mA. Changes in oxyhemoglobin in different brain regions and the derived interhemispheric correlation coefficient (IHCC) representing the symmetry in response of two hemispheres were evaluated to observe cortical activation and cerebral autoregulation. Our results showed that cortical activation of normal subjects exhibited overall deactivations in HES compared with that under LES and NES. In stroke patients, bilateral S2 activated significantly greater under LES compared with those under NES and HES. The IHCC of the normal group displayed a significant higher value in SMC compared with that of the stroke group. This paper utilized noninvasive NIRS to observe hemodynamic changes and bilateral autoregulation symmetry from IHCC suggesting that passive cycling with LES could better facilitate cortical activation compared with that obtained with NES or HES. The results of this paper could provide general guidelines to simplify the settings of electrical stimulation-assisted-passive cycling in clinical use.
|Number of pages||9|
|Journal||IEEE Transactions on Neural Systems and Rehabilitation Engineering|
|Publication status||Published - 2018 Jun|
All Science Journal Classification (ASJC) codes
- Biomedical Engineering
- Computer Science Applications