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Session: Poster session II
Session starts: Thursday 24 January, 16:00

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Joost van Kordelaar (TU Delft)
Mark van de Ruit (TU Delft)
Teodoro Solis-Escalante (Radboud UMC)
Leo Aerden (Reinier de Graaf Gasthuis)
Erwin van Wegen (Amsterdam UMC)
Alfred Schouten (TU Delft)
Gert Kwakkel (Amsterdam UMC)
Frans van der Helm (TU Delft)

Abstract:
How much a stroke survivor will recover is still difficult to predict with current prediction models. Information about proprioceptive function may improve these models as it is assumed that proprioception is a prerequisite for regaining motor function. However, objective clinical tests to measure proprioception are currently lacking. Recent studies suggest that the signal-to-noise ratio (SNR) of evoked cortical responses to robotic wrist joint manipulations, as measured with electroencephalography (EEG), may objectively reflect the intactness of proprioceptive pathways to the cortex. The aim of this study was to assess whether this EEG-based metric differs between patients with high (‘recoverers’) and low (‘non-recoverers’) motor recovery. Data from 32 patients was used for the present study. Clinical examinations and EEG measurements took place within the first 3 weeks after stroke and at 5, 12 and 26 weeks. Patients were labelled as ‘recoverer’ (or ‘non-recoverer’) as their recovery on the upper limb section of the Fugl-Meyer Motor Assessment was larger (or smaller) than 50% of the maximal possible improvement on the assessment. EEG recordings were obtained in a customized measurement van with a 64 electrode cap while the wrist angle was manipulated with a haptic robot. Patients were instructed not to exert any force onto the robot (i.e. ‘relax task’). The cortical evoked response at electrode level was quantified by the SNR, which reflects the magnitude of the response relative to the magnitude of background EEG activity. Twenty-two patients were labelled as recoverers and ten as non-recoverers. In the recoverers, the SNR was -16.4 dB in the first and -16.3 dB in the last measurement. In the non-recoverers SNR slightly increased from -18.3 dB to -17.1 dB between the first and last measurements. None of the found changes within and between groups were significant (p > 0.05). The lack of significant differences between groups suggests that the SNR at electrode level does not distinguish between patients with high and low motor recovery after stroke. To improve our methodology we propose to adopt an EEG source localization method in order to identify only the sources that respond to the robotic manipulations and improve SNR specificity.