EEG-Based Attention Assessment in Motor-Rehabilitation |
|---|
| Andrea Apicella, Pasquale Arpaia, Mirco Frosolone, Giovanni Improta, Francesco Isgrò, Nicola Moccaldi, Angela Natalizio |
- Abstract:
- wireless and wearable device with a low number of channels and dry electrodes is proposed for EEG-based attention assessment during motor-rehabilitation tasks. The system is a part of an instrument for real-time engagement assessment in rehabilitation 4.0. An experimental campaign on nine volunteers was realized for metrologically characterizing the system. Common Spatial Pattern (CSP) algorithm was used for features selection from the brain signal. The performance of three different supervised classifiers for distracted and non-distracted conditions were compared. The higher accuracy, 71.63 ± 3.43 %, was obtained by the k-Nearest Neighbors classifier.
- Download:
- IMEKO-TC4-2020-04.pdf
- DOI:
- -