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Improved Detection and Force Decoding through Combined Near-Infrared Spectroscopy and Electroencephalographic Measurements

  • Conference paper

Part of the Biosystems & Biorobotics book series (BIOSYSROB,volume 7)

Abstract

Stroke is the leading cause of acquired disability worldwide. Therefore, several techniques have been suggested for the rehabilitation such as brain-computer interface technology combined with assistive technology. To control the assistive technology, the brain activity should be decoded to determine when the patient intends to initiate a movement, moreover, the kinetic information should be decoded. In this study, electroencephalography (EEG) was recorded simultaneously with near-infrared spectroscopy (NIRS) to determine whether the detection of foot movements and force decoding could be improved using a hybrid approach (combination of EEG and NIRS). Fourteen healthy subjects performed foot movements associated with two levels of force (20 % and 60 % maximum voluntary contraction, MVC) from which subject independent features were extracted and classified using linear discriminant analysis. The detection accuracy was 76 ± 10 % and force decoding was 81 ± 15 % when using the hybrid approach. The performance was on average improved with more than 10 percentage points. It was found that EEG and NIRS were almost as good as the hybrid approach for movement detection and force decoding, respectively. This study showed that BCI performance may be improved with simultaneous recordings of EEG and NIRS.

Keywords

  • Classification Accuracy
  • Linear Discriminant Analysis
  • Maximum Voluntary Contraction
  • Hybrid Approach
  • Movement Detection

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Correspondence to Mia H. Hansen .

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Hansen, M.H., Kassebaum, E., Plocharska, M.A., Jochumsen, M., Kamavuako, E.N. (2014). Improved Detection and Force Decoding through Combined Near-Infrared Spectroscopy and Electroencephalographic Measurements. In: Jensen, W., Andersen, O., Akay, M. (eds) Replace, Repair, Restore, Relieve – Bridging Clinical and Engineering Solutions in Neurorehabilitation. Biosystems & Biorobotics, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-08072-7_63

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  • DOI: https://doi.org/10.1007/978-3-319-08072-7_63

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08071-0

  • Online ISBN: 978-3-319-08072-7

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