Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Detection of movement intention from single-trial movement-related cortical potentials using random and non-random paradigms

Detection of movement intention from single-trial movement-related cortical potentials using... Detection of motor intention with short latency from scalp electroencephalography (EEG) is essential for the development of brain-computer interface (BCI) systems for neuromodulation. This latency determines the temporal association between motor intention and the triggered afferent neurofeedback. In this study, we compared two typical experimental paradigms for the detection of movement intention from EEG. A template-matching algorithm was used to detect movement-related cortical potentials (MRCPs) in eight healthy subjects for two types of cued motor imageries using either a random or non-random cue. For the random cue, the true positive rates of detection of movement intention were 63.5 ± 5.9% (foot movement) and 61 ± 6.5% (right hand movement). Detection occurred 102.8 ± 119.3 ms and 112.2 ± 104 ms prior to onset of execution cue. On the other hand, foot and hand movement intentions were detected significantly earlier (p < 0.05) (198 ± 147.3 ms and 206 ± 134.2 ms prior to onset, respectively) and with a greater true positive rate (p < 0.05) (75.3 ± 5.5% and 70.2 ± 6.1%) when non-random cues were used. These results suggest that a non-random cue paradigm is preferable to a typical random cue in BCI systems designed for neuromodulation. However, the important consideration of variable practice afforded by the random cue, which is known to facilitate learning, requires further study. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Brain-Computer Interfaces Taylor & Francis

Detection of movement intention from single-trial movement-related cortical potentials using random and non-random paradigms

Detection of movement intention from single-trial movement-related cortical potentials using random and non-random paradigms

Brain-Computer Interfaces , Volume 2 (1): 11 – Jan 2, 2015

Abstract

Detection of motor intention with short latency from scalp electroencephalography (EEG) is essential for the development of brain-computer interface (BCI) systems for neuromodulation. This latency determines the temporal association between motor intention and the triggered afferent neurofeedback. In this study, we compared two typical experimental paradigms for the detection of movement intention from EEG. A template-matching algorithm was used to detect movement-related cortical potentials (MRCPs) in eight healthy subjects for two types of cued motor imageries using either a random or non-random cue. For the random cue, the true positive rates of detection of movement intention were 63.5 ± 5.9% (foot movement) and 61 ± 6.5% (right hand movement). Detection occurred 102.8 ± 119.3 ms and 112.2 ± 104 ms prior to onset of execution cue. On the other hand, foot and hand movement intentions were detected significantly earlier (p < 0.05) (198 ± 147.3 ms and 206 ± 134.2 ms prior to onset, respectively) and with a greater true positive rate (p < 0.05) (75.3 ± 5.5% and 70.2 ± 6.1%) when non-random cues were used. These results suggest that a non-random cue paradigm is preferable to a typical random cue in BCI systems designed for neuromodulation. However, the important consideration of variable practice afforded by the random cue, which is known to facilitate learning, requires further study.

Loading next page...
 
/lp/taylor-francis/detection-of-movement-intention-from-single-trial-movement-related-L751IvXFj0

References (35)

Publisher
Taylor & Francis
Copyright
© 2015 Taylor & Francis
ISSN
2326-2621
eISSN
2326-263x
DOI
10.1080/2326263X.2015.1053301
Publisher site
See Article on Publisher Site

Abstract

Detection of motor intention with short latency from scalp electroencephalography (EEG) is essential for the development of brain-computer interface (BCI) systems for neuromodulation. This latency determines the temporal association between motor intention and the triggered afferent neurofeedback. In this study, we compared two typical experimental paradigms for the detection of movement intention from EEG. A template-matching algorithm was used to detect movement-related cortical potentials (MRCPs) in eight healthy subjects for two types of cued motor imageries using either a random or non-random cue. For the random cue, the true positive rates of detection of movement intention were 63.5 ± 5.9% (foot movement) and 61 ± 6.5% (right hand movement). Detection occurred 102.8 ± 119.3 ms and 112.2 ± 104 ms prior to onset of execution cue. On the other hand, foot and hand movement intentions were detected significantly earlier (p < 0.05) (198 ± 147.3 ms and 206 ± 134.2 ms prior to onset, respectively) and with a greater true positive rate (p < 0.05) (75.3 ± 5.5% and 70.2 ± 6.1%) when non-random cues were used. These results suggest that a non-random cue paradigm is preferable to a typical random cue in BCI systems designed for neuromodulation. However, the important consideration of variable practice afforded by the random cue, which is known to facilitate learning, requires further study.

Journal

Brain-Computer InterfacesTaylor & Francis

Published: Jan 2, 2015

Keywords: brain computer interface; movement detection; movement-related cortical potential; random paradigm; non-random paradigm

There are no references for this article.