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Extracting Attempted Hand Movements from EEGs in People with Complete Hand Paralysis Following Stroke.

Muralidharan A, Chae J, Taylor DM - Front Neurosci (2011)

Bottom Line: To reduce inappropriate triggering of a movement-assist device during rest, the classification threshold could be adjusted to require more certainty about one's intent to move before triggering a device.Additionally, a device could be set to activate only after multiple time samples in a row were classified as finger-extension events.These options resulted in some sessions with no false triggers while the person was resting, but moderate-to-high true trigger rates during attempted-movements.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Case Western Reserve University Cleveland, OH, USA.

ABSTRACT
This study examines the feasibility of using electroencephalograms (EEGs) to rapidly detect the intent to open one's hand in individuals with complete hand paralysis following a subcortical ischemic stroke. If detectable, this motor-planning activity could be used in real time to trigger a motorized hand exoskeleton or an electrical stimulation device that opens/closes the hand. While EEG-triggered movement-assist devices could restore function, they may also promote recovery by reinforcing the use of remaining cortical circuits. EEGs were recorded while participants were cued to either relax or attempt to extend their fingers. Linear-discriminant analysis was used to detect onset of finger-extension from the EEGs in a leave-one-trial-out cross-validation process. In each testing trial, the classifier was applied in pseudo-real-time starting from an initial hand-relaxed phase, through movement planning, and into the initial attempted-finger-extension phase (finger-extension phase estimated from typical time-to-movement-onset measured in the unaffected hand). The classifiers detected attempted-finger-extension at a significantly higher rate during both motor-planning and early attempted execution compared to rest. To reduce inappropriate triggering of a movement-assist device during rest, the classification threshold could be adjusted to require more certainty about one's intent to move before triggering a device. Additionally, a device could be set to activate only after multiple time samples in a row were classified as finger-extension events. These options resulted in some sessions with no false triggers while the person was resting, but moderate-to-high true trigger rates during attempted-movements.

No MeSH data available.


Related in: MedlinePlus

Spectrogram from one channel of EEG showing epochs used in the different stages of analysis (red = higher power; blue = lower power). Triangles indicate initial presentation of the hand-open cue and an estimated movement-onset time (median time-to-movement-onset in the unaffected hand). The two gray boxes spanning the spectrogram indicate the two 1-s time segments used in Phase-I of the analysis [i.e., the relaxed (0) and attempted-finger-extension (1) epochs]. Analysis in Phase-II emphasized early detection of attempted-finger-extension during the “movement-preparation” epoch. The lower part of the figure shows how the assigned rest/attempted-finger-extension transition point (0-to-1) was systematically shifted across the movement-preparation epoch in Phase-II as part of the classifier optimization process.
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Figure 1: Spectrogram from one channel of EEG showing epochs used in the different stages of analysis (red = higher power; blue = lower power). Triangles indicate initial presentation of the hand-open cue and an estimated movement-onset time (median time-to-movement-onset in the unaffected hand). The two gray boxes spanning the spectrogram indicate the two 1-s time segments used in Phase-I of the analysis [i.e., the relaxed (0) and attempted-finger-extension (1) epochs]. Analysis in Phase-II emphasized early detection of attempted-finger-extension during the “movement-preparation” epoch. The lower part of the figure shows how the assigned rest/attempted-finger-extension transition point (0-to-1) was systematically shifted across the movement-preparation epoch in Phase-II as part of the classifier optimization process.

Mentions: Classifiers for early detection of attempted-finger-extension were developed in two phases. The goal of the first phase was to identify combinations of specific EEG features that modulate the most with finger-extension. The goal of the second phase was to maximize early detection of movement-onset during motor-planning using the best set of EEG features identified in phase one. These two phases used two distinct epochs of data as described below and illustrated in Figure 1.


Extracting Attempted Hand Movements from EEGs in People with Complete Hand Paralysis Following Stroke.

Muralidharan A, Chae J, Taylor DM - Front Neurosci (2011)

Spectrogram from one channel of EEG showing epochs used in the different stages of analysis (red = higher power; blue = lower power). Triangles indicate initial presentation of the hand-open cue and an estimated movement-onset time (median time-to-movement-onset in the unaffected hand). The two gray boxes spanning the spectrogram indicate the two 1-s time segments used in Phase-I of the analysis [i.e., the relaxed (0) and attempted-finger-extension (1) epochs]. Analysis in Phase-II emphasized early detection of attempted-finger-extension during the “movement-preparation” epoch. The lower part of the figure shows how the assigned rest/attempted-finger-extension transition point (0-to-1) was systematically shifted across the movement-preparation epoch in Phase-II as part of the classifier optimization process.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3066795&req=5

Figure 1: Spectrogram from one channel of EEG showing epochs used in the different stages of analysis (red = higher power; blue = lower power). Triangles indicate initial presentation of the hand-open cue and an estimated movement-onset time (median time-to-movement-onset in the unaffected hand). The two gray boxes spanning the spectrogram indicate the two 1-s time segments used in Phase-I of the analysis [i.e., the relaxed (0) and attempted-finger-extension (1) epochs]. Analysis in Phase-II emphasized early detection of attempted-finger-extension during the “movement-preparation” epoch. The lower part of the figure shows how the assigned rest/attempted-finger-extension transition point (0-to-1) was systematically shifted across the movement-preparation epoch in Phase-II as part of the classifier optimization process.
Mentions: Classifiers for early detection of attempted-finger-extension were developed in two phases. The goal of the first phase was to identify combinations of specific EEG features that modulate the most with finger-extension. The goal of the second phase was to maximize early detection of movement-onset during motor-planning using the best set of EEG features identified in phase one. These two phases used two distinct epochs of data as described below and illustrated in Figure 1.

Bottom Line: To reduce inappropriate triggering of a movement-assist device during rest, the classification threshold could be adjusted to require more certainty about one's intent to move before triggering a device.Additionally, a device could be set to activate only after multiple time samples in a row were classified as finger-extension events.These options resulted in some sessions with no false triggers while the person was resting, but moderate-to-high true trigger rates during attempted-movements.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Case Western Reserve University Cleveland, OH, USA.

ABSTRACT
This study examines the feasibility of using electroencephalograms (EEGs) to rapidly detect the intent to open one's hand in individuals with complete hand paralysis following a subcortical ischemic stroke. If detectable, this motor-planning activity could be used in real time to trigger a motorized hand exoskeleton or an electrical stimulation device that opens/closes the hand. While EEG-triggered movement-assist devices could restore function, they may also promote recovery by reinforcing the use of remaining cortical circuits. EEGs were recorded while participants were cued to either relax or attempt to extend their fingers. Linear-discriminant analysis was used to detect onset of finger-extension from the EEGs in a leave-one-trial-out cross-validation process. In each testing trial, the classifier was applied in pseudo-real-time starting from an initial hand-relaxed phase, through movement planning, and into the initial attempted-finger-extension phase (finger-extension phase estimated from typical time-to-movement-onset measured in the unaffected hand). The classifiers detected attempted-finger-extension at a significantly higher rate during both motor-planning and early attempted execution compared to rest. To reduce inappropriate triggering of a movement-assist device during rest, the classification threshold could be adjusted to require more certainty about one's intent to move before triggering a device. Additionally, a device could be set to activate only after multiple time samples in a row were classified as finger-extension events. These options resulted in some sessions with no false triggers while the person was resting, but moderate-to-high true trigger rates during attempted-movements.

No MeSH data available.


Related in: MedlinePlus