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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

Adjusted true-positive rate as a function of false-positive rate. Adjusted true-positive rate was calculated as the true-positive rates during the motor-planning epoch minus the false-positive rate during the relaxed epoch. Boxes indicate 25, 50, and 75% quartiles respectively. (A) Duration of the motor-planning epoch was estimated using the median time-to-movement-onset of the unaffected hand. (B) Estimate of the duration of the motor-planning epoch was expanded by 200, 400, or 600 ms (results for optimal expansion plotted).
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Figure 2: Adjusted true-positive rate as a function of false-positive rate. Adjusted true-positive rate was calculated as the true-positive rates during the motor-planning epoch minus the false-positive rate during the relaxed epoch. Boxes indicate 25, 50, and 75% quartiles respectively. (A) Duration of the motor-planning epoch was estimated using the median time-to-movement-onset of the unaffected hand. (B) Estimate of the duration of the motor-planning epoch was expanded by 200, 400, or 600 ms (results for optimal expansion plotted).

Mentions: Figure 2A shows the adjusted true-positive rate (true-positive rate minus false-positive rate) at the default threshold and when the threshold was adjusted to achieve the different predefined false-positive rates. By design, the default threshold setting determined by linear-discriminant analysis maximizes the difference between the two classification states. However, the default threshold generally resulted in relatively high false-positive rates (22 ± 9%). Adjusting the classification thresholds to achieve a lower false-positive rate typically reduced the difference between the true- and false-positive rates. While each participant had a significant difference between their true- and the false-positive rate each day when the default threshold was used (P-values ranged from 8 × 10−6 to 4 × 10−13), shifting the classifier threshold to achieve the lower false-positive rates in some cases reduced the difference between the true- and false-positive rates to a non-significant level. Note in Figure 2, false-positive rates have already been subtracted out making the chance level zero in all cases. The increase in adjusted true-positive rates at higher false-positive thresholds indicating that allowing some false-positives can pay off by disproportionately increasing the adjusted true-positive rate.


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

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

Adjusted true-positive rate as a function of false-positive rate. Adjusted true-positive rate was calculated as the true-positive rates during the motor-planning epoch minus the false-positive rate during the relaxed epoch. Boxes indicate 25, 50, and 75% quartiles respectively. (A) Duration of the motor-planning epoch was estimated using the median time-to-movement-onset of the unaffected hand. (B) Estimate of the duration of the motor-planning epoch was expanded by 200, 400, or 600 ms (results for optimal expansion plotted).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: Adjusted true-positive rate as a function of false-positive rate. Adjusted true-positive rate was calculated as the true-positive rates during the motor-planning epoch minus the false-positive rate during the relaxed epoch. Boxes indicate 25, 50, and 75% quartiles respectively. (A) Duration of the motor-planning epoch was estimated using the median time-to-movement-onset of the unaffected hand. (B) Estimate of the duration of the motor-planning epoch was expanded by 200, 400, or 600 ms (results for optimal expansion plotted).
Mentions: Figure 2A shows the adjusted true-positive rate (true-positive rate minus false-positive rate) at the default threshold and when the threshold was adjusted to achieve the different predefined false-positive rates. By design, the default threshold setting determined by linear-discriminant analysis maximizes the difference between the two classification states. However, the default threshold generally resulted in relatively high false-positive rates (22 ± 9%). Adjusting the classification thresholds to achieve a lower false-positive rate typically reduced the difference between the true- and false-positive rates. While each participant had a significant difference between their true- and the false-positive rate each day when the default threshold was used (P-values ranged from 8 × 10−6 to 4 × 10−13), shifting the classifier threshold to achieve the lower false-positive rates in some cases reduced the difference between the true- and false-positive rates to a non-significant level. Note in Figure 2, false-positive rates have already been subtracted out making the chance level zero in all cases. The increase in adjusted true-positive rates at higher false-positive thresholds indicating that allowing some false-positives can pay off by disproportionately increasing the adjusted true-positive rate.

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