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Detecting the Intention to Move Upper Limbs from Electroencephalographic Brain Signals.

Gudiño-Mendoza B, Sanchez-Ante G, Antelis JM - Comput Math Methods Med (2016)

Bottom Line: The analysis of these EEG traces showed that significant event-related desynchronization is present before and during the execution of the movements, predominantly in the motor-related α and β frequency bands and in electrodes placed above the motor cortex.This oscillatory brain activity was used to continuously detect the intention to move the limbs, that is, to identify the motor phase prior to the actual execution of the reaching movement.The results showed, first, significant classification between relax and movement intention and, second, significant detection of movement intention prior to the onset of the executed movement.

View Article: PubMed Central - PubMed

Affiliation: Tecnologico de Monterrey, Campus Guadalajara, Avenida General Ramón Corona 2514, 45201 Zapopan, JAL, Mexico.

ABSTRACT
Early decoding of motor states directly from the brain activity is essential to develop brain-machine interfaces (BMI) for natural motor control of neuroprosthetic devices. Hence, this study aimed to investigate the detection of movement information before the actual movement occurs. This information piece could be useful to provide early control signals to drive BMI-based rehabilitation and motor assisted devices, thus providing a natural and active rehabilitation therapy. In this work, electroencephalographic (EEG) brain signals from six healthy right-handed participants were recorded during self-initiated reaching movements of the upper limbs. The analysis of these EEG traces showed that significant event-related desynchronization is present before and during the execution of the movements, predominantly in the motor-related α and β frequency bands and in electrodes placed above the motor cortex. This oscillatory brain activity was used to continuously detect the intention to move the limbs, that is, to identify the motor phase prior to the actual execution of the reaching movement. The results showed, first, significant classification between relax and movement intention and, second, significant detection of movement intention prior to the onset of the executed movement. On the basis of these results, detection of movement intention could be used in BMI settings to reduce the gap between mental motor processes and the actual movement performed by an assisted or rehabilitation robotic device.

No MeSH data available.


Related in: MedlinePlus

Significant event-related desynchronization/synchronization activity computed for all trials and subjects. Horizontal axis represents time (units of s) while vertical axis represents frequency (units of Hz). Solid black lines in all graphs represent t = 0 s or the movement onset. Significant desynchronization (p < 0.05) is observed in all sensors in the motor-related α[8,13] Hz and β[14,30] Hz frequency bands from t ≈ −1.5 s, while no significant desynchronization or synchronization (p > 0.05) is observed before t ≈ −1.5 s.
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fig3: Significant event-related desynchronization/synchronization activity computed for all trials and subjects. Horizontal axis represents time (units of s) while vertical axis represents frequency (units of Hz). Solid black lines in all graphs represent t = 0 s or the movement onset. Significant desynchronization (p < 0.05) is observed in all sensors in the motor-related α[8,13] Hz and β[14,30] Hz frequency bands from t ≈ −1.5 s, while no significant desynchronization or synchronization (p > 0.05) is observed before t ≈ −1.5 s.

Mentions: The significant activity of event-related desynchronization/synchronization computed across all trials and subjects is presented in Figure 3. Significant desynchronization (p < 0.05) is observed in all sensors and in the motor-related α[8, 13] Hz and β[14, 30] Hz frequency bands around the movement onset t = 0 s. This significant desynchronization starts in the movement intention phase roughly at 1 s prior to the movement onset and remains significant up to the movement execution interval t ≥ 0. No significant desynchronization or synchronization (p > 0.05) is observed before ≈−1 s. Note that the significant desynchronization is uniformly distributed in all sensors and in both hemispheres; that is, no spatial pattern of desynchronization/synchronization is observed across the motor cortex.


Detecting the Intention to Move Upper Limbs from Electroencephalographic Brain Signals.

Gudiño-Mendoza B, Sanchez-Ante G, Antelis JM - Comput Math Methods Med (2016)

Significant event-related desynchronization/synchronization activity computed for all trials and subjects. Horizontal axis represents time (units of s) while vertical axis represents frequency (units of Hz). Solid black lines in all graphs represent t = 0 s or the movement onset. Significant desynchronization (p < 0.05) is observed in all sensors in the motor-related α[8,13] Hz and β[14,30] Hz frequency bands from t ≈ −1.5 s, while no significant desynchronization or synchronization (p > 0.05) is observed before t ≈ −1.5 s.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4863091&req=5

fig3: Significant event-related desynchronization/synchronization activity computed for all trials and subjects. Horizontal axis represents time (units of s) while vertical axis represents frequency (units of Hz). Solid black lines in all graphs represent t = 0 s or the movement onset. Significant desynchronization (p < 0.05) is observed in all sensors in the motor-related α[8,13] Hz and β[14,30] Hz frequency bands from t ≈ −1.5 s, while no significant desynchronization or synchronization (p > 0.05) is observed before t ≈ −1.5 s.
Mentions: The significant activity of event-related desynchronization/synchronization computed across all trials and subjects is presented in Figure 3. Significant desynchronization (p < 0.05) is observed in all sensors and in the motor-related α[8, 13] Hz and β[14, 30] Hz frequency bands around the movement onset t = 0 s. This significant desynchronization starts in the movement intention phase roughly at 1 s prior to the movement onset and remains significant up to the movement execution interval t ≥ 0. No significant desynchronization or synchronization (p > 0.05) is observed before ≈−1 s. Note that the significant desynchronization is uniformly distributed in all sensors and in both hemispheres; that is, no spatial pattern of desynchronization/synchronization is observed across the motor cortex.

Bottom Line: The analysis of these EEG traces showed that significant event-related desynchronization is present before and during the execution of the movements, predominantly in the motor-related α and β frequency bands and in electrodes placed above the motor cortex.This oscillatory brain activity was used to continuously detect the intention to move the limbs, that is, to identify the motor phase prior to the actual execution of the reaching movement.The results showed, first, significant classification between relax and movement intention and, second, significant detection of movement intention prior to the onset of the executed movement.

View Article: PubMed Central - PubMed

Affiliation: Tecnologico de Monterrey, Campus Guadalajara, Avenida General Ramón Corona 2514, 45201 Zapopan, JAL, Mexico.

ABSTRACT
Early decoding of motor states directly from the brain activity is essential to develop brain-machine interfaces (BMI) for natural motor control of neuroprosthetic devices. Hence, this study aimed to investigate the detection of movement information before the actual movement occurs. This information piece could be useful to provide early control signals to drive BMI-based rehabilitation and motor assisted devices, thus providing a natural and active rehabilitation therapy. In this work, electroencephalographic (EEG) brain signals from six healthy right-handed participants were recorded during self-initiated reaching movements of the upper limbs. The analysis of these EEG traces showed that significant event-related desynchronization is present before and during the execution of the movements, predominantly in the motor-related α and β frequency bands and in electrodes placed above the motor cortex. This oscillatory brain activity was used to continuously detect the intention to move the limbs, that is, to identify the motor phase prior to the actual execution of the reaching movement. The results showed, first, significant classification between relax and movement intention and, second, significant detection of movement intention prior to the onset of the executed movement. On the basis of these results, detection of movement intention could be used in BMI settings to reduce the gap between mental motor processes and the actual movement performed by an assisted or rehabilitation robotic device.

No MeSH data available.


Related in: MedlinePlus