DocumentCode :
2095401
Title :
Self-paced movement intention detection from human brain signals: Invasive and non-invasive EEG
Author :
Lew, E. ; Chavarriaga, Ricardo ; Huaijian Zhang ; Seeck, M. ; del Millan, J.R.
Author_Institution :
Center for Neuroprosthetics, Swiss Fed. Inst. of Technol. Lausanne (EPFL), Lausanne, Switzerland
fYear :
2012
fDate :
Aug. 28 2012-Sept. 1 2012
Firstpage :
3280
Lastpage :
3283
Abstract :
Neural signatures of humans´ movement intention can be exploited by future neuroprosthesis. We propose a method for detecting self-paced upper limb movement intention from brain signals acquired with both invasive and non-invasive methods. In the first study with scalp electroencephalograph (EEG) signals from healthy controls, we report single trial detection of movement intention using movement-related potentials (MRPs) in a frequency range between 0.1 to 1 Hz. Movement intention can be detected above chance level (p<;0.05) on average 460 ms before the movement onset with low detection rate during the non-movement intention period. Using intracranial EEG (iEEG) from one epileptic subject, we detect movement intention as early as 1500 ms before movement onset with accuracy above 90% using electrodes implanted in the bilateral supplementary motor area (SMA). The coherent results obtained with non-invasive and invasive method and its generalization capabilities across different days of recording, strengthened the theory that self-paced movement intention can be detected before movement initiation for the advancement in robot-assisted neurorehabilitation.
Keywords :
biomechanics; electroencephalography; medical signal detection; patient rehabilitation; MRP; SMA; bilateral supplementary motor area; epileptic subject; frequency 0.1 Hz to 1 Hz; human brain signals; human movement intention; iEEG; intracranial EEG; movement-related potentials; neural signatures; neuroprosthesis; non-invasive EEG; non-invasive methods; robot-assisted neurorehabilitation; scalp electroencephalograph signals; self-paced movement intention detection; self-paced upper limb movement intention; Electric potential; Electrodes; Electroencephalography; Electromyography; Humans; Materials requirements planning; Scalp; Adult; Brain; Electroencephalography; Epilepsy; Evoked Potentials; Female; Humans; Male; Movement; Reference Values; Signal Processing, Computer-Assisted;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2012.6346665
Filename :
6346665
Link To Document :
بازگشت