Classification of hand posture from electrocorticographic signals recorded during varying force conditions
In the presented work, standard and high-density electrocorticographic (ECoG) electrodes were used to record cortical field potentials in three human subjects during a hand posture task requiring the application of specific levels of force during grasping. We show two-class classification accuracies...
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| Veröffentlicht in: | 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2011-01, Vol.2011, p.5782-5785 |
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| container_title | 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
| container_volume | 2011 |
| creator | Degenhart, A. D. Collinger, J. L. Vinjamuri, R. Kelly, J. W. Tyler-Kabara, E. C. Wei Wang |
| description | In the presented work, standard and high-density electrocorticographic (ECoG) electrodes were used to record cortical field potentials in three human subjects during a hand posture task requiring the application of specific levels of force during grasping. We show two-class classification accuracies of up to 80% are obtained when classifying between two-finger pinch and whole-hand grasp hand postures despite differences in applied force levels across trials. Furthermore, we show that a four-class classification accuracy of 50% is achieved when predicting both hand posture and force level during a two-force, two-hand-posture grasping task, with hand posture most reliably predicted during high-force trials. These results suggest that the application of force plays a significant role in ECoG signal modulation observed during motor tasks, emphasizing the potential for electrocorticography to serve as a source of control signals for dexterous neuroprosthetic devices. |
| doi_str_mv | 10.1109/IEMBS.2011.6091431 |
| format | Article |
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These results suggest that the application of force plays a significant role in ECoG signal modulation observed during motor tasks, emphasizing the potential for electrocorticography to serve as a source of control signals for dexterous neuroprosthetic devices.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Electrodes</subject><subject>Electroencephalography - methods</subject><subject>Force</subject><subject>Hand - physiology</subject><subject>Hand Strength - physiology</subject><subject>Humans</subject><subject>Modulation</subject><subject>Motor Cortex - physiology</subject><subject>Muscle Contraction - physiology</subject><subject>Muscle Strength - physiology</subject><subject>Muscle, Skeletal - physiology</subject><subject>Physical Exertion - physiology</subject><subject>Posture - physiology</subject><subject>Prosthetics</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Time frequency analysis</subject><issn>1094-687X</issn><issn>1558-4615</issn><issn>2694-0604</issn><isbn>9781424441211</isbn><isbn>1424441218</isbn><isbn>1424441226</isbn><isbn>1457715899</isbn><isbn>9781457715891</isbn><isbn>9781424441228</isbn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNo9kNtOAjEQhuspgsgLaGL6Aoudnnb3UggqCcYLNfGOdNsulMB20y4mvr0lgHPzX3xf_swMQndARgCkfJxN38YfI0oARpKUwBmcoRvglHMOlMpz1AchioxLEBdoWObFiQFcJkZKnski_-6hYYxrkkbKkjF6jXqUUiGk4H20nmxUjK52WnXON9jXeKUag1sfu12wuA5-i-3G6i547UPntF8G1a6cxtEtG7WJONgEjDXY7IJrlvhHhd991j5oi7VvjNtXx1t0VSffDo85QF_P08_JazZ_f5lNnuaZY1J2mZVGsCpnUBEpKiZMqQptNKNapf2VzZOguCTCQG2LmlFgIqeSghQq16piA_Rw6G131daaRRvcNq20OB2dhPuD4Ky1__j4YvYHeB9rJw</recordid><startdate>20110101</startdate><enddate>20110101</enddate><creator>Degenhart, A. 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| identifier | ISSN: 1094-687X |
| ispartof | 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011-01, Vol.2011, p.5782-5785 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Accuracy Algorithms Electrodes Electroencephalography - methods Force Hand - physiology Hand Strength - physiology Humans Modulation Motor Cortex - physiology Muscle Contraction - physiology Muscle Strength - physiology Muscle, Skeletal - physiology Physical Exertion - physiology Posture - physiology Prosthetics Reproducibility of Results Sensitivity and Specificity Time frequency analysis |
| title | Classification of hand posture from electrocorticographic signals recorded during varying force conditions |
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