title: Decoding fingertip trajectory from electrocorticographic signals in humans.
abstract: Seeking to apply brain-machine interface technology in neuroprosthetics, a number of methods for predicting trajectory of the elbow and wrist have been proposed and have shown remarkable results. Recently, the prediction of hand trajectory and classification of hand gestures or grasping types have attracted considerable attention. However, trajectory prediction for precise finger motion has remained a challenge. We proposed a method for the prediction of fingertip motions from electrocorticographic signals in human cortex. A patient performed extension/flexion tasks with three fingers. Average Pearson's correlation coefficients and normalized root-mean-square errors between decoded and actual trajectories were 0.83-0.90 and 0.24-0.48, respectively. To confirm generalizability to other users, we applied our method to the BCI Competition IV open data sets. Our method showed that the prediction accuracy of fingertip trajectory could be equivalent to that of other results in the competition.
authors.affiliation: Precision and Intelligence Laboratory, Tokyo Institute of Technology, Yokohama 226-8503, Japan.
authors.forename: Yasuhiko
authors.initials: Y
authors.lastname: Nakanishi
authors.affiliation: Department of Neurosurgery, Osaka University Medical School, Osaka 565-0871, Japan; ATR Computational Neuroscience Laboratories, Japan; Division of Functional Diagnostic Science, Osaka University Graduate School of Medicine, Japan.
authors.forename: Takufumi
authors.initials: T
authors.lastname: Yanagisawa
authors.affiliation: Precision and Intelligence Laboratory, Tokyo Institute of Technology, Yokohama 226-8503, Japan. Electronic address: shinduk@cns.pi.titech.ac.jp.
authors.forename: Duk
authors.initials: D
authors.lastname: Shin
authors.affiliation: Precision and Intelligence Laboratory, Tokyo Institute of Technology, Yokohama 226-8503, Japan.
authors.forename: Chao
authors.initials: C
authors.lastname: Chen
authors.affiliation: Precision and Intelligence Laboratory, Tokyo Institute of Technology, Yokohama 226-8503, Japan.
authors.forename: Hiroyuki
authors.initials: H
authors.lastname: Kambara
authors.affiliation: Precision and Intelligence Laboratory, Tokyo Institute of Technology, Yokohama 226-8503, Japan.
authors.forename: Natsue
authors.initials: N
authors.lastname: Yoshimura
authors.affiliation: ATR Computational Neuroscience Laboratories, Japan; Nara Institute of Science and Technology, Nara 630-0192, Japan.
authors.forename: Ryohei
authors.initials: R
authors.lastname: Fukuma
authors.affiliation: Department of Neurosurgery, Osaka University Medical School, Osaka 565-0871, Japan.
authors.forename: Haruhiko
authors.initials: H
authors.lastname: Kishima
authors.affiliation: Department of Neurosurgery, Osaka University Medical School, Osaka 565-0871, Japan.
authors.forename: Masayuki
authors.initials: M
authors.lastname: Hirata
authors.affiliation: Precision and Intelligence Laboratory, Tokyo Institute of Technology, Yokohama 226-8503, Japan.
authors.forename: Yasuharu
authors.initials: Y
authors.lastname: Koike
mesh_terms: D000465:Algorithms; D062207:Brain-Computer Interfaces; D004569:Electroencephalography / Q000379:methods; D004827:Epilepsy / Q000503:physiopathology; D005260:Female; D005385:Fingers / Q000294:innervation / Q000502:physiology*; D006801:Humans; D009068:Movement / Q000502:physiology*; D066191:Sensorimotor Cortex / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
keywords: Brain–machine interface; Electrocorticography; Linear regression; Neuroprosthetics; Sensorimotor cortex; Trajectory prediction