PREDICTION OF ARM 3D-TRAJECTORY FROM HUMAN ELECTROCORTICOGRAMS

Yasuhiko Nakanishi, Takafumi Yanagisawa, Duk Shin, Chao Chen, Hiroyuki Kambara, Natsue Yoshimura, Masayuki Hirata, Toshiki Yoshimine, Yasuharu Koike
Abstract:
Electrocorticogram (ECoG), which is less invasive than intracotical microwire, has higher spatiotemporal resolution than EEG. Although a number of studies have predicted three dimensional (3D) trajectories of monkeys’ arm with ECoG signals, those of human arms are not available yet as far as we know. In this study, we applied ECoG to a patient suffering from thalamic hemorrhage and predicted his 3D arm trajectories (4 joint angles and 6 coordinates at arm joints). He performed tasks of rotating three objects clockwise on a table. As results of leave-one-out cross-validation (LOO-CV), average Pearson’s correlation coefficients (CC) and normalized root-mean-square errors (nRMSE) were 0.44 ~ 0.73 and 0.18 ~ 0.42, respectively. We expect that our proposed method can contribute to further research in neuro-prosthesis and neuro-rehabilitation with ECoG signals.
Keywords:
brain machine interface, electrocorticogram, human sensorimotor cortex
Download:
IMEKO-TC18-2013-014.pdf.pdf
DOI:
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Event details
IMEKO TC:
TC18
Event name:
TC18 Symposium 2013
Title:
5th Symposium on Measurement, Analysis and Modeling of Human Functions
Place:
Vancouver, CANADA
Time:
27 June 2013 - 29 June 2013