Title :
Multimodal human-humanoid interaction using motions, brain NIRS and spike trains
Author :
Matsuyama, Yasuo ; Ochiai, Nimiko ; Hatakeyama, Takashi ; Noguchi, Keita
Author_Institution :
Dept. of Comput. Sci. & Eng., Waseda Univ., Tokyo, Japan
Abstract :
Heterogeneous bio-signals including human motions, brain NIRS and neural spike trains are utilized for operating biped humanoids. The Bayesian network comprising Hidden Markov Models and Support Vector Machines is designed for the signal integration. By this method, the system complexity is reduced so that that total operation is within the scope of PCs. The designed system is capable of transducing original sensory meaning to another. This leads to prosthesis, rehabilitation and gaming. In addition to the supervised mode, the humanoid can act autonomously for its own designed tasks.
Keywords :
belief networks; brain; control engineering computing; hidden Markov models; human-robot interaction; humanoid robots; legged locomotion; neural nets; Bayesian network; biped humanoids; brain NIRS; gaming; heterogeneous bio-signals; hidden Markov models; human motions; multimodal human-humanoid interaction; neural spike trains; original sensory meaning; prosthesis; rehabilitation; signal integration; support vector machines; system complexity; Bayesian methods; Computer science; Hidden Markov models; Humans; Motion measurement; Neural prosthesis; Personal communication networks; Prosthetics; Signal design; Support vector machines; Brain NIRS; HMM/SVM-Embedded BN; Human-Humanoid Interaction; Motion Recogntion; Multimodal; Neural Spike Train; Non-Verbal; Sensory Transducing;
Conference_Titel :
Human-Robot Interaction (HRI), 2010 5th ACM/IEEE International Conference on
Conference_Location :
Osaka
Print_ISBN :
978-1-4244-4892-0
Electronic_ISBN :
978-1-4244-4893-7
DOI :
10.1109/HRI.2010.5453208
