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We present a novel human-machine interface, called GOM-Face , and its application to humanoid robot control. The GOM-Face bases its interfacing on three electric potentials measured on the face: 1) glossokinetic potential (GKP), which involves the tongue movement; 2) electrooculogram (EOG), which involves the eye movement; 3) electromyogram, which involves the teeth clenching. Each potential has been individually used for assistive interfacing to provide persons with limb motor disabilities or even complete quadriplegia an alternative communication channel. However, to the best of our knowledge, GOM-Face is the first interface that exploits all these potentials together. We resolved the interference between GKP and EOG by extracting discriminative features from two covariance matrices: a tongue-movement-only data matrix and eye-movement-only data matrix. With the feature extraction method, GOM-Face can detect four kinds of horizontal tongue or eye movements with an accuracy of 86.7% within 2.77 s. We demonstrated the applicability of the GOM-Face to humanoid robot control: users were able to communicate with the robot by selecting from a predefined menu using the eye and tongue movements.

Although several studies have been performed to detect cancer using canine olfaction, none have investigated whether canine olfaction trained to the specific odor of one cancer is able to detect odor related to other unfamiliar cancers. To resolve this issue, we employed breast and colorectal cancer in vitro, and investigated whether trained dogs to odor related to metabolic waste from breast cancer are able to detect it from colorectal cancer, and vice versa. The culture liquid samples used in the cultivation of cancerous cells (4T1 and CT26) were employed as an experimental group. Two different breeds of dogs were trained for the different cancer odor each other. The dogs were then tested using a double-blind method and cross-test to determine whether they could correctly detect the experimental group, which contains the specific odor for metabolic waste of familiar or unfamiliar cancer. For two cancers, both dogs regardless of whether training or non-training showed that accuracy was over 90%, and sensitivity and specificity were over 0.9, respectively. Through these results, it was verified that the superior olfactory ability of dogs can discriminate odor for metabolic waste of cancer cells from it of benign cells, and that the specific odor for metabolic waste of breast cancer has not significant differences to it of colorectal cancer. That is, it testifies that metabolic waste between breast and colorectal cancer have the common specific odor in vitro. Accordingly, a trained dogs for detecting odor for metabolic waste of breast cancer can perceive it of colorectal cancer, and vice versa. In order to the future work, we will plan in vivo experiment for the two cancers and suggest research as to what kind of cancers have the common specific odor. Furthermore, the relationship between breast and colorectal cancer should be investigated using other research methods.

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In this paper we present an immersive brain computer interface (BCI) where we use a virtual reality head-mounted display (VRHMD) to invoke SSVEP responses. Compared to visual stimuli in monitor display, we demonstrate that visual stimuli in VRHMD indeed improve the user engagement for BCI. To this end, we validate our method with experiments on a VR maze game, the goal of which is to guide a ball into the destination in a 2D grid map in a 3D space, successively choosing one of four neighboring cells using SSVEP evoked by visual stimuli on neighboring cells. Experiments indicate that the averaged information transfer rate is improved by 10% for VRHMD, compared to the case in monitor display and the users feel easier to play the game with the proposed system.

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Steady-state somatosensory evoked potential (SSSEP) is a recently developing brain-computer interface (BCI) paradigm where the brain response to tactile stimulation of a specific frequency is used. Generally, SSSEP-based BCI classifies whether the subjects focus on the tactile stimulation at the fingers in the left or right hand. In this paper, we examine the spatial pattern difference in SSSEP from each kind of focuses. The experimental results showed that when the subjects focus to the stimulation at one hand, SSSEP response in the contralateral side decreases. These results could be related to the neurological background, that the sensory cortices for each hand is located in the contra lateral sides of the hands. We also investigate the spatial patterns obtained from common spatial pattern (CSP). In the survey results, the spatial filters, whose corresponding spatial pattern vectors emphasize the left and right parietal lobes, where the somatosensory cortices for each hand are located, made clearly separable clusters of the feature values for each class.