Slim and robust eye tracker on eyeglass temples with NIR patterned mirrors.

Eye trackers play a crucial role in the development of future display systems, such as head-mounted displays and augmented reality glasses. However, ensuring robustness and accuracy in gaze estimation poses challenges, particularly with limited space available for the transmitter and receiver components within these devices. To address the issues, we propose what we believe is a novel eye tracker design mounted on foldable temples, which not only supports accurate gaze estimation but also provides slim form-factor and unobstructed vision. Our temple-mounted eye tracker utilizes a near-infrared imaging system and incorporates a patterned near-infrared mirror for calibration markers. We present wearable prototypes of the eye tracker and introduce a unique calibration and gaze extraction algorithm by considering the mirror's spatial reflectance distribution. The accuracy of gaze extraction is evaluated through tests involving multiple users with realistic scenarios. We conclude with an evaluation of the results and a comprehensive discussion on the applicability of the temple-mounted eye tracker.

A novel rat robot controlled by electrical stimulation of the nigrostriatal pathway.

OBJECTIVE: Artificial manipulation of animal movement could offer interesting advantages and potential applications using the animal's inherited superior sensation and mobility. Although several behavior control models have been introduced, they generally epitomize virtual reward-based training models. In this model, rats are trained multiple times so they can recall the relationship between cues and rewards. It is well known that activation of one side of the nigrostriatal pathway (NSP) in the rat induces immediate turning toward the contralateral side. However, this NSP stimulation-induced directional movement has not been used for the purpose of animal-robot navigation. In this study, the authors aimed to electrically stimulate the NSP of conscious rats to build a command-prompt rat robot. METHODS: Repetitive NSP stimulation at 1-second intervals was applied via implanted electrodes to induce immediate contraversive turning movements in 7 rats in open field tests in the absence of any sensory cues or rewards. The rats were manipulated to navigate from the start arm to a target zone in either the left or right arm of a T-maze. A leftward trial was followed by a rightward trial, and each rat completed a total of 10 trials. In the control group, 7 rats were tested in the same way without NSP stimulation. The time taken to navigate the maze was compared between experimental and control groups. RESULTS: All rats in the experimental group successfully reached the target area for all 70 trials in a short period of time with a short interstimulus interval (< 0.7 seconds), but only 41% of rats in the control group reached the target area and required a longer period of time to do so. The experimental group made correct directional turning movements at the intersection zone of the T-maze, taking significantly less time than the control group. No significant difference in navigation duration for the forward movements on the start and goal arms was observed between the two groups. However, the experimental group showed quick and accurate movement at the intersection zone, which made the difference in the success rate and elapsed time of tasks. CONCLUSIONS: The results of this study clearly indicate that a rat-robot model based on NSP stimulation can be a practical alternative to previously reported models controlled by virtual sensory cues and rewards.

Cross detection for odor of metabolic waste between breast and colorectal cancer using canine olfaction.

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.

Publisher Correction: Manipulation of Rat Movement via Nigrostriatal Stimulation Controlled by Human Visually Evoked Potentials.

A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.

Manipulation of Rat Movement via Nigrostriatal Stimulation Controlled by Human Visually Evoked Potentials.

Here, we report that the development of a brain-to-brain interface (BBI) system that enables a human user to manipulate rat movement without any previous training. In our model, the remotely-guided rats (known as ratbots) successfully navigated a T-maze via contralateral turning behaviour induced by electrical stimulation of the nigrostriatal (NS) pathway by a brain- computer interface (BCI) based on the human controller's steady-state visually evoked potentials (SSVEPs). The system allowed human participants to manipulate rat movement with an average success rate of 82.2% and at an average rat speed of approximately 1.9 m/min. The ratbots had no directional preference, showing average success rates of 81.1% and 83.3% for the left- and right-turning task, respectively. This is the first study to demonstrate the use of NS stimulation for developing a highly stable ratbot that does not require previous training, and is the first instance of a training-free BBI for rat navigation. The results of this study will facilitate the development of borderless communication between human and untrained animals, which could not only improve the understanding of animals in humans, but also allow untrained animals to more effectively provide humans with information obtained with their superior perception.

A hybrid NIRS-EEG system for self-paced brain computer interface with online motor imagery.

BACKGROUND: For a self-paced motor imagery based brain-computer interface (BCI), the system should be able to recognize the occurrence of a motor imagery, as well as the type of the motor imagery. However, because of the difficulty of detecting the occurrence of a motor imagery, general motor imagery based BCI studies have been focusing on the cued motor imagery paradigm. NEW METHOD: In this paper, we present a novel hybrid BCI system that uses near infrared spectroscopy (NIRS) and electroencephalography (EEG) systems together to achieve online self-paced motor imagery based BCI. We designed a unique sensor frame that records NIRS and EEG simultaneously for the realization of our system. Based on this hybrid system, we proposed a novel analysis method that detects the occurrence of a motor imagery with the NIRS system, and classifies its type with the EEG system. RESULTS: An online experiment demonstrated that our hybrid system had a true positive rate of about 88%, a false positive rate of 7% with an average response time of 10.36 s. COMPARISON WITH EXISTING METHOD(S): As far as we know, there is no report that explored hemodynamic brain switch for self-paced motor imagery based BCI with hybrid EEG and NIRS system. CONCLUSIONS: From our experimental results, our hybrid system showed enough reliability for using in a practical self-paced motor imagery based BCI.

GOM-Face: GKP, EOG, and EMG-based multimodal interface with application to humanoid robot control.

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.