Enhancing Depth Completion with Multi-View Monitored Distillation

This paper presents a novel method for depth completion, which leverages multi-view improved monitored distillation to generate more precise depth maps. Our approach builds upon the state-of-the-art ensemble distillation method, in which we introduce a stereo-based model as a teacher model to improve the accuracy of the student model for depth completion. By minimizing the reconstruction error for a given image during ensemble distillation, we can avoid learning inherent error modes of completion-based teachers. To provide self-supervised information, we also employ multi-view depth consistency and multi-scale minimum reprojection. These techniques utilize existing structural constraints to yield supervised signals for student model training, without requiring costly ground truth depth information. Our extensive experimental evaluation demonstrates that our proposed method significantly improves the accuracy of the baseline monitored distillation method.Comment: 6 pages, 5 figures, references adde

P300 and Motor Imagery Based Brain-Computer Interface for Controlling Wheelchairs 1

This paper proposes a brain-computer interface (BCI) wheelchair that integrates the advantages of event-related potential (ERP) and motor imagery (MI). The ERP, known as P300, is generally used to observe ERP, which is based on visual evocation. For example, users are presented with a screen that flashes possible targets. Users have to focus on the desired target and the result of ERP is recognized as targets and nontargets to control corresponding devices. P300 has the advantages of requiring no initial user training and easy to be observed in a simple and discriminative task Methods 2.1 The Control Scheme. The control scheme of wheelchair is divided into speed control and steering control, as shown in The steering control, which includes left turn and right turn, is activated by investigating the MI-based user's intention. For example, users are required to imagine the movement of kinesthetic of left hand to make a left turn of the wheelchair. When users image the movement of kinesthetic of both hands, the wheelchair is stopped immediately. Like driving, drivers adjust steering frequently to reach the desired positions and to avoid collisions. Because MI has the feature of fast feedback, it is suitable for continuous control commands. In order to achieve high reliability of the recognized result, the stimuli on the screen change according to the current condition of wheelchair. For example, the screen presents "Forward" and "Backward" at the idle state. When the "Forward" condition has been selected, the wheelchair moves with the speed of "Speed 1", and the screen presents "Speed 2" and "Stop" for changing speed and stopping the wheelchair. The bottom of left side of The finite state machine (FSM) is applied to describe the dynamic system with event transitions, as shown in Online Experiments. The online experiments, which involve three subjects, were conducted to validate this system. There are four obstacles arranged in a 7 m  4 m field. Eac

Wireless Stimulus-on-Device Design for Novel P300 Hybrid Brain-Computer Interface Applications

Improving the independent living ability of people who have suffered spinal cord injuries (SCIs) is essential for their quality of life. Brain-computer interfaces (BCIs) provide promising solutions for people with high-level SCIs. This paper proposes a novel and practical P300-based hybrid stimulus-on-device (SoD) BCI architecture for wireless networking applications. Instead of a stimulus-on-panel architecture (SoP), the proposed SoD architecture provides an intuitive control scheme. However, because P300 recognitions rely on the synchronization between stimuli and response potentials, the variation of latency between target stimuli and elicited P300 is a concern when applying a P300-based BCI to wireless applications. In addition, the subject-dependent variation of elicited P300 affects the performance of the BCI. Thus, an adaptive model that determines an appropriate interval for P300 feature extraction was proposed in this paper. Hence, this paper employed the artificial bee colony- (ABC-) based interval type-2 fuzzy logic system (IT2FLS) to deal with the variation of latency between target stimuli and elicited P300 so that the proposed P300-based SoD approach would be feasible. Furthermore, the target and nontarget stimuli were identified in terms of a support vector machine (SVM) classifier. Experimental results showed that, from five subjects, the performance of classification and information transfer rate were improved after calibrations (86.00% and 24.2 bits/ min before calibrations; 90.25% and 27.9 bits/ min after calibrations)

Medulloblastoma Presenting With Pure Word Deafness: Report of One Case and Review of Literature

Pure word deafness (PWD) is a rare disorder characterized by impaired verbal comprehension sparing discrimination and recognition of nonverbal sounds with relatively normal spontaneous speech, writing, and reading comprehension. Etiologies of this syndrome are varied, and there are rare reports about brain tumor with PWD in children. We report a case of medulloblastoma presented with PWD in a 7-year-old girl. She visited our outpatient clinic because of English dictation performance deterioration. PWD was diagnosed by the otolaryngologist after examinations. Posterior fossa tumor and obstructive hydrocephalus were shown in the magnetic resonance imaging of the brain. The diagnosis of medulloblastoma was then made by pathology

Development of a Blood Pressure Measurement Instrument with Active Cuff Pressure Control Schemes

This paper presents an oscillometric blood pressure (BP) measurement approach based on the active control schemes of cuff pressure. Compared with conventional electronic BP instruments, the novelty of the proposed BP measurement approach is to utilize a variable volume chamber which actively and stably alters the cuff pressure during inflating or deflating cycles. The variable volume chamber is operated with a closed-loop pressure control scheme, and it is activated by controlling the piston position of a single-acting cylinder driven by a screw motor. Therefore, the variable volume chamber could significantly eliminate the air turbulence disturbance during the air injection stage when compared to an air pump mechanism. Furthermore, the proposed active BP measurement approach is capable of measuring BP characteristics, including systolic blood pressure (SBP) and diastolic blood pressure (DBP), during the inflating cycle. Two modes of air injection measurement (AIM) and accurate dual-way measurement (ADM) were proposed. According to the healthy subject experiment results, AIM reduced 34.21% and ADM reduced 15.78% of the measurement time when compared to a commercial BP monitor. Furthermore, the ADM performed much consistently (i.e., less standard deviation) in the measurements when compared to a commercial BP monitor

Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation

A high efficient time-shift correlation algorithm was proposed to deal with the peak time uncertainty of P300 evoked potential for a P300-based brain-computer interface (BCI). The time-shift correlation series data were collected as the input nodes of an artificial neural network (ANN), and the classification of four LED visual stimuli was selected as the output node. Two operating modes, including fast-recognition mode (FM) and accuracy-recognition mode (AM), were realized. The proposed BCI system was implemented on an embedded system for commanding an adult-size humanoid robot to evaluate the performance from investigating the ground truth trajectories of the humanoid robot. When the humanoid robot walked in a spacious area, the FM was used to control the robot with a higher information transfer rate (ITR). When the robot walked in a crowded area, the AM was used for high accuracy of recognition to reduce the risk of collision. The experimental results showed that, in 100 trials, the accuracy rate of FM was 87.8% and the average ITR was 52.73 bits/min. In addition, the accuracy rate was improved to 92% for the AM, and the average ITR decreased to 31.27 bits/min. due to strict recognition constraints