Recently, practical brain-computer interface is actively carried out, especially, in an ambulatory environment.However, the electroencephalography signals are distorted by movement artifacts and electromyography signals in ambulatory condition, which make hard to recognize human intention.In addition, as hardware issues are also challenging, ear-EEG has been developed for practical brain-computer interface and is widely used.However, ear-EEG still contains contaminated signals.In this paper, we proposed robust two-stream deep neural networks in walking conditions and analyzed the visual response EEG signals in the scalp and ear in terms of statistical analysis and braincomputer interface performance.We validated the signals with the visual response paradigm, steady-state visual evoked potential.The brain-computer interface performance deteriorated as 3~14% when walking fast at 1.6 m/s.When applying the proposed method, the accuracies increase 15% in cap-EEG and 7% in ear-EEG.The proposed method shows robust to the ambulatory condition in session dependent and session-to-session experiments.
Purpose: To evaluate the accuracy of intraocular lens (IOL) power calculations according to the chosen formulas and anterior chamber depths in eyes with short axial lengths. Methods: A retrospective analysis was performed on 57 eyes of 50 patients (axial length axial length
【Purpose: This study was conducted to discover the related factors of neonatal suckling in the initiation of breastfeeding in primiparous mothers and to provide basic data for promoting nursing intervention strategies to improve the practice of breastfeeding. Method: The subjects of this study were 71 primiparous mothers who had normal vaginal deliveries at one obstetric hospital in P metropolitan city and one delivery center in J city. The collected data was analyzed using the SPSS program. Result: The average IBFAT(Infant Breastfeeding Assessment Tool) score was 9.6 $\pm$ 2.3. The general characteristics studied that had a significant influence on neonatal suckling in the initiation of breastfeeding were the place of delivery (ex: Hospital, Postnatal Unit), whether oxytocin was used, no usage of analgesic medication, amount of satisfaction after the first breastfeeding weight of the newborns and the Apgar score at one minute. Conclusions: A higher IBFAT score was related to primiparous mothers who had a hospital delivery, received oxytocin, received maternal labour analgesics, neonatal weight, Apgar score at one minute, and satisfaction after the first breastfeeding.】
The steady-state visually evoked potential (SSVEP) is a natural response of the brain to visual stimulation at specific frequencies and is used widely for electroencephalography-based brain–computer interface (BCI) systems. Although the SSVEP is useful for its high level of decoding accuracy, visual fatigue from the repetitive visual flickering is an unavoidable problem. In addition, hybrid BCI systems that combine the SSVEP with the event-related potential (ERP) have been proposed recently. These hybrid BCI systems would improve the decoding accuracy; however, the competing effect by simultaneous presentation of the visual stimulus could possibly supervene the signal in the hybrid system. Nevertheless, previous studies have not sufficiently reported these problems of visual fatigue with SSVEP stimuli or the competing effect in the SSVEP+ERP system. In this study, two different experiments were designed to explore our claims. The first experiment evaluated the visual fatigue level and decoding accuracy for the different types of SSVEP stimuli, which were the peripheral-field SSVEP (pSSVEP) and the central-field SSVEP (cSSVEP). We report that the pSSVEP could reduce the visual fatigue level by avoiding direct exposure of the eye-retina to the flickering visual stimulus, while also delivering a decoding accuracy comparable to that of cSSVEP. The second experiment was designed to examine the competing effect of the SSVEP stimuli on ERP performance and vice versa. To do this, the visual stimuli of ERP and SSVEP were presented simultaneously as part of the BCI speller layout. We found a clear competing effect wherein the evoked brain potentials were influenced by the SSVEP stimulus and the band power at the target frequencies was also decreased significantly by the ERP stimuli. Nevertheless, these competing effects did not lead to a significant loss in decoding accuracy; their features preserved sufficient information for discriminating a target class. Our work is the first to evaluate the visual fatigue and competing effect together, which should be considered when designing BCI applications. Furthermore, our findings suggest that the pSSVEP is a viable substitution for the cSSVEP because of its ability to reduce the level of visual fatigue while maintaining a minimal loss of decoding accuracy.
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