This study aimed to enhance the real-time performance and accuracy of vigilance assessment by developing a hidden Markov model (HMM). Electrocardiogram (ECG) signals were collected and processed to remove noise and baseline drift. A group of 20 volunteers participated in the study. Their heart rate variability (HRV) was measured to train parameters of the modified hidden Markov model for a vigilance assessment. The data were collected to train the model using the Baum–Welch algorithm and to obtain the state transition probability matrix $\widehat{A}$ and the observation probability matrix $\widehat{B}$. Finally, the data of three volunteers with different transition patterns of mental state were selected randomly and the Viterbi algorithm was used to find the optimal state, which was compared with the actual state. The constructed vigilance assessment model had a high accuracy rate, and the accuracy rate of data prediction for these three volunteers exceeded 80%. Our approach can be used in wearable products to improve their vigilance level assessment functionality or in other fields that have key positions with high concentration requirements and monotonous repetitive work.

To study the alteration of cytokine factors in aqueous humor and retinal microstructure in the formation of serous retinal detachment (SRD) secondary to retinal vein occlusion. The subjects were 39 patients with RVO, of whom 31 patients had SRD (RVO-SRD). Spectral Domain Optical Coherence Tomography (SD-OCT) was used to measure the completeness of photoreceptor inner segment/outer segment (IS/OS) and the external limiting membrane (ELM) as well as the structure of RVO-SRD, including the height and shape of SRD. The aqueous humor was collected before intravitreal injection of Ranibizumab. The concentrations of VEGF, MCP-1, IL-8, IL-6, b-FGF and TNF-α in the aqueous humor were measured. All patients participated in the 6-month follow-up examinations, which included visual acuity, intraocular pressure, ophthalmologic examination, and SD-OCT. The time of recurrence of RVO-SRD was recorded. The formation of SRD was associated with the area of congested vein, disrupted IS/OS, ELM layers and high VEGF, MCP-1, IL-8, IL-6 levels. However, the height and shape of SRD were not relevant to any inflammatory factors. Moreover, high levels of MCP-1, IL-8 and IL-6 were found in large areas of congested veins. High levels of MCP-1 and IL-6 were observed in the patients with incomplete IS/OS and ELM. The recurrence of SRD was related to the high MCP-1 level. High concentrations of cytokine factors in aqueous humor could induce vascular leakage, exacerbate the extent of macular edema, disrupt the structure of ELM and IS/OS, and develop SRD in RVO.

Purpose: To determine the response time and protective mechanism of the cyclic guanosine monophosphate (cGMP) channel in 661w cells. Methods: 661w cells were exposed to 4500Lux visible light for three and four days at the following exposure time periods per day: 20, 30, 60, 90, 120, and 180. Cells were incubated for the rest of the time without any other treatment. Cell activity and cell death rates were measured with Hoechst/PI (diphenylmethane/propidium iodide) staining. Western Blot was used to detect the levels of guanylate cyclase-activating proteins 1 (GCAP1), cGMP, and phosphodiesterase (PDE)6 in the cGMP-gated channel. Results: 661w cells showed low mortality within three days. The mortality rate increased from the fourth day, especially during the longer times (120 and 180 min) of light exposure. After three-day illumination, the level of cGMP increased after 20 and 90 min and the level of GCAP1 increased after 60 and 90 min. After four days of illumination, the level of GCAP1 upregulated after a time of 20 and 60 min, while the cGMP level decreased from 30 min. The expression of PDE6 upregulated at each light period. Conclusion: The survival rate of 661w cells was relevant to the time of light exposure. The changes in GCAP1, cGMP, and PDE6 levels over time were possibly related to cell metabolism and restoration after light-induced damage.

Purpose: To construct a hidden Markov model (HMM) for vigilance assessment to improve the real-time performance and accuracy of current vigilance measurement. Methods: ECG signal was collected by sensors, while the noise and baseline drift was eliminated from the original ECG signal. 10 volunteers were randomly selected. Their heart rate variability (HRV) were measured and trained parameters of the modified Hidden Markov model for vigilance assessment. Then, these data were collected to optimize using the Baum-Welch algorithm and obtained the state transition probability matrix A ̂ and the observation probability matrix B ̂. Finally, the data of three volunteers with different transition patterns of mental state were selected randomly and used the Viterbi algorithm to find the optimal state, which compared with the actual state. Results: The constructed vigilance assessment model had a high accuracy rate the accuracy rate of data prediction for these three volunteers exceeded 80%. Conclusion: The Hidden Markov model for vigilance assessment can accurately predict the vigilance level and indicate broad application prospects.