Blink Research Articles

Normative values of the nociceptive blink reflex habituation

Introduction: Habituation is a physiological phenomenon, characterized by response reduction to repeated stimulus presentation. In headache disorders, habituation studies have involved different paradigms with several stimulation parameters and sensory modalities, and consistently showed impaired habituation in primary headaches in the interictal phase. The nociceptive blink reflex (nBR) and its related R2 response, modulated by a polysynaptic network in the trigeminocervical complex, is one of the most studied in the field. The lack of nBR habituation normative data hampered the possibility to draw conclusions regarding the functional status of individual patients. The present study aims to define normative values for the nBR habituation process in healthy subjects without a personal diagnosis and family history of migraine, or other headache disorders.Methods: We enrolled 40 healthy subjects (24 females, 32.7±11.6 years) for nBR recording and nBR habituation assessment. To assess the habituation of nBR, 26 consecutive stimuli were administered at three different and randomized stimulus frequencies (0.2, 0.3, 0.5 Hz). After excluding the first response, the remaining 25 area under the curve (AUC) were divided in 5 blocks, and the average values of the AUC was calculated for each block. The percentage reduction in the AUC of the fifth block, compared to the first, represents the habituation index (HI) value. We considered a one-tailed 10th percentile threshold as the lower threshold of normative values for nBR HI.Results: The habituation phenomenon was confirmed for all study frequencies. The absolute AUC of the R2 component across the five blocks of stimulation was higher in female subjects when compared to male for 0.5 Hz (p=0.021) and 0.2 Hz (p=0.007). We found a frequency-dependent habituation pattern, being lower at the 0.2 Hz stimulation when compared to 0.5 Hz (p=0.001), and 0.3 Hz (p=0.008). The average HIs were 73.1±13.6 at 0.5 Hz, 69.2±15.0 at 0.3 Hz, and 61.1±21.4 at 0.2 Hz. HIs were comparable between male and female subjects, without correlations with age, intensity of stimulation, and latency of the R2 component. The 10th percentile of the HIs was 43.5% for 0.5 Hz, 55.8% for 0.3 Hz, and 28.6% for 0.2 Hz.Conclusions: We investigated the nBR habituation in a population of healthy subjects for normative data collection. We described a frequency- dependent degree of habituation, being more pronounced at higher frequencies of stimulation. Moreover, we described gender-related features of response behaviour, which is extremely important in the migraine field. Our study further characterized the physiological habituation phenomenon in healthy controls exposed to a nociceptive stimulation. The definition of a normative habituation value will open novel possibilities in the study of migraine, as well as other headache and pain disorders.

Analysis of Factors Associated with Anterior Location of Marx’s Line

Purpose The study aimed to investigate the factors associated with anterior location of Marx’s line in ocular surface and living habits, especially in tear film. Materials and methods This cross-sectional study enlisted 483 participants with meibomian gland dysfunction, who were divided into two groups: 160 participants with mild anterior location of Marx’s line and 323 participants with moderate-to-severe anterior location. Participants completed a survey of demographic characteristics (sex, age, length of visual terminal use, sleep duration, skin property), and the Ocular Surface Disease Index and Standard Patient Evaluation of Eye Dryness questionnaires. They also underwent slit-lamp examinations of the lids, and measurements of non-invasive tear break up time, tear meniscus height, fluorescein tear break up time, lipid layer thickness, partial blink rate, lid wiper epitheliopathy, and meibomian gland dropout. Results The tear meniscus height (mild:0.21(0.18–0.25), moderate-to-severe:0.19(0.16–0.23), p = 0.004), fluorescein tear break up time(mild:3(2–4),moderate to severe:2(1–3), p = 0.000), max LLT(mild:87(62–100), moderate-to-severe:99(69–100), p = 0.04), average LLT(mild:64.5(47.5–96.75), moderate-to-severe:74(53–100), p = 0.012), min LLT(mild:52(38–75), moderate-to-severe:59(41–85), p = 0.029) differed significantly between mild and moderate-to-severe anterior location of Marx’s line, and associated to the anterior location of Marx’s line(r=-0.134, p = 0.03; r=-0.194, p = 0.000; r = 0.093, p = 0.041; r = 0.119, p = 0.009; r = 0.105, p = 0.022) However, no statistical significance was observed in the OSDI, SPEED, partial blink rate, non-invasive tear breakup time, lipid layer thickness, meibomian gland dropout and lid wiper epitheliopathy(p > 0.05). Meanwhile, in the demographic characteristics, statistically significant correlations were associated with skin property(r = 0.154, p = 0.001) and sleep duration(r=-0.124, p = 0.006), but not with age, sex, and the length of visual terminal use (p > 0.05). Conclusions Lower TMH and shorter TBUT positively correlated with anterior location of the Marx’s line, and were risk factors. Meanwhile, participants with oily skin and shorter sleep duration were more likely to exhibit anterior location of Marx’s line.

Orbital Structure Involvement in Midface Fractures Impacting Ocular Injury at a Tertiary Hospital in Eastern Indonesia

ABSTRACT Introduction: The midface is a complex anatomical area consisting of several areas. Although various factors protect the eye from trauma, such as orbital rim, blink reflex, elasticity of ocular structures, and protective eye movements by hands and head, ocular injuries remain common in patients with midface fractures, with an incidence rate of up to 90.6%. This study, the first of its kind conducted in Indonesia, aims to evaluate the characteristics and incidence of ocular injuries in midface fractures and to examine the relationship between the treatment. Methods: This observational analytic study employed a retrospective cohort design, utilizing medical record data of midface fracture patients. The independent variables included age, sex, cause, incidence, segment and severity of ocular injury, number of orbital wall involvements, and treatment options. The dependent variable was midface fracture patients. The Mann–Whitney and Fisher’s exact tests were employed to analyze the multivariate data. Results: Individuals aged 32–37 were most commonly affected due to accidents, with the anterior ocular segment and maxilla bone frequently affected. There are no special factors that differentiate a person from experiencing an ocular injury in a midface fracture (P > 0.05). Ocular injuries correlated with orbital wall injury (P = 0.008) at least one discontinuity. Impaired functions included movement and visual disturbances, diplopia, and dystopia (P = 0.134). Conclusions: No significant relationship was found between age, sex, and cause of trauma with ocular injuries in patients with midface fractures. However, a significant relationship was observed between the amount of orbital rim involvement and at least one wall discontinuity occurring in midface fracture patients.

Feeding behaviour related to different feeding devices.

Slow feeding devices (SFDs) are useful tools in order to improve the horse well-being and to reduce wastage, but their use may result in unnatural posture during feeding and frustration behaviours. Moreover, it may be important to evaluate the laterality during feeding. The aim of the study was to investigate ponies' feeding behaviour (i.e., lateralisation, frustration, postural eating style) with different hay feeding methods: on the ground (G), a fully filled hay net (HF), a partially filled hay net (HL), and a slow feeder hay box (HB). Nine ponies of two different breed types (Shetland and Welsh/Cob) were evaluated. Video recordings were obtained and then behavioural analysis was conducted. Data were analysed statistically using k-means cluster analysis, repeated measurement mixed model procedure, principal component analysis (PCA) and Pearson's correlation coefficient. Head tilting was more often performed during feeding from HF and HL compared to G and HB. Forelimb forward, referring to the position that ponies assumed during feeding, was performed less frequently with the hay nets. Ponies, in particular Welsh/Cobs, tended to be more left-lateralized and performed more backward ears when feeding from the hay nets. Blink rate was observed to be greater when ponies were fed from G. No head pushing, striking with forelimb and pawing while feeding was seen. Animals fed from HF tended to eat from the top of the hay net and consequently showed an arched neck; while HL and HB showed for elongated neck an intermediate pattern between G and HF. From our results, HB seemed to be a useful compromise between natural feeding on the ground and the use of hay nets.

Optimization of Wheelchair Control via Multi-Modal Integration: Combining Webcam and EEG

Even though Electric Powered Wheelchairs (EPWs) are a useful tool for meeting the needs of people with disabilities, some disabled people find it difficult to use regular EPWs that are joystick-controlled. Smart wheelchairs that use Brain–Computer Interface (BCI) technology present an efficient solution to this problem. This article presents a cutting-edge intelligent control wheelchair that is intended to improve user involvement and security. The suggested method combines facial expression analysis via a camera with EEG signal processing using the EMOTIV Insight EEG dataset. The system generates control commands by identifying specific EEG patterns linked to facial expressions such as eye blinking, winking left and right, and smiling. Simultaneously, the system uses computer vision algorithms and inertial measurements to analyze gaze direction in order to establish the user’s intended steering. The outcomes of the experiments prove that the proposed system is reliable and efficient in meeting the various requirements of people, presenting a positive development in the field of smart wheelchair technology.

Utility and Prognostic Value of Intraoperative Blink Reflex in Trigeminal or Facial Nerve Monitoring in Skull Base Surgeries: A Systematic Review

Blink reflex (BR) is an oligosynaptic reflex that involves the ophthalmic branch of the trigeminal nerve (TN), ipsilateral main sensory and trigeminospinal nuclei, bilateral facial nuclei, and the facial nerves (FN). Theoretically, as it tests the function of both TN and FN simultaneously, it is an ideal tool for monitoring the status of TN and FN during skull base surgeries. Nevertheless, it is only recently utilized in surgeries as the use of anesthesia limits its use. Two authors inputted the search terms: [(Blink Reflex) AND (Intraoperative Neuromonitoring OR Neuro Intraoperative Monitoring OR Intraoperative OR NIOM OR IONM) AND (skull base surgery OR Facial Nerve OR Trigeminal Nerve OR Microvascular Decompression OR Hemifacial Spasm)] in Medline through its Pubmed interface and other search engines. Papers that fulfilled the inclusion and exclusion criteria were obtained and scrutinized. Only 7 observational papers with a total of 437 participants were included in the current systematic review. All studies (n=5) involving the use of BR in FN surgery noted that IOBR is beneficial, safe, sensitive, specific, and predictive of outcomes while all 2 papers involving trigeminal neuralgia patients recommended BR's use in microvascular decompression (MVD) of TN. IOBR is a sensitive, specific and safe monitoring technique that has good predictability of facial paresis and paresthesia among patients undergoing MVD for trigeminal neuralgia and primary hemifacial spasm and those who are for cerebellopontine angle tumor resection.

Deep fakes Detection Using Human Eye Blinking Pattern: Deep Vision

Abstract: Deepfake technology is developing rapidly and has the ability to create fake videos that pose a threat to people. Modern depth detection methods often rely on facial disparity, but as technology advances these methods become obsolete. In this study, we propose a new method for deepfake detection based on observation of human eye blink patterns. Human eye blinking is a natural and involuntary action that is difficult to accurately replicate in deepfake video. In our study, we used the unique characteristics of individual blink patterns, which are influenced by many factors such as genetics, muscle tone and unconscious reflexes. We use computer vision and machine learning techniques to extract and identify these patterns from video clips. Our preliminary tests show good results in detecting deepfakes with high accuracy. We are focused on continuing to support the fight against the spread of fraud by focusing on a part of human behaviour that is difficult to replicate. This approach has the potential to improve existing tools for in-depth discovery and increase the overall security and reliability of multimedia content in the digital age. This research opens new avenues for the development of more robust, reliable and flexible deep recognition technologies. This represents a significant step forward in the ongoing fight against malicious misuse of electronic devices.

The effect of processing partial information in dynamic face perception

Face perception is a major topic in vision research. Most previous research has concentrated on (holistic) spatial representations of faces, often with static faces as stimuli. However, faces are highly dynamic stimuli containing important temporal information. How sensitive humans are regarding temporal information in dynamic faces is not well understood. Studies investigating temporal information in dynamic faces usually focus on the processing of emotional expressions. However, faces also contain relevant temporal information without any strong emotional expression. To investigate cues that modulate human sensitivity to temporal order, we utilized muted dynamic neutral face videos in two experiments. We varied the orientation of the faces (upright and inverted) and the presence/absence of eye blinks as partial dynamic cues. Participants viewed short, muted, monochromic videos of models vocalizing a widely known text (National Anthem). Videos were played either forward (in the correct temporal order) or backward. Participants were asked to determine the direction of the temporal order for each video, and (at the end of the experiment) whether they had understood the speech. We found that face orientation, and the presence/absence of an eye blink affected sensitivity, criterion (bias) and reaction time: Overall, sensitivity was higher for upright compared to inverted faces, and in the condition where an eye blink was present compared to the condition without an eye blink. Reaction times were mostly faster in the conditions with higher sensitivity. A bias to report inverted faces as ‘backward’ observed in Experiment I, where upright and inverted faces were presented randomly interleaved within each block, was absent when presenting upright and inverted faces in different blocks in Experiment II. Language comprehension results revealed that there was higher sensitivity when understanding the speech compared to not understanding the speech in both experiments. Taken together, our results showed higher sensitivity with upright compared to inverted faces, suggesting that the perception of dynamic, task-relevant information was superior with the canonical orientation of the faces. Furthermore, partial information coming from eye blinks, in addition to mouth movements, seemed to play a significant role in dynamic face perception, both when faces were presented upright and inverted. We suggest that studying the perception of facial dynamics beyond emotional expressions will help us to better understand the mechanisms underlying the temporal integration of facial information from different -partial and holistic- sources, and that our results show how different strategies, depending on the available information, are employed by human observers when judging the temporal order of faces.

FATIGUE DETECTION OF DRIVERS USING MACHINE LEARNING

In this project, the aim is to develop a prototype drowsiness detection system to address driver fatigue, a major cause of accidents worldwide. The system detects driver drowsiness by monitoring eye blinks and yawning. If the driver's eyes remain closed for an extended period or if yawning is detected, an alarm is sounded. Programming for this system is conducted in OpenCV, utilizing the Haar cascade library for face detection and other machine learning libraries to detect facial features. The system operates in real-time and is nonintrusive, prioritizing driver safety without being obtrusive. By effectively monitoring driver alertness and issuing timely warnings, this system contributes significantly to enhancing road safety. Keywords - Driver fatigue, drowsiness detection, eye blink, yawn detection, OpenCV, Haar cascade, machine learning, facial features.

MORSE CODE-BASED AUTHENTICATION SYSTEM

To tackle analytically complex issues, data science is a multidisciplinary combination of data inference, algorithm development, and technology. Nearly every industry, including business, finance, healthcare, and education, uses data science to manage massive volumes of data. Practical uses include text prediction, image processing, identity recognition, audio processing for speech, stock movement, and cancer prediction. Given that the majority of individuals on the planet have issues with security and authentication, For those who use Morse Code for self-authentication, we can offer real-time eye tracing for password authentication. As we all know, the 21st century has seen significant support for advancements in authorization and authentication technology. Since the late 1990s, personal identification numbers, or PINs, have been extensively used for user authentication and security. These days, it is easy to crack PIN codes, so we would rather use a different strategy. On the other hand, PIN authentication using hands-off gaze-based PIN entry techniques offers a more secure password entry option because it leaves no physical traces behind. Key Words: Morse code, Face recognition, Pin Entry, Eye Blinks, Gaze based

DROWSINESS AND ALCOHOL DETECTION USING ARDUINO

Accidents on road ways are increasing in our day to day lives. These accidents pose significant threats to human safety and well-being. There are several ways for reduction of accidents. Some of them are Drowsiness detection and Alcoholic detection. By using sensors, communication devices and algorithms, the system aims to identify potential hazards. This abstract presents a comprehensive approach to accident reduction using Internet of Things (IoT) technology. Drowsiness Detection System aims to mitigate the risks of drowsy driving and enhance road safety. By utilizing an Arduino microcontroller and various sensors, this system continuously monitors the driver’s vital signs and facial expressions. It analyzes parameters such as eye blink patterns, head movements, and heart rate to accurately identify signs of drowsiness. Upon detecting drowsiness, the system promptly alerts the driver through alarms or visual cues, prompting them to take necessary actions to prevent accidents. This project serves as a vital tool in reducing road accidents caused by driver drowsiness, ensuring safer journeys for all. This project presents the design and implementation of an Alcohol Detection with Engine Locking for cars using Arduino UNO as the MCU (Master Control Unit). The system will continuously monitor level of alcohol concentration in alcohol detection sensor and thus turn off the engine of vehicle if the alcohol concentration is above threshold level. The model will also send the message of whereabouts of the vehicle through SIM900A. The project provides an efficient solution to control accidents due to drunk driving Key Words: Arduino UNO, Sensor Fusion, Real time monitoring, MQ-3 sensor, GPS module, GSM module, Telematics.

Application of conjunctival graft surgery in the treatment of corneal ulcers in dogs

The study of conjunctival graft surgery for treating corneal ulcers in dogs was conducted at Alpha Pet Veterinary Clinic and Bang Pham Veterinary Hospital from August 2021 to August 2022. Dogs were clinically examined with corneal ulcers and corneal perforations, corneal reflexes, and then fluorescein 2% reagent was used to examine and measure the diameter of the corneal damaged area by using Castroviejo calipers. The surgical method of conjunctival stem grafting was applied and evaluated effects of treatment on corneal ulcers in dogs. A total of 3,024 dogs were examined and treated during the study period. There were 195 dogs with eye diseases, accounting for 6.45% of the cases. The rate of corneal ulcers was 15.90% (31/195 cases). Among the corneal ulcer cases, conjunctival graft surgery was performed in 14 cases. The successful rate of conjunctival stem grafting was 71.43%. The complication rate of conjunctival stem grafting was 42.86%, in which 2 cases of mild complications were successfully treated. The average wound healing duration was 39.45 days. The occurrence of complications depended on the types of complication. Mild complications including suture detachment and corneal edema appeared after 2.5 to 5.5 days while corneal epithelial cysts and ocular edema occurred at 22 to 42 days after surgery. Therefore, this method could be used in treatment of corneal ulcers, particularly in cases of deep ulcers or corneal perforations that required to directly connect to blood vessels.

Developing a quantitative method of mangiferin in rabbit lacrimal fluid as a tool for investigating pre-cornea drug residence

Mangiferin (MGF) has been evidenced to effectively treat infectious diseases caused by Herpes simplex virus, especially on the acyclovir-resistant strains. For ophthalmic disease treatment, prolonging drug retention in the eyes plays an essential role in effectively delivering drugs, which are prone to elimination by eye blinking and tear fluid secretion. The objective of this study was to develop a method for analysis of MGF in tear fluid that can be further utilised to evaluate the kinetics of precornea drug concentration. For sample collection, lacrimal tear fluid was absorbed into pre-weighed absorbing paper strips, which were then immediately weighed again right after sampling to calculate the sample mass. Subsequently, MGF was extracted from the paper strips using a mixture of methanol : acetic acid 0.6% (35:65, v/v). The extracted solution was finally injected into an HPLC system for MGF analysis (RP-column C18 - 4.6 x 250 mm, 5 μm was stabilised at 40oC; moblie phase methanol : acetic acid 0.6%; 35 : 65 (v/v) at a flow rate of 1.0 mL/min; autosampler, injection volume 10 µL; detection wavelength: 258 nm). The developed methodology was validated following the U.S. FDA and ICH M10 guidances for bioanalytical method validation, with respect to system suitability, linearity, recovery, accuracy and precision, dilution integrity and stability. The method was also successfully employed to determine MGF concentration in the tear fluid collected from rabbit eyes at one hour after instilling with MGF suspension. The methodology herein provides a practical tool to investigate kinetics of MGF in tear fluid that can be applied in ophthalmic drug development as well as drug quality evaluation activities.

Collision Avoidance Systems for Vehicle Safety Using Ultrasonic Distance Sensing Eye Blink Sensor and Alcohol Detector

Car wrecks are increasingly seen as a major safety issue; damage and fatality reports from these collisions are frequent. There are also more pedestrians who are killed by automobile accidents in cities and on highways. Additionally, autonomous cars often kill wild creatures that go farther into nature reserves. One cannot put a figure on the cost of a life, yet auto accidents hurt assets. This study looks at the creation and use of a complete collision avoidance system with the goal of improving vehicle safety by using cutting-edge technology. The suggested system includes an alcohol detector to stop accidents caused by intoxicated driving, an eye blink sensor to identify driver weariness, and an ultrasonic distance sensor to enable automated braking and collision avoidance. These sensors are seamlessly integrated to identify possible traffic dangers and initiate necessary reactions, all without depending on driver participation, thanks to the use of Arduino microcontrollers. The system design, methodology, and experimental findings are discussed in the study, which also shows how successful this integrated approach is at reducing road accidents. This study advances the global objective of increasing road safety by democratizing access to cutting-edge safety features that were previously only available in expensive cars.

Video-based analysis of the blink reflex in Parkinson’s disease patients

We developed a video-based tool to quantitatively assess the Glabellar Tap Reflex (GTR) in patients with idiopathic Parkinson’s disease (iPD) as well as healthy age-matched participants. We also video-graphically assessed the effect of dopaminergic medication on the GTR in iPD patients, as well as the frequency and blinking duration of reflex and non-reflex blinks. The Glabellar Tap Reflex is a clinical sign seen in patients e.g. suffering from iPD. Reliable tools to quantify this sign are lacking. Methods: We recorded the GTR in 11 iPD patients and 12 healthy controls (HC) with a consumer-grade camera at a framerate of at least 180 images/s. In these videos, reflex and non-reflex blinks were analyzed for blink count and blinking duration in an automated fashion. Results: With our setup, the GTR can be extracted from high-framerate cameras using landmarks of the MediaPipe face algorithm. iPD patients did not habituate to the GTR; dopaminergic medication did not alter that response. iPD patients’ non-reflex blinks were higher in frequency and higher in blinking duration (width at half prominence); dopaminergic medication decreased the median frequency (Before medication—HC: p < 0.001, After medication—HC: p = 0.0026) and decreased the median blinking duration (Before medication—HC: p = 0.8594, After medication—HC: p = 0.6943)—both in the direction of HC. Conclusion: We developed a quantitative, video-based tool to assess the GTR and other blinking-specific parameters in HC and iPD patients. Further studies could compare the video data to electromyogram (EMG) data for accuracy and comparability, as well as evaluate the specificity of the GTR in patients with other neurodegenerative disorders, in whom the GTR can also be present. Significance: The video-based detection of the blinking parameters allows for unobtrusive measurement in patients, a safer and more comfortable option.

EEG Eye Blink Artifacts Removal with Wavelet Denoising and Bandpass Filtering

EEG Eye Blink Artifacts Removal with Wavelet Denoising and Bandpass Filtering

Teprotumumab improves light sensitivity in patients with thyroid eye disease.

Teprotumumab, a novel IGF-1R antibody, has been shown to significantly reduce the signs of acute and chronic Thyroid Eye Disease (TED). Light sensitivity is a reported symptom in patients with TED. There is a lack of a prospective study that has explored the effects on light sensitivity in a large cohort of patients with acute and chronic TED following treatment with teprotumumab. Consecutive patients who were diagnosed with TED and reported light sensitivity at baseline were considered for study eligibility. All patients had measurements of Visual Light Sensitivity Questionnaire-8 (VLSQ-8), proptosis, clinical activity score (CAS), and MRD1 (distance between the upper eyelid margin and corneal reflex, mm) and MRD2 (distance between the lower eyelid margin and corneal reflex, mm) before and after treatment. Ninety patients (41 acute, 49 chronic) met the inclusion criteria. The mean (SD) age was 47.3 (14.3). Eighty-six (95.6%) patients completed all 8 infusions. There was a significant reduction in the total score and across all categories of the VLSQ-8 (p< 0.01 for all). Seventy-two (80%) patients had a clinically significant improvement (≥2 reduction) in at least one category. There was no significant difference in the total VLSQ-8 score between the acute and chronic group (p= 0.8). Teprotumumab improves light sensitivity in patients with acute and chronic TED. The results of this study highlight that the improvements in light sensitivity following treatment are not directly related to the mechanical changes in TED, suggesting another underlying mechanism ispotentially involved.

Differences in behaviour, facial expressions and locomotion between positive anticipation and frustration in horses

Animal welfare is a result of accumulated negative and positive emotions. Therefore, it is important to limit the former and promote the latter. Doing so requires a precise identification of these emotions. The aim of this study was to characterize the behaviours, facial expressions and locomotor parameters of 21 horses in two conditions with opposite valence, presumed to induce positive anticipation and frustration. In the positive anticipation situation, the horse was led to a bucket of food, knowing that they would be allowed to eat it. In the frustration situation, experimenters indicated to the horse that food was available without allowing them to eat it. In the positive anticipation situation, horses exhibited a lower neck position with the ears forward and upper lip advanced and went faster by increasing their stride frequency accompanied by increased global locomotor activity. In the frustration situation, horses exhibited a higher neck position with the ears backward or to the side, accompanied by ear movements and eye blinks, and interacted more with the experimenters. This study describes new possible indicators of positive anticipations and frustration in horses.

Artificial intelligence of things for smart cities: advanced solutions for enhancing transportation safety

In the context of smart cities, ensuring road safety is crucial due to increasing urbanization and the interconnected nature of contemporary urban environments. Leveraging innovative technologies is essential to mitigate risks and create safer communities. Thus, there is a compelling imperative to develop advanced solutions to enhance road safety within smart city frameworks. In this article, we introduce a comprehensive vehicle safety framework tailored specifically for smart cities in the realm of Artificial Intelligence of Things (AIoT). This framework seamlessly integrates a variety of sensors, including eye blink, ultrasonic, and alcohol sensors, to bolster road safety. The utilization of eye blink sensor serves to promptly detect potential hazards, alerting drivers through audible cues and thereby enhancing safety on smart city roads. Moreover, ultrasonic sensors provide real time information about surrounding vehicle speeds, thereby facilitating smoother traffic flow. To address concerns related to alcohol consumption and its potential impact on road safety, our framework incorporates a specialized sensor that effectively monitors the driver’s alcohol levels. In instances of high alcohol content, the system utilizes GPS and GSM technology to automatically adjust the vehicle’s speed while simultaneously notifying pertinent authorities for prompt intervention. Additionally, our proposed system optimizes inter-vehicle communication in smart cities by leveraging Li-Fi technology, enabling faster and more efficient data transmission via visible light communication (VLC). The integration of Li-Fi enhances connectivity among connected vehicles, contributing to a more cohesive and intelligent urban transportation network. Through the structured integration of AIoT technologies, our framework lays a robust foundation for a safer, smarter, and more sustainable future in smart city transportation. It offers significant advancements in road safety and establishes the groundwork for further enhancement in intelligent urban transportation networks.

Feature Extraction from Regenerated EEG – A Better Approach for ICA Based Eye Blink Artifact Detection

Purpose: Independent Component Analysis (ICA) decomposition is a commonly used technique for eye blink artifact detection from Electroencephalogram (EEG) signals. Feature extraction from the decomposed ICs is a prime step for blink detection. This paper presents a new model of eye blink detection for ICA based approach, where the decomposed ICs are projected to their corresponding EEG segments (ReEEG), and feature extraction is performed on the ReEEG instead of the IC. ReEEG represents the eye blink activity more distinctly. Hence, ReEEG-based feature extraction is more potential in detecting eye blink artifacts than the traditional IC-based feature extraction.&#x0D; Materials and Methods: This paper employs twelve EEG features to substantiate the superiority of ReEEG over IC. Support Vector Machine (SVM) is used as a classifier. A dataset, having 2638 clinical EEG epochs, is employed. All the considered twelve features are extracted from ReEEG and fed to SVM one at a time for blink detection. Then the obtained results are compared with an IC-based model with the same features.&#x0D; Results: The comparison reveals the success of the proposed ReEEG-based blink detection approach over the traditional IC-based approach. Accuracy, precision, recall, and f1 scores are calculated as performance measuring metrics. For almost all features, ReEEG-based approach achieved up to 12.25% higher accuracy, 24.95% higher precision, 13.49% higher recall, and 12.89% higher f1 score than the IC-based traditional method.&#x0D; Conclusion: The proposed model will be useful for researchers in dealing with the eye blink artifacts of EEG signals with more efficacy.