Voluntary Blinks Research Articles

Design recommendations for voluntary blink interactions based on pressure sensors

Voluntary blink control is vital in eye-controlled human–computer interaction (ECHCI). Pressure sensors, known for their low power consumption and strong resistance to interference, are suitable for blink detection. Existing research has predominantly focused on sensor materials and signal processing, and studies on the characteristics and optimized design of voluntary blink actions in ECHCI remain relatively limited. Therefore, this study presents a blink detection system based on pressure sensors and investigates the efficiency of voluntary blink actions. We examined the effects of two independent variables, blink count (single, double, and triple) and blink side (bilateral and unilateral), on recognition accuracy and three time-related variables. Subsequently, the subjective workload and evaluation experiments were conducted for each blink action. The results indicate that the blink count has a more pronounced impact on interaction efficiency and comfort, with continuous blink actions exceeding three blinks not being recommended. Bilateral blinks were perceived as more natural and comfortable than unilateral blinks. Moreover, we discovered that the participants exhibited greater attentiveness and focus when performing double bilateral blink actions, making it suitable for important commands. Based on the experimental results, the top three recommended voluntary blink actions are single bilateral blink (SB), double bilateral blink (DB), and single unilateral blink (SU). Finally, a test involving controlling the movement of a toy car using the recommended blink actions validates the usability of the actions and detection system. These findings provide valuable guidance for the design and optimization of voluntary-blink interaction systems, further enhancing this interaction method’s feasibility.

Electrophysiological Activity from the Eye Muscles, Cerebellum and Cerebrum During Reflexive (Classical Pavlovian) Versus Voluntary (Ivanov-Smolensky) Eye-Blink Conditioning

We report an experiment to investigate the role of the cerebellum and cerebrum in motor learning of timed movements. Eleven healthy human subjects were recruited to perform two experiments, the first was a classical eye-blink conditioning procedure with an auditory tone as conditional stimulus (CS) and vestibular unconditional stimulus (US) in the form of a double head-tap. In the second experiment, subjects were asked to blink voluntarily in synchrony with the double head-tap US preceded by a CS, a form of Ivanov-Smolensky conditioning in which a command or instruction is associated with the US. Electrophysiological recordings were made of extra-ocular EMG and EOG at infra-ocular sites (IO1/2), EEG from over the frontal eye fields (C3’/C4’) and from over the posterior fossa over the cerebellum for the electrocerebellogram (ECeG). The behavioural outcomes of the experiments showed weak reflexive conditioning for the first experiment despite the double tap but robust, well-synchronised voluntary conditioning for the second. Voluntary conditioned blinks were larger than the reflex ones. For the voluntary conditioning experiment, a contingent negative variation (CNV) was also present in the EEG leads prior to movement, and modulation of the high-frequency EEG occurred during movement. US-related cerebellar activity was prominent in the high-frequency ECeG for both experiments, while conditioned response-related cerebellar activity was additionally present in the voluntary conditioning experiment. These results demonstrate a role for the cerebellum in voluntary (Ivanov-Smolensky) as well as in reflexive (classical Pavlovian) conditioning.

An EMG-based wearable multifunctional Eye-control glass to control home appliances and communicate by voluntary blinks

The purpose of this work is to first apply the electromyogram (EMG) of corrugator supercilii muscles as the only signal to control home appliances and communicate with others by means of voluntary blinks, especially for the severely disabled. An EMG-based wearable eye-control glass is constructed as a multifunctional human–machine interface (HMI) device in this work. Twelve healthy subjects participated in the experiment to perform the home appliance eye-control task and the eye-communication task. This multifunctional eye-control glass is low-cost, easy-to-use, and wearable, and the experiment results indicate the high selectivity of voluntary blinks/natural blinks and left-eye blinks/right-eye blinks, excellent sensitivity, fast response time, high accuracy, low individual differences, and a prominent information transfer rate of the wearable device. This study provides a novel way for the construction of wearable eye-control devices to help healthy and disabled people conveniently control home appliances and communicate with the external world. It is gentler for users when applying this EMG-based wearable eye-control glass in various practical applications, like in the cinema or a meeting, than gesture and voice interactions. For disabled people without speaking ability, users can perform simple communication and express their needs with clinical staff with the help of this wearable device. Especially, this novel method greatly facilitates the daily lives of patients in the lock-in state through blink control. Moreover, the relationship between voluntary blinks and the movement of corrugator supercilii muscles is proven.

Trigger motion and interface optimization of an eye-controlled human-computer interaction system based on voluntary eye blinks

ABSTRACT Eye-controlled human-computer interaction (ECHCI) attracts attention for its human-centered, natural and direct operation characteristics. The most common ECHCI trigger motion is “gazing,” which causes Midas Touch problems, lowering usability and operation experience. This paper innovatively proposed using motion combinations based on blinking as the trigger of interactive objects (IOs). Trigger motions and IO design parameters were explored on the platform consisting of Tobii eye-tracker and computer vision kits. In the motion experiment, it was concluded 2-blinks could bring a low task load and high success rate of 95%. In the IO size experiment, the larger the IO diameter, the shorter the users’ response time and the higher users’ interaction success rate, and 55.5 mm was the optimal setting. Based on this, it was found a larger spacing could bring higher operation efficiency, and 33.3 mm was taken as the recommended value. Based on the conclusion above, an eye-controlled multimedia player prototype was built for usability evaluation, which showed an equally high efficiency compared to mouse-controlled HCI. The findings in this paper overcame Midas Touch issues and avoided the interference of unavoidable involuntary blinking, which brought a significant increase in system robustness and has a wide range of potential applications.

LabVIEW Instruments for Creating Brain-Computer Interface Applications by Simulating Graphical Animations and Sending Text Messages to Virtual and Physical LEDs Based Display Systems Connected to Arduino Board

The brain-computer interface (BCI) is a multidisciplinary research field aimed at helping people with neuromotor disabilities. A BCI system enables the control of mechatronic devices by using cognitive intentions translated into electroencephalographic signals. This paper presents the implementation of LabVIEW-based display systems that can be controlled by a brain-computer interface based on detecting the voluntary eye blinks used as commands. The interactive virtual or physical display systems are helpful thanks to running or simulating various graphical animations or transmitting different text messages in a user-customizable way. The proposed LabVIEW-based virtual display systems provide versatile functionalities such as: customizing the own visual animations and the movement of any text message by switching the direction (to the left or to the right) depending on the user’s choice. This paper presents five original virtual LEDs based display systems developed in LabVIEW graphical programming environment. The implemented LabVIEW applications included: an 8x8 LEDs matrix for simulating graphical animations, 2x16 LCD TEXT for showing text messages, and a 7-segments display for implementing chronometer functionality. Moreover, the LabVIEW virtual display systems were interfaced with the physical display systems (8x8 LEDs matrix controlled by MAX7219 driver and 2x16 LCD TEXT) connected to the Arduino Uno board.

Predictive text analysis using eye blinks

The current work aims to facilitate interaction with others to those with the inability to perform activities requiring motor skills or those who cannot speak. It proposes a modus operandi or a system based on Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM), which automatically identifies eye blinks in real-time to predict a lexicon. The system implements an auxiliary input that enables individuals to interact with others with the help of a device, where voluntary long blinks help in transition from a counter to a predictive table, while the short blinks are used to make the counter stop and select the lexicon. The system does not require prior manual initialization, special lighting, or previous face detection as it can calibrate it if the user is in the camera region and close. The proposed user interface makes the process of words detection by blinking easier with 74% accuracy.

A closed-loop brain-computer interface with augmented reality feedback for industrial human-robot collaboration

Industrial human-robot collaboration (HRC) aims to combine human intelligence and robotic capability to achieve higher productiveness. In industrial HRC, the communication between humans and robots is essential to enhance the understanding of the intent of each other to make a more fluent collaboration. Brain-computer interface (BCI) is a technology that could record the user’s brain activity that can be translated into interaction messages (e.g., control commands) to the outside world, which can build a direct and efficient communication channel between human and robot. However, due to lacking information feedback mechanisms, it is challenging for BCI to control robots with a high degree of freedom with a limited number of classifiable mental states. To address this problem, this paper proposes a closed-loop BCI with contextual visual feedback by an augmented reality (AR) headset. In such BCI, the electroencephalogram (EEG) patterns from the multiple voluntary eye blinks are considered the input and its online detection algorithm is proposed whose average accuracy can reach 94.31%. Moreover, an AR-enable information feedback interface is designed to achieve an interactive robotic path planning. A case study of an industrial HRC assembly task is also developed to show that the proposed closed-up BCI could shorten the time of user input in human-robot interaction.

Controlling a Mouse Pointer with a Single-Channel EEG Sensor.

(1) Goals: The purpose of this study was to analyze the feasibility of using the information obtained from a one-channel electro-encephalography (EEG) signal to control a mouse pointer. We used a low-cost headset, with one dry sensor placed at the FP1 position, to steer a mouse pointer and make selections through a combination of the user’s attention level with the detection of voluntary blinks. There are two types of cursor movements: spinning and linear displacement. A sequence of blinks allows for switching between these movement types, while the attention level modulates the cursor’s speed. The influence of the attention level on performance was studied. Additionally, Fitts’ model and the evolution of the emotional states of participants, among other trajectory indicators, were analyzed. (2) Methods: Twenty participants distributed into two groups (Attention and No-Attention) performed three runs, on different days, in which 40 targets had to be reached and selected. Target positions and distances from the cursor’s initial position were chosen, providing eight different indices of difficulty (IDs). A self-assessment manikin (SAM) test and a final survey provided information about the system’s usability and the emotions of participants during the experiment. (3) Results: The performance was similar to some brain–computer interface (BCI) solutions found in the literature, with an averaged information transfer rate (ITR) of 7 bits/min. Concerning the cursor navigation, some trajectory indicators showed our proposed approach to be as good as common pointing devices, such as joysticks, trackballs, and so on. Only one of the 20 participants reported difficulty in managing the cursor and, according to the tests, most of them assessed the experience positively. Movement times and hit rates were significantly better for participants belonging to the attention group. (4) Conclusions: The proposed approach is a feasible low-cost solution to manage a mouse pointer.

Brain-Computer Interfacing for Wheelchair Control by Detecting Voluntary Eye Blinks

The human brain is considered as one of the most powerful quantum computers and combining the human brain with technology can even outperform artificial intelligence. Using a Brain-Computer Interface (BCI) system, the brain signals can be analyzed and programmed for specific tasks. This research work employs BCI technology for a medical application that gives the unfortunate paralyzed individuals the capability to interact with their surroundings solely using voluntary eye blinks. This research contributes to the existing technology to be more feasible by introducing a modular design with three physically separated components: a headwear, a computer, and a wheelchair. As the signal-to-noise ratio (SNR) of the existing systems is too high to separate the eye blink artifacts from the regular EEG signal, a precise ThinkGear module is used which acquired the raw EEG signal through a single dry electrode. This chip offers an advanced filtering technology that has a high noise immunity along with an embedded Bluetooth module using which the acquired signal is transferred wirelessly to a computer. A MATLAB program captures voluntary eye blink artifacts from the brain waves and commands the movement of a miniature wheelchair via Bluetooth. To distinguish voluntary eye blinks from involuntary eye blinks, blink strength thresholds are determined. A Graphical User Interface (GUI) designed in MATLAB displays the EEG waves in real-time and enables the user to determine the movements of the wheelchair which is specially designed to take commands from the GUI. The findings from the testing phase unveil the advantages of a modular design and the efficacy of using eye blink artifacts as the control element for brain-controlled wheelchairs. The work presented here gives a basic understanding of the functionality of a BCI system, and provides eye blink-controlled navigation of a wheelchair for patients suffering from severe paralysis.

Blink input interface enabling multiple candidate selection through sound feedback

Several input interfaces that employ eye-blinking detection have been proposed. These input interfaces can detect operating intentions indicated by eye-blink actions. In this study, we propose a new blink input interface with the aim of increasing the classifiable blink types in addition to the regular voluntary blink. The proposed interface employs a sound feedback that facilitates multiple candidate selection. The feedback sound represents each input candidate and is generated while switching over time. This interface enables the user to input their operating intentions by controlling the timing of eye opening. We developed a prototype with the proposed interface and evaluated the system. The results indicated that a total classification rate of 96.5% is achieved for four types of voluntary blinks with 10 subjects. This classification rate is in accordance that of our previous report for two types of voluntary blinks. Thus, we concluded that our proposed method is reliable.

Boosted visual performance after eye blinks.

We blink more often than required for maintaining the corneal tear film. Whether there are perceptual or cognitive consequences of blinks that may justify their high frequency is unclear. Previous findings showed that blinks may indicate switches between large-scale cortical networks, such as dorsal attention and default-mode networks. Thus, blinks may trigger a refresh of visual attention. Yet, this has so far not been confirmed behaviorally. Here, we tested the effect of blinks on visual performance in a series of rapid serial visual presentation tasks. In Experiment 1, participants had to identify a target digit embedded in a random stream of letter distractors, presented foveally for 60 ms each. Participants blinked once during the presentation stream. In a separate condition, blinks were simulated by shutter glasses. Detection performance was enhanced (up to 13% point increase in accuracy) for targets appearing up to 300 ms after eye blinks. Performance boosts were stronger for voluntary blinks than artificial blinks. This performance boost was also replicated with more naturalistic stimuli (Experiment 2). We conclude that eye blinks lead to attentional benefits for object recognition in the period after reopening of the eyelids and may be used strategically for temporarily boosting visual performance.

Videographic Analysis of Blink Dynamics following Upper Eyelid Blepharoplasty and Its Association with Dry Eye

Background:This study was undertaken to characterize the effects of upper eyelid blepharoplasty on blink dynamics and to evaluate the hypothesis that changes in blink dynamics following blepharoplasty are associated with postoperative dry eye.Methods:The voluntary blink of 14 eyes of 7 patients with dermatochalasis undergoing upper eyelid blepharoplasty was recorded with a high-speed camera preoperatively and 6–8 months postoperatively, alongside a group of 11 controls. The images were analyzed for palpebral aperture, blink duration, and maximum velocity during opening and closing phases. Patients undergoing blepharoplasty were assessed for dry eye symptoms pre- and postoperatively at 6–8 months using the ocular surface disease index score.Results:Despite intraoperative orbicularis oculi resection, there was no significant compromise of blink duration or maximum velocity of eyelid opening or closure post-blepharoplasty. Postoperatively, patients had an increase in palpebral aperture compared with both preoperatively (8.71 versus 7.85 mm; P = 0.013) and control groups (8.71 versus 7.87 mm; P = 0.04). Postoperatively at 6–8 months, there was an increase in dry eye symptoms in 6 of 7 patients compared with preoperatively (ocular surface disease index, 16.6 versus 12.5; P < 0.05). There was no positive correlation between the increase in palpebral aperture and the increase in dry eye symptoms (r = –0.4; P = 0.30).Conclusions:Using modern videographic technology, this study demonstrates that upper eyelid blepharoplasty results in an increase in resting palpebral aperture but has no effect on dynamic blink parameters. Changes in palpebral aperture or blink dynamics are unlikely to be the cause of dry eye syndrome following blepharoplasty.

Use of spontaneous blinking for application in human authentication

Contamination of electroencephalogram (EEG) signals due to natural blinking electrooculogram (EOG) signals is often removed to enhance the quality of EEG signals. This paper discusses the possibility of using solely involuntary blinking signals for human authentication. The EEG data of 46 subjects were recorded while the subject was looking at a sequence of different pictures. During the experiment, the subject was not focused on any kind of blinking task. Having the blink EOG signals separated from EEG, 25 features were extracted and the data were preprocessed in order to handle the corrupt or missing values. Since spontaneous and voluntary blinks have different characteristics in terms of kinematic variables and because the previous studies’ control setup may have altered the type of blink from spontaneous to voluntary, a series of statistical analysis was carried out in order to inspect the changes in the multivariate probability distribution of data compared to the previous studies. Statistical significance shows that it is very likely that the blink features of both voluntary and involuntary blink signal are generated by Gaussian probability density function, although different than voluntary blink, spontaneous blink is not well discriminated with Gaussian. Despite testing several models, none managed to classify the data using only the information of a single spontaneous blink. Thereby, we examined the possibility of learning the patterns of a series of blinks using Gated Recurrent Unit (GRU). Our results show that individuals can be distinguished with up to 98.7% accuracy using only a reasonably short sequence of involuntary blinking signals.

Non-invasive high-speed blinking kinematics characterization.

The objective of this study was to analyze the differences in blinking kinematics of spontaneous and voluntary blinks using for the first time a self-developed, non-invasive, and image processing-based method. The blinks of 30 subjects were recorded for 1 min with the support of an eye-tracking device based on a high-speed infrared video camera, working at 250 frames per second, under two different experimental conditions. For the first condition, subjects were ordered to look in the straightforward position at a fixation target placed 1 m in front of them, with no further instructions. For the second, subjects were additionally asked to blink only following a sound signal every 6 s. Mean complete blinks increased by a factor of 1.7 from the spontaneous to the voluntary condition while mean incomplete blinks reduced significantly by a factor of 0.4. In both conditions, closing mean and peak velocities were always significantly greater and durations significantly lower than opening ones. When comparing the values for each condition, velocities and amplitudes for the voluntary condition were always greater than the corresponding values for spontaneous. Voluntary blinks revealed significant kinematic differences compared to spontaneous, thus supporting a different supranuclear pathway organization. This study presents a new method, based on image analysis, for the non-invasive kinematic characterization of blinking.

Auditory Electrooculogram-based Communication System for ALS Patients in Transition from Locked-in to Complete Locked-in State

Patients in the transition from locked-in (i.e., a state of almost complete paralysis with voluntary eye movement control, eye blinks or twitches of face muscles, and preserved consciousness) to complete locked-in state (i.e., total paralysis including paralysis of eye-muscles and loss of gaze-fixation, combined with preserved consciousness) are left without any means of communication. An auditory communication system based on electrooculogram (EOG) was developed to enable such patients to communicate. Four amyotrophic lateral sclerosis patients in transition from locked-in state to completely locked-in state, with ALSFRS-R score of 0, unable to use eye trackers for communication, learned to use an auditory EOG-based communication system. The patients, with eye-movement amplitude between the range of ±200μV and ±40μV, were able to form complete sentences and communicate independently and freely, selecting letters from an auditory speller system. A follow-up of one year with one patient shows the feasibility of the proposed system in long-term use and the correlation between speller performance and eye-movement decay. The results of the auditory speller system have the potential to provide a means of communication to patient populations without gaze fixation ability and with low eye-movement amplitude range.

Brain computer interface based smart keyboard using neurosky mindwave headset

In the last decade, numerous researches in the field of ‎ electro-encephalo-graphy (EEG) and brain-computer-interface ‎‎ (BCI) have been accomplished. BCI has been developed to aid ‎ disabled/partially disabled people to efficiently communicate ‎ with the community. This paper presents a control tool using ‎ the Neurosky Mindwave headset, which detects brainwaves ‎‎ (voluntary blinks and attention) to form a brain-computer ‎ interface (BCI) by receiving the system signals from the frontal lobe. This paper proposed an alternative computer input device ‎ for those disabled people (who are physically challenged) ‎ rather than the conventional one. The work suggested to use ‎ two virtual keyboard designs. The conducted experiment ‎ revealed a significant result in developing user printing skills ‎ on PCs. Encouraging results (1.55-1.8 word per minute ‎‎ (WPM)) were obtained in this research in comparison to other ‎ studies.

Self-powered eye motion sensor based on triboelectric interaction and near-field electrostatic induction for wearable assistive technologies

Abstract Triboelectric nanogenerators show great potential as flexible motion transducers for wearable human-machine interfaces (HMI). The present research explores a new configuration named Non-Attached Electrode-Dielectric Triboelectric Sensor (NEDTS) and its application in specialized HMI to support people with disabilities in daily life. In this topology, the conductive electrodes are not bonded to the dielectric materials by any coating or sputtering process. Instead, due to the triboelectric interaction between the two elements in motion, voltage is generated in a separate conductor by non-contact electrostatic induction. This allows a near field remote sensing using triboelectric/electrostatic coupling. By applying the mentioned sensing technique, an Orbicularis Oculi muscle motion sensor has been developed to monitor voluntary and involuntary eye blinks. The new transducer is integrated into a portable HMI for hands-free computer cursor control to assist people with mobility impairment. The conceived device was also tested in other applications as hands-free remote car and drone control, and for monitoring driving behaviour. Additionally, a PDMS-based eyelid motion sensor has been tested to feature other virtues of the NEDTS when sensing unconventional motion dynamics.

RVEB—An algorithm for recognizing voluntary eye blinks based on the signal recorded from prefrontal EEG channels

ObjectiveThe paper presents an algorithm for recognizing voluntary eye blinks (RVEB). The algorithm is based on the analysis of time waveforms recorded from two prefrontal EEG (electroencephalographic) channels. Two versions of the algorithm are provided: 1) for recognizing different numbers of winks with the left or right eye (left-right RVEB algorithm); 2) for recognizing different numbers of winks with the left or right eye, or different numbers of blinks with both eyes (left-right-both RVEB algorithm). MethodsThe paper provides a description of the algorithm and its verification via a two-session experiment conducted with 12 healthy subjects. Results(i) the average detection accuracy reached 96.9% and 93.8% for the left-right and left-right-both RVEB algorithm, respectively; (ii) the recognition rate was stable across different eye conditions and different numbers of winks/blinks; (iii) the average time needed to perform one command in a free user session with four blinking schemes was equal to 2.04 s and the average accuracy was 95%. ConclusionThe comparison with other papers shows that the proposed algorithm is able to recognize: a higher number of control states (9 states) than reference algorithms (1–4 states) with a high detection rate and short calibration period (15–21 s). SignificanceComparing to nowadays Brain-Computer Interfaces (BCIs), the RVEB algorithm provides more comfortable communication (for people able to control their eyelid muscles) than BCIs based on steady state visually evoked potentials or P300 component and more control states than BCIs based on motor imagery.

Study of Blink Dynamics: Involuntary vs Voluntary Blinks

Study of Blink Dynamics: Involuntary vs Voluntary Blinks

An Electrooculography based Human Machine Interface for wheelchair control

This paper presents a novel single channel Electrooculography (EOG) based efficient Human–Machine Interface (HMI) for helping the individuals suffering from severe paralysis or motor degenerative diseases to regain mobility. In this study, we propose a robust system that generates control command using only one type of asynchronous eye activity (voluntary eye blink) to navigate the wheelchair without a need of graphical user interface. This work demonstrates a simple but robust and effective multi-level threshold strategy to generate control commands from multiple features associated with the single, double and triple voluntary eye blinks to control predefined actions (forward, right turn, left turn and stop). Experimental trials were carried out on the able-bodied and disabled subjects to validate the universal applicability of the algorithms. It achieved an average command detection and execution accuracy of 93.89% with information transfer rate (ITR) of 62.64 (bits/min) that shows the robust, sensitive and responsive features of the presented interface. In comparison with the established state of art similar HMI systems, our system achieved a better trade-off between higher accuracy and better ITR and while maintaining better performance in all qualitative and quantitative criteria. The results confirm that the proposed system offers a user-friendly, cost-effective and reliable alternative to the existing EOG-based HMI.