Single-channel Electrooculography Research Articles

Single-channel EOG sleep staging on a heterogeneous cohort of subjects with sleep disorders

Objective. Sleep staging based on full polysomnography is the gold standard in the diagnosis of many sleep disorders. It is however costly, complex, and obtrusive due to the use of multiple electrodes. Automatic sleep staging based on single-channel electro-oculography (EOG) is a promising alternative, requiring fewer electrodes which could be self-applied below the hairline. EOG sleep staging algorithms are however yet to be validated in clinical populations with sleep disorders. Approach. We utilized the SOMNIA dataset, comprising 774 recordings from subjects with various sleep disorders, including insomnia, sleep-disordered breathing, hypersomnolence, circadian rhythm disorders, parasomnias, and movement disorders. The recordings were divided into train (574), validation (100), and test (100) groups. We trained a neural network that integrated transformers within a U-Net backbone. This design facilitated learning of arbitrary-distance temporal relationships within and between the EOG and hypnogram. Main results. For 5-class sleep staging, we achieved median accuracies of 85.0% and 85.2% and Cohen’s kappas of 0.781 and 0.796 for left and right EOG, respectively. The performance using the right EOG was significantly better than using the left EOG, possibly because in the recommended AASM setup, this electrode is located closer to the scalp. The proposed model is robust to the presence of a variety of sleep disorders, displaying no significant difference in performance for subjects with a certain sleep disorder compared to those without. Significance. The results show that accurate sleep staging using single-channel EOG can be done reliably for subjects with a variety of sleep disorders.

Eye Fatigue Detection through Machine Learning Based on Single Channel Electrooculography

Nowadays, eye fatigue is becoming more common globally. However, there was no objective and effective method for eye fatigue detection except the sample survey questionnaire. An eye fatigue detection method by machine learning based on the Single-Channel Electrooculography-based System is proposed. Subjects are required to finish the industry-standard questionnaires of eye fatigue; the results are used as data labels. Then, we collect their electrooculography signals through a single-channel device. From the electrooculography signals, the five most relevant feature values of eye fatigue are extracted. A machine learning model that uses the five feature values as its input is designed for eye fatigue detection. Experimental results show that there is an objective link between electrooculography and eye fatigue. This method could be used in daily eye fatigue detection and it is promised in the future.

Toward graphene textiles in wearable eye tracking systems for human-machine interaction.

The study of eye movements and the measurement of the resulting biopotential, referred to as electrooculography (EOG), may find increasing use in applications within the domain of activity recognition, context awareness, mobile human–computer and human–machine interaction (HCI/HMI), and personal medical devices; provided that, seamless sensing of eye activity and processing thereof is achieved by a truly wearable, low-cost, and accessible technology. The present study demonstrates an alternative to the bulky and expensive camera-based eye tracking systems and reports the development of a graphene textile-based personal assistive device for the first time. This self-contained wearable prototype comprises a headband with soft graphene textile electrodes that overcome the limitations of conventional “wet” electrodes, along with miniaturized, portable readout electronics with real-time signal processing capability that can stream data to a remote device over Bluetooth. The potential of graphene textiles in wearable eye tracking and eye-operated remote object interaction is demonstrated by controlling a mouse cursor on screen for typing with a virtual keyboard and enabling navigation of a four-wheeled robot in a maze, all utilizing five different eye motions initiated with a single channel EOG acquisition. Typing speeds of up to six characters per minute without prediction algorithms and guidance of the robot in a maze with four 180° turns were successfully achieved with perfect pattern detection accuracies of 100% and 98%, respectively.

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.

Real-time estimation of horizontal gaze angle by saccade integration using in-ear electrooculography.

The manuscript proposes and evaluates a real-time algorithm for estimating eye gaze angle based solely on single-channel electrooculography (EOG), which can be obtained directly from the ear canal using conductive ear moulds. In contrast to conventional high-pass filtering, we used an algorithm that calculates absolute eye gaze angle via statistical analysis of detected saccades. The estimated eye positions of the new algorithm were still noisy. However, the performance in terms of Pearson product-moment correlation coefficients was significantly better than the conventional approach in some instances. The results suggest that in-ear EOG signals captured with conductive ear moulds could serve as a basis for light-weight and portable horizontal eye gaze angle estimation suitable for a broad range of applications. For instance, for hearing aids to steer the directivity of microphones in the direction of the user’s eye gaze.

A human-machine interface based on single channel EOG and patchable sensor

This study demonstrates that single channel electrooculography (EOG) recorded by ultrathin and flexible electrodes can be practically used to control computer or machine, with the aid of proper recognition algorithms and efficient controlling methods. First, micro-fabrication process and transfer technology were used to develop a patchable sensor including three electrodes (a measurement electrode, a ground electrode, and a reference electrode). Each electrode was composed of golden ribbon in the form of a filamentary serpentine mesh to provide conformal contact of skin and stretchability. Second, EOG was recorded by the proposed sensor installed above the eyebrow. The peak and trough of eye movement signals were extracted as features to recognize three types of eye movements (blink, upward and downward) using a threshold-based recognition algorithm. Finally, a human-machine interface (HMI) system was realized by converting eye movements to computer commands including scroll up, scroll down, and close. To verify the effectiveness of the system, eight subjects were trained to use their eye movements to navigate a document on the screen. The sensor was approximately triangular with a 5 cm side-length and a 70 um thickness. The electrode can be stretched to 10% longer without any damage. The weight of the sensor was 180 mg. The demonstration system was capable of making continuous controls with an average accuracy of 84%. Single channel EOG recorded with a patchable sensor is feasible for developing a wearable HMI system. The proposed system provides a comfortable user experience, a stable control method and a simple systematic framework for developing practical HMI systems.

Efficient Implementation and Design of a New Single-Channel Electrooculography-Based Human–Machine Interface System

This brief introduces a new and practical human-machine interface (HMI) system based on single-channel electrooculography (EOG) signals. The proposed system uses a consumer wireless recording device to collect EOG and employs new encoding/decoding paradigms to convey users' intentions with EOG from eye movements including blinking and looking up. The simplicity and mobility of the system provides a comfortable and practical solution to HMI. Furthermore, to reduce the hardware complexity and power consumption of the signal processing modules of the EOG-based HMI system, a novel multiplierless implementation is developed, where all the algorithms involved, such as bandpass filtering, wavelet filtering, and support vector machine, can be realized using a limited number of adders and shifters only. Experimental results show that the proposed system offers a simple, practical, and yet reliable EOG-based HMI with low complexity and power consumption.

O28: Comparison of the language lateralizations suggested by magnetoencephalography and navigated transcranial magnetic stimulation in healthy subjects using a picture naming task

O28: Comparison of the language lateralizations suggested by magnetoencephalography and navigated transcranial magnetic stimulation in healthy subjects using a picture naming task

O29: Beyond skeletomotor function of human basal ganglia: oculomotor, visual and affective neurons

Deep brain stimulation (DBS) of targets in basal ganglia is an effective treatment of motor dysfunction in Parkinson’s disease and primary dystonia. However this treatment may be accompanied by unwanted non-motor side effects. To confirm their neurophysiological nature we searched for any neurons in the subthalamic nucleus (STN), substantia nigra pars reticulata (SNr) and globus pallidus (GP) involved in processing of visually presented emotional scenes. Nineteen Parkinson’s disease patients, which underwent implantation of DBS electrodes to STN or GP, were investigated with simultaneous intraoperative microelectrode recordings and single channel electrooculography during a visual emotional task containing a series of photographs varying in emotional valence and arousal. Recordings were analyzed by the WaveClus program which allowed for detection and sorting of individual neurons. Out of 183 neurons that were detected, 130 were found in the STN, 30 in the SNr and 23 in the GP. Twenty percent of the neurons in each of these structures showed eye movement-related activity. In the STN, we observed 35 neurons whose firing rate changed significantly within first 500 ms after presentation of a photograph suggesting their participation in visual or attentional mechanisms. Activity of 14 STN neurons showed significant changes during 500–1500 ms interval in alpha band of the instantaneous firing rate related to the emotional content of presented photographs. Activity of 8 of neurons was related to the arousal while activity of another 6 neurons was changing in relation to the emotional valence. Our results showed that basal ganglia contain relatively high share of oculomotor neurons suggesting their critical role in eye-movement control. In addition, the STN neurons involved in visual processing and in transmission of emotional information provide evidence of separate management of the affective dimensions of valence and arousal. Therefore, it is not surprising that DBS may have various non-motor consequences. Supported by grants: IGA MZ CR NT12282–5/2011; research projects: MSM 0021620849, MSM 6840770012 and PRVOUK-P26/LF1/4.

18. Beyond skeletomotor function of human basal ganglia: Oculomotor, visual and affective neurons

Deep brain stimulation (DBS) of targets in basal ganglia is an effective treatment of motor dysfunction in Parkinson’s disease and primary dystonia. However this treatment may be accompanied by unwanted non-motor side effects. To confirm their neurophysiological nature we searched for any neurons in the subthalamic nucleus (STN), substantia nigra pars reticulata (SNr) and globus pallidus (GP) involved in processing of visually presented emotional scenes. Nineteen Parkinson’s disease patients, which underwent implantation of DBS electrodes to STN or GP, were investigated with simultaneous intraoperative microelectrode recordings and single channel electrooculography during a visual emotional task containing a series of photographs varying in emotional valence and arousal. Recordings were analyzed by the WaveClus program which allowed for detection and sorting of individual neurons. Out of 183 neurons that were detected, 130 were found in the STN, 30 in the SNr and 23 in the GP. Twenty percent of the neurons in each of these structures showed eye movement-related activity. In the STN, we observed 35 neurons whose firing rate changed significantly within first 500 ms after presentation of a photograph suggesting their participation in visual or attentional mechanisms. Activity of 14 STN neurons showed significant changes during 500–1500 ms interval in alpha band of the instantaneous firing rate related to the emotional content of presented photographs. Activity of 8 of neurons was related to the arousal while activity of another 6 neurons was changing in relation to the emotional valence. Our results showed that basal ganglia contain relatively high share of oculomotor neurons suggesting their critical role in eye-movement control. In addition, the STN neurons involved in visual processing and in transmission of emotional information provide evidence of separate management of the affective dimensions of valence and arousal. Therefore, it is not surprising that DBS may have various non-motor consequences. Supported by grants: IGA MZ ČR NT12282–5/2011; research projects: MŠM 0021620849, MŠM 6840770012 and PRVOUK-P26/LF1/4.

Basal Ganglia Neuronal Activity during Scanning Eye Movements in Parkinson’s Disease

The oculomotor role of the basal ganglia has been supported by extensive evidence, although their role in scanning eye movements is poorly understood. Nineteen Parkinsońs disease patients, which underwent implantation of deep brain stimulation electrodes, were investigated with simultaneous intraoperative microelectrode recordings and single channel electrooculography in a scanning eye movement task by viewing a series of colored pictures selected from the International Affective Picture System. Four patients additionally underwent a visually guided saccade task. Microelectrode recordings were analyzed selectively from the subthalamic nucleus, substantia nigra pars reticulata and from the globus pallidus by the WaveClus program which allowed for detection and sorting of individual neurons. The relationship between neuronal firing rate and eye movements was studied by crosscorrelation analysis. Out of 183 neurons that were detected, 130 were found in the subthalamic nucleus, 30 in the substantia nigra and 23 in the globus pallidus. Twenty percent of the neurons in each of these structures showed eye movement-related activity. Neurons related to scanning eye movements were mostly unrelated to the visually guided saccades. We conclude that a relatively large number of basal ganglia neurons are involved in eye motion control. Surprisingly, neurons related to scanning eye movements differed from neurons activated during saccades suggesting functional specialization and segregation of both systems for eye movement control.