Graphene textiles towards soft wearable interfaces for electroocular remote control of objects

Study of eye movements (EMs) and measurement of the resulting biopotentials, referred to as electrooculography (EOG), may find increasing use in applications within the domain of activity recognition, context awareness, mobile human-computer interaction (HCI) applications, and personalized medicine provided that the limitations of conventional “wet” electrodes are addressed. To overcome the limitations of conventional electrodes, this work, reports for the first time the use and characterization of graphene-based electroconductive textile electrodes for EOG acquisition using a custom-designed embedded eye tracker. This self-contained wearable device consists of a headband with integrated textile electrodes and a small, pocket-worn, battery-powered hardware with real-time signal processing which can stream data to a remote device over Bluetooth. The feasibility of the developed gel-free, flexible, dry textile electrodes was experimentally authenticated through side-by-side comparison with pre-gelled, wet, silver/silver chloride (Ag/AgCl) electrodes, where the simultaneously and asynchronous recorded signals displayed correlation of up to ~87% and ~91% respectively over durations reaching hundred seconds and repeated on several participants. Additionally, an automatic EM detection algorithm is developed and the performance of the graphene-embedded “all-textile” EM sensor and its application as a control element toward HCI is experimentally demonstrated. The excellent success rate ranging from 85% up to 100% for eleven different EM patterns demonstrates the applicability of the proposed algorithm in wearable EOG-based sensing and HCI applications with graphene textiles. The system-level integration and the holistic design approach presented herein which starts from fundamental materials level up to the architecture and algorithm stage is highlighted and will be instrumental to advance the state-of-the-art in wearable electronic devices based on sensing and processing of electrooculograms

Graphene smart textile-based wearable eye movement sensor for electro-ocular control and interaction with objects

Wearable graphene textile embedded smart headband and its feasibility in electrooculography (EOG) applications is demonstrated by benchmarking against clinical Ag/AgCl wet electrodes; where the recorded biopotentials displayed excellent correlation of 91.3% over durations up to hundred seconds. Automatic eye movement (EM) detection is implemented and performance of the grapheneembedded "all-textile" eye movement sensor and its application as a control element toward human-computer interaction (HCI) and human-machine interfaces (HMI) is experimentally demonstrated by: 1) generating digital clock transitions directly from eye blinks for facilitating switching requirements in HCI/HMI applications, 2) controlling and sequentially lighting up a single LED in a 5 x 5 LED array in four directions to draw a pattern of "8", 3) evaluating the limits of the entire system in an hour-long EOG recording session which includes several activities like checking a phone, watching a video, reading, and performing several EMs including blinks, saccades, and fixations. The excellent success rate ranging from 85% up to 100% for eleven different EM patterns demonstrates the applicability of the proposed algorithm in wearable EOG-based sensing and HCI/HMI applications with graphene textiles. The system-level integration and the holistic design approach presented herein which starts from fundamental materials level up to the architecture and algorithm stage is highlighted and will be instrumental to advance the state-of-the-art in wearable electronic devices

Graphene-coated wearable textiles for EOG-based human-computer interaction

Electrooculography (EOG) is a well-known approach to analyze eye movement features. Applications of EOG can be found in various areas including medical diagnosis, neurosciences, control systems, sensors and interfaces for human-computer interaction (HCI). However, standard gelbased electrodes limit wearability and portability which hinder the development of long-term EOG monitoring applications. To overcome these limitations, we have employed graphene-coated fabric electrodes as suitable alternatives for the currently used silver/silver chloride (Ag/AgCl)“wet” electrodes. Proof of the concept is provided by side by side comparison of conventional electrodes and fabric electrodes in automatic blink detection with sequential multi-step thresholding algorithm. Additionally, the EOG biopotentials are converted into real-time digital signals which could be used as clock signals to facilitate the development of HCI applications

Electrooculography by wearable graphene textiles

Study of eye movements and measurement of the resulting biopotentials, referred to as electrooculography (EOG), may find increasing use in applications within the domain of personalized medicine provided that the limitations of conventional "wet" electrodes are addressed. To overcome the limitations of conventional electrodes, in this paper, we report for the first time the use and characterization of graphene-coated electroconductive textile electrodes for EOG acquisition. The feasibility of the developed gel-free, flexible, dry textile electrodes was experimentally authenticated through side-by-side comparison with pre-gelled, wet, silver/silver chloride (Ag/AgCl) electrodes, where the simultaneously recorded signals displayed correlation of up to similar to 87% over durations reaching hundred seconds and repeated on eight participants. This outstanding performance demonstrates the potential of graphene textiles in wearable devices based on sensing and processing of electrooculograms

Analysis of pitot tube airflow velocity sensor behavior in blockage situations

Several airplanes crashes throughout the past decades are linked to the failure of the airplane flow velocity sensor known as pitot device or pitot tube. The study of its behavior in blockage, either due to human errors or due to environmental factors, could be valuable in the development of safer, more sustainable, and robust velocity sensors with improved performance. This work aims to look into this widely used but not very widely studied sensor and presents a three-dimensional model of a pitot device along with its analysis when either one of its ports is blocked. Results show that in blockage condition pitot tubes can overestimate the velocity up to ∼ %5.6

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 (HCl/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 degrees turns were successfully achieved with perfect pattern detection accuracies of 100% and 98%, respectively

Gel-free wearable electroencephalography (EEG) with soft graphene textiles

Attaching rigid wearables to ones skin may be socially challenging to be accustomed since their wearers may feel vulnerable with compromising their privacy, especially if the device is for tracking neurological or medical conditions. The development of flexible, long-term wearable, conductive nanomaterials with high fidelity can enable continuous and socially discrete ambulatory electroencephalography (EEG) since the sensing materials are the garment fibers themselves (i.e., 3rd generation intelligent clothing), not a rigid device. Here we introduce graphene-based electronic iles (e-ile) sensors in series of proof of principle experiments to record brain waves, including alpha rhythms activity, merely from the forehead and achieved an impressive correlation of ~ 91% in benchmarking with commercial dry electrodes

Smart armband with graphene textile electrodes for EMG-based muscle fatigue monitoring

We report the successful acquisition of surface electromyography (sEMG) signals from an intelligent armband and its application in localized muscle fatigue monitoring with a costume-designed, small-scale front-end readout circuitry. The correlation coefficient of the graphene-based ile electrodes in benchmarking against Ag/AgCl electrodes is recorded to be ~ 97%. SNR values for Ag/AgCl and graphene ile electrodes were 15.9 dB and 14.3 dB, respectively. The muscle fatigue experiment was an isometric contraction conducted on the right biceps brachii of subjects. The recorded signal showed indications of localized muscle fatigue with an apparent increase in the total band energy and decreased instantaneous median frequency (IMF) with linear regression slopes of 0.0082 mV2/s and -0.19 Hz/s, respectively. Recorded promising results show that graphene iles can be applied as practical sensing elements for wearable sEMG acquisition and enable novel applications such as muscle fatigue monitoring

Wearable graphene textile-enabled EOG sensing

Electrooculogram (EOG) is a measurement technique to record the biopotential signals induced by eyeball movement and EOG signals are critical for the development of wearable medical sensors and also interfaces for human-computer interaction. Unlike traditional "wet" electrodes which profoundly hinder the development of wearable EOG sensors, in this study, we report for the first time the use of graphene-coated fabric electrodes for EOG acquisition and overcome the limitations of conventional "wet" electrodes. We demonstrate the proof-of-concept of graphene textile electrodes for EOG acquisition with side-by-side comparison to conventional Ag/AgCl electrodes