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

Biosignal‐based human–machine interfaces for assistance and rehabilitation : a survey

As a definition, Human–Machine Interface (HMI) enables a person to interact with a device. Starting from elementary equipment, the recent development of novel techniques and unobtrusive devices for biosignals monitoring paved the way for a new class of HMIs, which take such biosignals as inputs to control various applications. The current survey aims to review the large literature of the last two decades regarding biosignal‐based HMIs for assistance and rehabilitation to outline state‐of‐the‐art and identify emerging technologies and potential future research trends. PubMed and other databases were surveyed by using specific keywords. The found studies were further screened in three levels (title, abstract, full‐text), and eventually, 144 journal papers and 37 conference papers were included. Four macrocategories were considered to classify the different biosignals used for HMI control: biopotential, muscle mechanical motion, body motion, and their combinations (hybrid systems). The HMIs were also classified according to their target application by considering six categories: prosthetic control, robotic control, virtual reality control, gesture recognition, communication, and smart environment control. An ever‐growing number of publications has been observed over the last years. Most of the studies (about 67%) pertain to the assistive field, while 20% relate to rehabilitation and 13% to assistance and rehabilitation. A moderate increase can be observed in studies focusing on robotic control, prosthetic control, and gesture recognition in the last decade. In contrast, studies on the other targets experienced only a small increase. Biopotentials are no longer the leading control signals, and the use of muscle mechanical motion signals has experienced a considerable rise, especially in prosthetic control. Hybrid technologies are promising, as they could lead to higher performances. However, they also increase HMIs’ complex-ity, so their usefulness should be carefully evaluated for the specific application

Dry EEG Electrodes

Electroencephalography (EEG) emerged in the second decade of the 20th century as a technique for recording the neurophysiological response. Since then, there has been little variation in the physical principles that sustain the signal acquisition probes, otherwise called electrodes. Currently, new advances in technology have brought new unexpected fields of applications apart from the clinical, for which new aspects such as usability and gel-free operation are first order priorities. Thanks to new advances in materials and integrated electronic systems technologies, a new generation of dry electrodes has been developed to fulfill the need. In this manuscript, we review current approaches to develop dry EEG electrodes for clinical and other applications, including information about measurement methods and evaluation reports. We conclude that, although a broad and non-homogeneous diversity of approaches has been evaluated without a consensus in procedures and methodology, their performances are not far from those obtained with wet electrodes, which are considered the gold standard, thus enabling the former to be a useful tool in a variety of novel applications.This work was supported by Nicolo Association for the R+D+i in Neurotechnologies for disability, the research project P11-TIC-7983, Junta of Andalucia (Spain) and the Spanish National Grant TIN2012-32030, co-financed by the European Regional Development Fund (ERDF). We also thank Erik Jung, head of the Medical Microsystems working group, at the Department of System Integration & Interconnection Technologies, Fraunhofer IZM (Berlin), for his support

EOG-Based Human–Computer Interface: 2000–2020 Review

Electro-oculography (EOG)-based brain-computer interface (BCI) is a relevant technology influencing physical medicine, daily life, gaming and even the aeronautics field. EOG-based BCI systems record activity related to users' intention, perception and motor decisions. It converts the bio-physiological signals into commands for external hardware, and it executes the operation expected by the user through the output device. EOG signal is used for identifying and classifying eye movements through active or passive interaction. Both types of interaction have the potential for controlling the output device by performing the user's communication with the environment. In the aeronautical field, investigations of EOG-BCI systems are being explored as a relevant tool to replace the manual command and as a communicative tool dedicated to accelerating the user's intention. This paper reviews the last two decades of EOG-based BCI studies and provides a structured design space with a large set of representative papers. Our purpose is to introduce the existing BCI systems based on EOG signals and to inspire the design of new ones. First, we highlight the basic components of EOG-based BCI studies, including EOG signal acquisition, EOG device particularity, extracted features, translation algorithms, and interaction commands. Second, we provide an overview of EOG-based BCI applications in the real and virtual environment along with the aeronautical application. We conclude with a discussion of the actual limits of EOG devices regarding existing systems. Finally, we provide suggestions to gain insight for future design inquiries

Hybrid Human-Machine Interface to Mouse Control for Severely Disabled People

This paper describes a hybrid human-machine interface, based on electro-oculogram (EOG) and electromyogram (EMG), which allows the mouse control of a personal computer using eye movement and the voluntary contraction of any facial muscle. The bioelectrical signals are sensed through adhesives electrodes, and acquired by a custom designed portable and wireless system. The mouse can be moved in any direction, vertical, horizontal and diagonal, by two EOG channels and the EMG signal is used to perform the mouse click action. Blinks are avoided by a decision algorithm and the natural reading of the screen is possible with a specially designed software. A virtual keyboard was used for the experiments with healthy people and with a severely disabled patient. The results demonstrate an intuitive and accessible control, evaluated in terms of performance, time for task execution and user´s acceptance. Besides, a quantitative index to estimate the training impact was computed with good results.Fil: López Celani, Natalia Martina. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; ArgentinaFil: Orosco, Eugenio Conrado. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Pérez Berenguer, María Elisa. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; ArgentinaFil: Bajinay, Sergio. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; ArgentinaFil: Zanetti, Roberto. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; ArgentinaFil: Valentinuzzi, Maximo. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentin

전자피부 어플리케이션을 위한 투명 키리가미 전극 개발

학위논문 (석사)-- 서울대학교 대학원 : 공과대학 기계공학부, 2019. 2. 고승환.For relieving the inconvenience while wearing electronic devices, stretchability and imperceptibility are essentially required characteristics for desired form of electronic-skin devices. Yet accomplishing these properties simultaneously is still challenging although some progress has been made on materials and structure designs. Here, we suggest a novel fabrication technique brining an idea from kirigami, Japanese ancient paper-cutting craft, to enable transparent and highly conductive electrodes to be deformable. By using facile and fast laser patterning process, we show transparent kirigami electrodes composed of silver nanowires partially embedded in ultra-thin colorless-polyimide film. Owing to rapid laser patterning method, versatile patterns are developed in few minutes under non-vacuum and room temperature condition. These patterns impart tunable elasticity to the electrodes, which can be stretched over 400% tensile strain with strain-invariant electrical property and also show good electromechanical stability even after 10,000 cycles of 400% stretching while exhibiting high optical transparency (more than 80%). In addition, gold coating on the exposed surface of silver nanowires ensure biocompatibility and improved electrical stability, preventing allergic reaction of skin and oxidation of the silver nanowires. The transparent kirigami electrodes with customizable elasticity pave the innovative way that offers facile construction of appropriate geometries for achieving multi-functional transparent and wearable electronic skin applications. The versatility of this work is demonstrated by ultra-stretchable transparent kirigami heater for personal thermal management and conformal transparent kirigami electrophysiology sensor for continuous health monitoring of human body conditions. Finally, by integrating electronic-skin sensors with a quadrotor, we have successfully demonstrated human-machine interface using our stretchable transparent kirigami electrodes.웨어러블 전자소자를 착용할 때 이질감을 최소화하기 위해 전자피부의 형태로서 사용되는 전극은 투명하여 눈에 잘 보이지 않아야 하고, 피부처럼 구부러지며 늘어날 수 있어야 한다. 하지만 전극의 재료와 구조적 측면에서 많은 연구가 진행되었음에도 여전히 투명하면서 늘어나는 전극을 구현하는 데 어려움이 많다. 본 논문에서는 이러한 어려움을 극복하기 위해 무색의 폴리이미드와 은 나노와이어를 기반으로 한 플렉서블 투명전극에 레이저 공정을 이용한 키리가미 패턴을 넣음으로써 스트레처블 투명전극을 구현하는 공정을 고안했다. 이를 바탕으로 본래 길이의 400%까지 늘이는 반복인장시험을 10,000회 이상 진행한 후에도 저항변화가 거의 없는 투명전극을 제작했다. 또한 드러난 은 나노와이어의 표면에 선택적으로 금을 코팅함으로써 전극의 산화를 방지하고 생체에 부착 및 착용하기에 적합할 수 있도록 했다. 본 연구에서는 이를 이용해 용도에 맞게 디자인된 키리가미 패턴을 가진 투명전극을 적용한 웨어러블 히터와 생체신호 측정센서를 제작했다. 더 나아가 근전도 센서를 양팔에 부착한 후 역동적인 움직임에 대응되는 근전도 신호를 읽어 쿼드로터를 조종하는 시스템을 구축함으로써 진보된 인간-기계 인터페이스를 구현했다.Chapter 1. Introduction 1 1.1. Study Background 1 1.2. Purpose of Research 3 Chapter 2. Experiment 5 2.1. Fabrication of Transparent Kirigami Electrodes 5 2.2. Synthesis of Silver Nanowires 7 2.3. Fabrication of AgNWs/cPI Electrodes 8 2.4. Laser Ablation Patterning Process 9 2.5. Gold Coating on The Exposed AgNWs 10 2.6. Finite Element Simulation 12 Chapter 3. Result 13 3.1. Characterization of Transparent Kirigami Electrodes 13 3.2. Highly Stretchable and Transparent Kirigami Heater 18 3.3. Conformal and Transparent Kirigami Electrophysiology Sensor 20 3.4. Human-Machine Interface for Controlling a Quadrotor 23 Chapter 4. Conclusion 26 References 27 Abstract in Korean 30Maste

Proposals and Comparisons from One-Sensor EEG and EOG Human-Machine Interfaces

[Abstract] Human-Machine Interfaces (HMI) allow users to interact with different devices such as computers or home elements. A key part in HMI is the design of simple non-invasive interfaces to capture the signals associated with the user’s intentions. In this work, we have designed two different approaches based on Electroencephalography (EEG) and Electrooculography (EOG). For both cases, signal acquisition is performed using only one electrode, which makes placement more comfortable compared to multi-channel systems. We have also developed a Graphical User Interface (GUI) that presents objects to the user using two paradigms—one-by-one objects or rows-columns of objects. Both interfaces and paradigms have been compared for several users considering interactions with home elements.Xunta de Galicia; ED431C 2020/15Xunta de Galicia; ED431G2019/01Agencia Estatal de Investigación de España; RED2018-102668-TAgencia Estatal de Investigación de España; PID2019-104958RB-C42Xunta de Galicia; ED481A-2018/156This work has been funded by the Xunta de Galicia (by grant ED431C 2020/15, and grant ED431G2019/01 to support the Centro de Investigación de Galicia “CITIC”), the Agencia Estatal de Investigación of Spain (by grants RED2018-102668-T and PID2019-104958RB-C42) and ERDF funds of the EU (FEDER Galicia & AEI/FEDER, UE); and the predoctoral Grant No. ED481A-2018/156 (Francisco Laport

EMG-based eye gestures recognition for hands free interfacing

This study investigates the utilization of an Electromyography (EMG) based device to recognize five eye gestures and classify them to have a hands free interaction with different applications. The proposed eye gestures in this work includes Long Blinks, Rapid Blinks, Wink Right, Wink Left and finally Squints or frowns. The MUSE headband, which is originally a Brain Computer Interface (BCI) that measures the Electroencephalography (EEG) signals, is the device used in our study to record the EMG signals from behind the earlobes via two Smart rubber sensors and at the forehead via two other electrodes. The signals are considered as EMG once they involve the physical muscular stimulations, which are considered as artifacts for the EEG Brain signals for other studies. The experiment is conducted on 15 participants (12 Males and 3 Females) randomly as no specific groups were targeted and the session was video taped for reevaluation. The experiment starts with the calibration phase to record each gesture three times per participant through a developed Voice narration program to unify the test conditions and time intervals among all subjects. In this study, a dynamic sliding window with segmented packets is designed to faster process the data and analyze it, as well as to provide more flexibility to classify the gestures regardless their duration from one user to another. Additionally, we are using the thresholding algorithm to extract the features from all the gestures. The Rapid Blinks and the Squints were having high F1 Scores of 80.77% and 85.71% for the Trained Thresholds, as well as 87.18% and 82.12% for the Default or manually adjusted thresholds. The accuracies of the Long Blinks, Rapid Blinks and Wink Left were relatively higher with the manually adjusted thresholds, while the Squints and the Wink Right were better with the trained thresholds. However, more improvements were proposed and some were tested especially after monitoring the participants actions from the video recordings to enhance the classifier. Most of the common irregularities met are discussed within this study so as to pave the road for further similar studies to tackle them before conducting the experiments. Several applications need minimal physical or hands interactions and this study was originally a part of the project at HCI Lab, University of Stuttgart to make a hands-free switching between RGB, thermal and depth cameras integrated on or embedded in an Augmented Reality device designed for the firefighters to increase their visual capabilities in the field

Forehead EEG in Support of Future Feasible Personal Healthcare Solutions: Sleep Management, Headache Prevention, and Depression Treatment

© 2013 IEEE. There are current limitations in the recording technologies for measuring EEG activity in clinical and experimental applications. Acquisition systems involving wet electrodes are time-consuming and uncomfortable for the user. Furthermore, dehydration of the gel affects the quality of the acquired data and reliability of long-term monitoring. As a result, dry electrodes may be used to facilitate the transition from neuroscience research or clinical practice to real-life applications. EEG signals can be easily obtained using dry electrodes on the forehead, which provides extensive information concerning various cognitive dysfunctions and disorders. This paper presents the usefulness of the forehead EEG with advanced sensing technology and signal processing algorithms to support people with healthcare needs, such as monitoring sleep, predicting headaches, and treating depression. The proposed system for evaluating sleep quality is capable of identifying five sleep stages to track nightly sleep patterns. Additionally, people with episodic migraines can be notified of an imminent migraine headache hours in advance through monitoring forehead EEG dynamics. The depression treatment screening system can predict the efficacy of rapid antidepressant agents. It is evident that frontal EEG activity is critically involved in sleep management, headache prevention, and depression treatment. The use of dry electrodes on the forehead allows for easy and rapid monitoring on an everyday basis. The advances in EEG recording and analysis ensure a promising future in support of personal healthcare solutions