114 research outputs found

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

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    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

    Electro-oculography in the Field of Assistive Interaction Communication

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    There is sufficient evidence about feasible use of electrical bio signals in the field of Alternate Communication. Additionally, they are particularly suitable in the case of people with severe motor disorder, for example people with other physical disorder. Developing solutions for them involves different ways of using sensors that decides the user’s needs and limitations, which in turn converts the user’s intentions into commands. The system should be evaluated with an appropriate method. This paper submits alternative communication techniques used for communication using electrooculography technique. DOI: 10.17762/ijritcc2321-8169.15035

    Development of EOG Based Human Machine Interface Control System for Motorized Wheelchair

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    Abstract Rehabilitation devices are increasingly being used to improve the quality of the life of differentially abled people. Human Machine Interface (HMI) have been studied extensively to control electromechanical rehabilitation aids using biosignals such as EEG, EOG and EMG etc. among the various biosignals, EOG signals have been studied in depth due to the occurrence of a definite signal pattern. Persons suffering from extremely limited peripheral mobility like paraplegia or quadriplegia usually have the ability to coordinate eye movements. The current project focuses on the development of a prototype motor wheelchair controlled by EOG signals. EOG signals were used to generate control signals for the movement of the wheelchair. As a part of this work an EOG signal acquisition system was developed. The acquired EOG signal was then processed to generate various control signals depending upon the amplitude and duration of signal components. These control signals were then used to control the movements of the prototype motorized wheelchair model

    Applications of the electric potential sensor for healthcare and assistive technologies

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    The work discussed in this thesis explores the possibility of employing the Electric Potential Sensor for use in healthcare and assistive technology applications with the same and in some cases better degrees of accuracy than those of conventional technologies. The Electric Potential Sensor is a generic and versatile sensing technology capable of working in both contact and non-contact (remote) modes. New versions of the active sensor were developed for specific surface electrophysiological signal measurements. The requirements in terms of frequency range, electrode size and gain varied with the type of signal measured for each application. Real-time applications based on electrooculography, electroretinography and electromyography are discussed, as well as an application based on human movement. A three sensor electrooculography eye tracking system was developed which is of interest to eye controlled assistive technologies. The system described achieved an accuracy at least as good as conventional wet gel electrodes for both horizontal and vertical eye movements. Surface recording of the electroretinogram, used to monitor eye health and diagnose degenerative diseases of the retina, was achieved and correlated with both corneal fibre and wet gel surface electrodes. The main signal components of electromyography lie in a higher bandwidth and surface signals of the deltoid muscle were recorded over the course of rehabilitation of a subject with an injured arm. Surface electromyography signals of the bicep were also recorded and correlated with the joint dynamics of the elbow. A related non-contact application of interest to assistive technologies was also developed. Hand movement within a defined area was mapped and used to control a mouse cursor and a predictive text interface

    Physiological Approach To Characterize Drowsiness In Simulated Flight Operations During Window Of Circadian Low

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    Drowsiness is a psycho-physiological transition from awake towards falling sleep and its detection is crucial in aviation industries. It is a common cause for pilot’s error due to unpredictable work hours, longer flight periods, circadian disruption, and insufficient sleep. The pilots’ are prone towards higher level of drowsiness during window of circadian low (2:00 am- 6:00 am). Airplanes require complex operations and lack of alertness increases accidents. Aviation accidents are much disastrous and early drowsiness detection helps to reduce such accidents. This thesis studied physiological signals during drowsiness from 18 commercially-rated pilots in flight simulator. The major aim of the study was to observe the feasibility of physiological signals to predict drowsiness. In chapter 3, the spectral behavior of electroencephalogram (EEG) was studied via power spectral density and coherence. The delta power reduced and alpha power increased significantly (

    Design and Implementation of Wireless Point-Of-Care Health Monitoring Systems: Diagnosis For Sleep Disorders and Cardiovascular Diseases

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    Chronic sleep disorders are present in 40 million people in the United States. More than 25 million people remain undiagnosed and untreated, which accounts for over $22 billion in unnecessary healthcare costs. In addition, another major chronic disease is the heart diseases which cause 23.8% of the deaths in the United States. Thus, there is a need for a low cost, reliable, and ubiquitous patient monitoring system. A remote point-of-care system can satisfy this need by providing real time monitoring of the patient\u27s health condition at remote places. However, the currently available POC systems have some drawbacks; the fixed number of physiological channels and lack of real time monitoring. In this dissertation, several remote POC systems are reported to diagnose sleep disorders and cardiovascular diseases to overcome the drawbacks of the current systems. First, two types of remote POC systems were developed for sleep disorders. One was designed with ZigBee and Wi-Fi network, which provides increase/decrease the number of physiological channels flexibly by using ZigBee star network. It also supports the remote real-time monitoring by extending WPAN to WLAN with combination of two wireless communication topologies, ZigBee and Wi-Fi. The other system was designed with GSM/WCDMA network, which removes the restriction of testing places and provides remote real-time monitoring in the true sense of the word. Second, a fully wearable textile integrated real-time ECG acquisition system for football players was developed to prevent sudden cardiac death. To reduce power consumption, adaptive RF output power control was implemented based on RSSI and the power consumption was reduced up to 20%. Third, as an application of measuring physiological signals, a wireless brain machine interface by using the extracted features of EOG and EEG was implemented to control the movement of a robot. The acceleration/deceleration of the robot is controlled based on the attention level from EEG. The left/right motion of eyeballs of EOG is used to control the direction of the robot. The accuracy rate was about 95%. These kinds of health monitoring systems can reduce the exponentially increasing healthcare costs and cater the most important healthcare needs of the society

    Eye-tracking assistive technologies for individuals with amyotrophic lateral sclerosis

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    Amyotrophic lateral sclerosis, also known as ALS, is a progressive nervous system disorder that affects nerve cells in the brain and spinal cord, resulting in the loss of muscle control. For individuals with ALS, where mobility is limited to the movement of the eyes, the use of eye-tracking-based applications can be applied to achieve some basic tasks with certain digital interfaces. This paper presents a review of existing eye-tracking software and hardware through which eye-tracking their application is sketched as an assistive technology to cope with ALS. Eye-tracking also provides a suitable alternative as control of game elements. Furthermore, artificial intelligence has been utilized to improve eye-tracking technology with significant improvement in calibration and accuracy. Gaps in literature are highlighted in the study to offer a direction for future research

    Multimodal Wearable Sensors for Human-Machine Interfaces

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    Certain areas of the body, such as the hands, eyes and organs of speech production, provide high-bandwidth information channels from the conscious mind to the outside world. The objective of this research was to develop an innovative wearable sensor device that records signals from these areas more conveniently than has previously been possible, so that they can be harnessed for communication. A novel bioelectrical and biomechanical sensing device, the wearable endogenous biosignal sensor (WEBS), was developed and tested in various communication and clinical measurement applications. One ground-breaking feature of the WEBS system is that it digitises biopotentials almost at the point of measurement. Its electrode connects directly to a high-resolution analog-to-digital converter. A second major advance is that, unlike previous active biopotential electrodes, the WEBS electrode connects to a shared data bus, allowing a large or small number of them to work together with relatively few physical interconnections. Another unique feature is its ability to switch dynamically between recording and signal source modes. An accelerometer within the device captures real-time information about its physical movement, not only facilitating the measurement of biomechanical signals of interest, but also allowing motion artefacts in the bioelectrical signal to be detected. Each of these innovative features has potentially far-reaching implications in biopotential measurement, both in clinical recording and in other applications. Weighing under 0.45 g and being remarkably low-cost, the WEBS is ideally suited for integration into disposable electrodes. Several such devices can be combined to form an inexpensive digital body sensor network, with shorter set-up time than conventional equipment, more flexible topology, and fewer physical interconnections. One phase of this study evaluated areas of the body as communication channels. The throat was selected for detailed study since it yields a range of voluntarily controllable signals, including laryngeal vibrations and gross movements associated with vocal tract articulation. A WEBS device recorded these signals and several novel methods of human-to-machine communication were demonstrated. To evaluate the performance of the WEBS system, recordings were validated against a high-end biopotential recording system for a number of biopotential signal types. To demonstrate an application for use by a clinician, the WEBS system was used to record 12‑lead electrocardiogram with augmented mechanical movement information

    Event Fixation Related Potential During Visual Emotion Stimulation

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    Cílem této diplomové práce je najít a popsat souvislost mezi fixací očí v emočně zabarveném stimulu, kterým je obrázek či video, a EEG signálu. K tomuto studiu je třeba vyvinout softwarové nástroje v prostředí Matlab k úpravě a zpracování dat získaných z eye trackeru a propojení s EEG signály pomocí nově vytvořených markerů. Na základě získaných znalostí o fixacích, jsou v prostředí BrainVision Analyzeru EEG data zpracovány a následně jsou segmentovány a průměrovány jako evokované potenciály pro jednotlivé stimuly (ERP a EfRP). Tato práce je vypracována ve spolupráci s Gipsa-lab v rámci výzkumného projektu.This diploma thesis is a part of a ongoing research project concerning new joint technique of eye fixations and EEG. The goal of this work is to find and analyze a connection between eye fixation in a face expressing an emotion (static or dynamic). For this study certain software developments need to be done to adjust fixation data in Matlab and connect them to EEG signals with newly created markers. Based on the obtained information on fixations, EEG data are processed in BrainVision Analyzer and segmented to obtain ERPs and EfRPs for each stimuli.
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