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2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Pant, Suman Bhat, Niyati Shobana, G. Sindhuja, R. Lekha, D. Srimathi, S. School of CA & IT Shri Guru Ram Rai University India B.E Computer engineering University of Mumbai Mumbai India Department of Computer Applications College of Science and Humanities SRM Institute of Science and Technology Kattankulathur India Department of Medical Electronics Saveetha Engineering college India CSE Department R.M.K. College of Engineering and Technology India Department of Bio Technology Saveetha School of Engineering SIMATS Tamilnadu Chennai India

ISBN: (纸本)9798350340235

human Gait Recognition (HGR) is a biometric system that is exploited for security purpose over the past few years. The efficiency of gait detection is affected by different features namely walking surfaces, wearing clothes, and carrying a bag. Moreover, detection from divergent views is a complicated problem in HGR. Numerous approaches were proposed for HGR using classical and DL methods but the conventional technique is not appropriate for massive data. This study leverages Ensemble Learning Model for human Gait Recognition in human computer interface (ELMHGA-HCI) technique. The ELMHGA-HCI technique intends to recognize various kinds of human gaits to assist HCI applications. In the ELMHGA-HCI technique, Time Domain (TD) and Frequency Domain (FD) features from the input signals. For gait recognition, an ensemble of three DL models takes place namely Bidirectional Long Short Term Memory (BiLSTM), Gated Recurrent Unit (GRU) and Recurrent Neural Network (RNN). To exhibit the enhancedgait recognition results of the ELMHGA-HCI technique, a widespread simulation analysis is done. The simulation outcomes pointed out the enhanced performance of the ELMHGA-HCI approach over other existing techniques. © 2023 IEEE.

关键词： Activity recognition Deep learning Ensemble learning Gait recognition human computer interface

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Investigation of Appropriate Classification Method for EOG Based human computer interface 30

Investigation of Appropriate Classification Method for EOG B...

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30th IEEE Signal Processing and Communications Applications Conference (SIU)

作者： Al-Zubaidi, Muna Layth Abdulateef Aras, Selim Ondokuz Mayis Univ Elekt Elekt Muhendisligi Samsun Turkey

ISBN: (数字)9781665450928

ISBN: (纸本)9781665450928

The reason why real feelings and mood changes can be seen through our eyes is that the eyes provide the most revealing and accurate information of all human communication signs. It is possible to control a human- computer interface by voluntarily moving the eyes, which have an important place in communication. In this study, the appropriate feature and classification methods were investigated to use the Electooculography signs obtained from seven different voluntary eye movements in the human-computer interface. The success of the system is increased by determining the combination that gives the best result from many features by using the sequential forward feature selection method. The developed method reached 93.9% success in the seven-class dataset. The results show that humancomputer interface control can be done with high accuracy with voluntary eye movements. Also, the development of a real-time working model is inspiring for work.

关键词： electrooculogram human computer interface classification

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Impact of Technical CRM on Ethiopia Bank human-computer interface and Competitive Advantage as Mediators of Performance 5

Impact of Technical CRM on Ethiopia Bank Human-Computer Inte...

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5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Jabo, Dawit Borji, Berhanu Kant, Shashi Bule Hora University Department of Marketing Ethiopia Hawassa University Department of Management Ethiopia Bule Hora University Department of Management Ethiopia

ISBN: (纸本)9798350383522

Banks through human computer interface (HCI) can better understand and predict the demands of both present and potential clients with the use of technical customer relationship management. According to the current study, a bank's performance is not immediately impacted by the mere adoption of technical CRM. This study aims to demonstrate how the bank may build effective technological CRM, which ultimately leads to bank success, with the assistance of competitive advantage (CA) and human computer interface (HCI). Through the use of factor analysis both confirmatory and exploratory researchers manifested the data normality and latent determinants determination. Structural equation mediation model (SEM) based on Baron and Kenny technique was employed to test the mediation of HCI and CA, this study suggests optimize the technical customer relationship management efficiency through serial mediation of HCI and CA. This study has been carried out in Ethiopian commercial banks to obtain a more comprehensive understanding and improvement of the existing technical CRM deployment. © 2024 IEEE.

关键词： Competitive Advantage Ethiopia Bank Performance human computer interface Technical CRM

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Toward a mexican sign language system using human computer interface

Toward a mexican sign language system using human computer i...

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2019 International Conference on Mechatronics, Electronics and Automotive Engineering, ICMEAE 2019

作者： Estrivero-Chavez, C.R. Contreras-Teran, M.A. Miranda-Hernandez, J.A. Cardenas-Cornejo, J.J. Ibarra-Manzano, M.A. Almanza-Ojeda, D.L. Dicis - Universidad de Guanajuato Electronics Eng. Department Palo Blanco s/n Salamanca Guanajuato Mexico

ISBN: (纸本)9781728160375

This article presents a new algorithm that serves as support for people interested in learning sign language base on the Mexican Sign Language Dictionary provided by the CONAPRED (National Council to Prevent Discrimination) in the 2011 edition. The system uses the Leap Motion machine shadow interaction system to capture the position of each finger of both hands, and by geometric modeling up to 27 signs can be statically modeled with an accuracy of 99.80%. © 2019 IEEE.

关键词： Clasifier human computer interface Mexican Sign Language SVM Training System

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Offline Analysis for Designing Electrooculogram Based human computer interface Control for Paralyzed Patients

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IEEE ACCESS 2018年 6卷 79151-79161页

作者： Gu Jialu Ramkumar, S. Emayavaramban, G. Thilagaraj, M. Muneeswaran, V. Rajasekaran, M. Pallikonda Hussein, Ahmed Faeq Nanjing Univ Chinese Med Dept Econ Nanjing 210046 Jiangsu Peoples R China Kalasalingam Acad Res & Educ Sch Comp Krishnankoil 626126 India Karpagam Acad Higher Educ Dept Elect & Elect Engn Coimbatore 641021 Tamil Nadu India Kalasalingam Acad Res & Educ Sch Elect & Elect Technol Krishnankoil 626126 India Al Nahrain Univ Biomed Engn Dept Coll Engn Baghdad 10072 Iraq

Currently, majority of persons were immobilized and need aid from caretakers due to disability. To reduce and overcome such problem, there was a need for developing human-computer interface (HCI) with the help of biosignals. In this paper, we propose a two-channel elecctrooculograpy (EOG)-based HCI to encourage the contact ability as well as value of life for paralyzed persons who cannot speak or shift their extremity by using 20 subjects with the help of ADT26 Bio amplifier. EOG signals were collected for 11 tasks from both vertical and horizontal eye movement by using gold-platted electrodes. The extracted EOG signals were processed with convolution and Plancherel theorem to obtain the features. Layered recurrent neural network (LRNN) was implemented to analyze the extracted features and then converted into a sequence of commands to control the HCI. A graphical user interface was developed using MATLAB to help a user to convey their thoughts. This paper shows an average classification accuracy of 90.72% for convolution features and 91.28% for Plancherel features. Off-line single trail analysis was also performed to analyze the recognition accuracy of the proposed HCI system. The off-line analysis displayed that Plancherel features using LRNN were high compared to convolution features using LRNN. From this paper, we found that LRNN architecture using Plancherel features was more suitable for developing EOG-based HCI. Single trail analysis was conducted to identify the recognizing accuracy in offline. The off-line results indicated that in comparison with other EOG-based HCI systems, our system was user friendly and needs minimum training to operate.

关键词： Elecctrooculograpy human computer interface layered recurrent neural network amyotrophic lateral sclerosis

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Wearable human computer interface for Control within Immersive VAMR Gaming Environments Using Data Glove and Hand Gestures

Wearable Human Computer Interface for Control within Immersi...

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IEEE Games, Entertainment, Media Conference (GEM)

作者： Wilk, Mariusz P. Torres-Sanchez, Javier Tedesco, Salvatore O'Flynn, Brendan Univ Coll Cork Tyndall Natl Inst Cork Ireland

ISBN: (纸本)9781538663042

The continuous advances in the state-of-the-art in the Virtual, Augmented, and Mixed Reality (VAMR) technology are important in many application spaces, including gaming, entertainment, and media technologies. VAMR is part of the broader human-computer interface (HCI) area focused on providing an unprecedentedly immersive way of interacting with computers. These new ways of interacting with computers can leverage the emerging user input devices. In this paper, we present a demonstrator system that shows how our wearable Virtual Reality (VR) Glove can be used with an off-the-shelf head-mounted VR device, the RealWear HMT-1 (TM). We show how the smart data capture glove can be used as an effective input device to the HMT-1 (TM) to control various devices, such as virtual controls, simply using hand gesture recognition algorithms. We describe our fully functional proof-of-concept prototype, along with the complete system architecture and its ability to scale by incorporating other devices.

关键词： Virtual Reality Augmented Reality Mixed Reality human computer interface VR Glove RealWear HMT-1 (TM) Hand Gesture Recognition Control Immersive Environment

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An Arduino based Gesture Control System for human-computer interface 4

An Arduino based Gesture Control System for Human-Computer I...

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4th International Conference on Computing Communication Control and Automation (ICCUBEA)

作者： Belgamwar, Shravani Agrawal, Sahil Savitribai Phule Pune Univ Sinhgad Coll Engn Dept Comp Engn Pune Maharashtra India

ISBN: (纸本)9781538652572

The basic goal of human computer Interaction System is to improve the interaction between users and computers by making the computer more receptive to user needs. human computer Interaction with a personal computer is not just limited to keyboard and mouse interaction today. Interaction between humans comes from different sensory modes like gesture, speech, facial and body expressions. The paper presents a literature survey conducted which provides an insight into the different methods that can be adopted and implemented to achieve hand gesture recognition. It also helps in understanding the advantages and disadvantages associated with the various techniques. Further, in this paper, we have proposed a cost-effective gesture recognition system that translates the detected gestures into actions. The system has two interfaces, the distance sensor interface and the accelerometer interface. The distance sensor interface translates the gestures for actions such as shuffling between different applications, volume control, scrolling, keyboard short-cuts and so on;while the accelerometer interface realizes the typing part of the system.

关键词： gesture control human computer interface ultrasonic distance sensor accelerometer

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Using the Technology Acceptance Model to Understand Behavioral Intentions in the Use of a human computer interface (HCI) System

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INTERNATIONAL JOURNAL OF ENGINEERING EDUCATION 2017年第1期33卷 121-127页

作者： Shyr, Wen-Jye Feng, Chi-Feng Liu, Po-Wen Chiang, Tsung-Lin Su, Te-Jen Natl Changhua Univ Educ Dept Ind Educ & Technol 1 Jin De Rd Changhua 500 Taiwan Natl Taiwan Univ Dept Elect Engn Taipei Taiwan Natl Kaohsiung Univ Appl Sci Dept Elect Engn Kaohsiung 80778 Taiwan Kaohsiung Med Univ Grad Inst Clin Med Kaohsiung Taiwan

This study presents the technology acceptance model to assist universities in predicting the behavioral intentions associated with the use of a human computer interface system for learning. A total of 41 students responded to a survey following the completion of an eight-week teaching course. Data were collected to examine the path relationships among all variables (perceived usefulness, perceived ease of use, attitude toward use, and behavioral intention to use) influencing the acceptance of the system learning. The partial least squares method was used to test the measurement and the structural model. Path analysis verified that acceptance of the human computer interface system was directly influenced by the learner's "attitude toward use'' and "perceived usefulness.'' Rich content and the ease of use should be the focus when designing systems for university students, due to their effects on the behavioral intentions of students.

关键词： technology acceptance model human computer interface

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A practical efficient human computer interface based on saccadic eye movements for people with disabilities

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computerS IN BIOLOGY AND MEDICINE 2016年 70卷 163-173页

作者： Soltani, Sima Mahnam, Amin Univ Isfahan Dept Biomed Engn Fac Engn Hezar Jirib Ave Esfahan Iran

human computer interfaces (HCI) provide new channels of communication for people with severe motor disabilities to state their needs, and control their environment. Some HCI systems are based on eye movements detected from the electrooculogram. In this study, a wearable HCI, which implements a novel adaptive algorithm for detection of saccadic eye movements in eight directions, was developed, considering the limitations that people with disabilities have. The adaptive algorithm eliminated the need for calibration of the system for different users and in different environments. A two-stage typing environment and a simple game for training people with disabilities to work with the system were also developed. Performance of the system was evaluated in experiments with the typing environment performed by six participants without disabilities. The average accuracy of the system in detecting eye movements and blinking was 82.9% at first tries with an average typing rate of 4.5 cpm. However an experienced user could achieve 96% accuracy and 7.2 cpm typing rate. Moreover, the functionality of the system for people with movement disabilities was evaluated by performing experiments with the game environment. Six people with tetraplegia and significant levels of speech impairment played with the computer game several times. The average success rate in performing the necessary eye movements was 61.5%, which increased significantly with practice up to 83% for one participant. The developed system is 2.6 x 4.5 cm in size and weighs only 15 g, assuring high level of comfort for the users. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： People with disabilities Electro-oculogram human computer interface Saccadic eye movement Wearable systems

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Multiple Fingertip Detection under Single Camera with human computer interface Applications 5

Multiple Fingertip Detection under Single Camera with Human ...

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5th IEEE Global Conference on Consumer Electronics

作者： Cheng, Hsu-Yung Natl Cent Univ Dept Comp Sci & Informat Engn Taoyuan Taiwan

ISBN: (纸本)9781509023332

This work proposes an accurate marker-less fingertip detection method under single camera. The moving skin regions are analyzed via enhanced mixture models. The models with adaptive learning rates can separate the backgrounds and moving skins effectively. For multiple fingertip detection, we propose an algorithm based on the likelihood computation of contour and curvature information. Furthermore, finger width validation and error correction via temporal information is used to improve the detection accuracy. The experiments have shown that the proposed method is robust and flexible. Finally, we implement a human computer interface system to test the effectiveness of the proposed framework.

关键词： Fingertip Detection human computer interface Skin Region Analysis Enhanced Mixture Models

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