Construction of neural nets in brain-computer interface for robot arm steering

Plechawska–Wójcik, Małgorzata; Wolszczak, Piotr; Cechowicz, Radosław; Łygas, Krystian

doi:10.1109/hsi.2016.7529656

Cited by 7 publications

(6 citation statements)

References 26 publications

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“…Expectations about performance, effort, and social acceptance positively influence the intent to use mobilepayment systems. Koenig-Lewis et al [64] use the Unified Technology Acceptance and Use Theory (UTAUT) as a base, to extend the framework by combining variables such as perceived enjoyment, social effect, knowledge, and perceived risk. Expected effort positively influences expectations about performance, and behavioral intention Tiago 2016.…”

Section: Expected Effortmentioning

confidence: 99%

Factors Affecting the Use of Facial-Recognition Payment: An Example of Chinese Consumers

Zhang

Kang

2019

IEEE Access

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The emergence and use of facial-recognition payment technology has brought new challenges. Although credit-card payment is quick and easy, it is easy to lose a card or forget the password. Because people use simple passwords and reuse them on different accounts and services, passwords can be shared and cracked. QR payment is inseparable from smart phones, smart phones may be lost, signals may be unstable, and batteries may be exhausted. However, facial-recognition technology, which detects and describes feature vectors without physical contact, directly contributes to overall efficiency, performance, and accuracy. Currently, studies of technical issues of facial-recognition technology and facial-recognition payment systems are very popular. There are many studies that emphasize the working principle of the facial-recognition system, the system's reliability, and the future development trend. However, for non-technical issues, such as from the perspective of consumers, research on the characteristics of facial-recognition payment and the factors affecting consumer's intent to use is rare. Therefore, the purpose of this study is to explore the factors influencing consumers' willingness to use facial-recognition payment systems. This study has selected security, visibility, and expected effort and social image as the feature variables of the facial-recognition payment system. Results in this paper shows that the safety, security, visibility and social image will affect consumers' intent to use the system. It can also influence consumers' intent to use through perceived usefulness. The amount of effort expected not only has direct influence on intent to use but also influences the intent to use by the mediating factor of perceived usefulness. In this article, Openness characteristic (consumer's personality) has a moderating effect on the relationship between security, expected effort and usage intention. INDEX TERMS Facial-recognition payment system, perceived usefulness, openness, intent to use.

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Section: Expected Effortmentioning

confidence: 99%

Factors Affecting the Use of Facial-Recognition Payment: An Example of Chinese Consumers

Zhang

Kang

2019

IEEE Access

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“…The output commands varied depending on the control object and included movements such as turning left and right, going forward and backward, lifting and dropping, and flexion and extension of the hand fingers. These studies demonstrate the potential of BCIs in enabling individuals with motor impairments to control robots and devices through their thoughts, opening up possibilities for assistive technology and neurorehabilitation [55][56][57][58][59][60][61][62][63][64][65][66][67][68].…”

Section: Resultsmentioning

confidence: 77%

Brain Computer Interfaces: The Future of Communication Between the Brain and the External World

ALMofleh,

Alseddiqi,

Najam

et al. 2023

Sci. Eng. Technol.

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This paper provides a comprehensive review of the current state of research on Brain Computer Interfaces (BCIs) and their potential applications. The objective of this study was to gather information from various sources, including journal articles, conference papers, and books, to analyze the advancements and limitations of BCIs. A systematic literature review was conducted using databases such as PubMed, IEEE Xplore, and Google Scholar, with specific keywords related to BCIs and their applications. The selected studies were thoroughly analyzed to identify common themes, methodologies, and key findings. The main contributions of this review include an overview of different types of BCIs, their applications in fields such as medicine, entertainment, and education, and the challenges and limitations faced by BCI technology. The findings highlight the potential of BCIs in restoring motor function, improving the quality of life for individuals with various conditions, and enhancing human-technology interaction. Furthermore, the review identifies future research directions, including signal processing improvements, exploring hybrid and multimodal approaches, conducting long-term real-world studies, addressing ethical considerations, and prioritizing user-centred design. This comprehensive analysis of existing literature provides valuable insights for researchers and practitioners in the field of BCIs and sets the stage for future advancements in this rapidly evolving domain.

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“…The use of quaternions or rotation vectors (in simplified case) simplifies the calculations and makes possible to include measurements from more than one axis, which results in better statistical properties of the signal, or allows to easily incorporate inertial measurement in tracking applications like robot arm steering [17].…”

Section: Resultsmentioning

confidence: 99%

Indoor mobile robot attitude estimation with MEMS gyroscope

Cechowicz

2017

ITM Web Conf.

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Abstract.A method of attitude estimation with a low-cost, strap-on MEMS sensor was proposed in the article. The method relies on dynamic gyroscope bias change estimation and updates during detected stops of the robot. The algorithm has been tested in laboratory with iRobot Roomba robot and should be improved to be useful in an industrial environment. The measurement of attitude of a mobile platform is necessary for correct navigation, especially in autonomous vehicles, which use dead reckoning between position updates from external sources. Since the system is intended to operate indoors, in industrial halls and shops, it cannot avail of GPS and Earth magnetic field sensors because of anomalies, which are common inside the steel constructions. Therefore, the accuracy of the gyroscope-based attitude estimation is significant. The proposed method aims to address the common problem of gyroscope bias drift, by dynamic update of sensor bias and simultaneous use of all gyroscope axes, to improve the quality of the measurements. A popular 3-axial gyroscope and 3-axial accelerometer sensors were used during the test runs. Obtained results suggest that it is possible to improve short-term accuracy of inertial dead reckoning, to get a system that could be of practical use in industrial AGV systems or intelligent vehicles.

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Construction of neural nets in brain-computer interface for robot arm steering

Cited by 7 publications

References 26 publications

Factors Affecting the Use of Facial-Recognition Payment: An Example of Chinese Consumers

Factors Affecting the Use of Facial-Recognition Payment: An Example of Chinese Consumers

Brain Computer Interfaces: The Future of Communication Between the Brain and the External World

Indoor mobile robot attitude estimation with MEMS gyroscope

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