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Individual-technology fit: Matching individual characteristics and features of biometric interface technologies with performance.

机译:适合个人技术:使生物识别接口技术的个人特征与功能与性能相匹配。

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The term biometric literally means "to measure the body", and has recently been associated with physiological measures commonly used for personal verification and security applications. In this work, biometric describes physiological measures that may be used for non-muscularly controlled computer applications, such as brain-computer interfaces. Biometric interface technology is generally targeted for users with severe motor disabilities which may last long-term due to illness or injury or short-term due to temporary environmental conditions. Performance with a biometric interface can vary widely across users depending upon many factors ranging from health to experience. Unfortunately, there is no systematic method for pairing users with biometric interface technologies to achieve the best performance. The current methods to accommodate users through trial-and-error result in the loss of valuable time and resources as users sometimes have diminishing abilities or suffer from terminal illnesses. This dissertation presents a framework and methodology that links user characteristics and features of biometric interface technologies with performance, thus expediting the technology-fit process. The contributions include an outline of the underlying components of capturing and representing individual user characteristics and the impact on the performance of basic interaction tasks using a methodology called biometric user profiling. In addition, this work describes a methodology for objectively measuring an individual's ability to control a specific biometric interface technology such as one based on measures of galvanic skin response or neural activity. Finally, this work incorporates these concepts into a new individual-technology fit framework for biometric interface technologies stemming from literature on task-technology fit.; Key words. user profiles, biometric user profiling, biometric interfaces, fit, individual-technology fit, galvanic skin response, functional near-infrared, brain-computer interface
机译:术语生物统计学从字面上意味着“测量身体”,并且最近与通常用于个人验证和安全应用的生理测量相关联。在这项工作中,生物特征描述了可用于非肌肉控制的计算机应用程序(例如脑机接口)的生理测量。生物识别接口技术通常针对患有严重运动障碍的用户,这些运动障碍可能由于疾病或受伤而长期持续,或者由于临时环境条件而短期持续。生物识别界面的性能在不同用户之间可能存在很大差异,具体取决于从健康到经验的许多因素。不幸的是,没有将用户与生物识别接口技术配对以实现最佳性能的系统方法。当前的通过反复试验为用户提供服务的方法会浪费宝贵的时间和资源,因为用户有时能力下降或患有绝症。本文提出了一种框架和方法,将生物特征接口技术的用户特征和特性与性能联系起来,从而加快了技术适应过程。这些贡献包括使用生物特征用户概要分析的方法捕获和表示单个用户特征的基本组件的概述,以及对基本交互任务性能的影响。此外,这项工作描述了一种方法,用于客观地测量个人控制特定生物识别接口技术的能力,例如基于皮肤电反应或神经活动的测量。最后,这项工作将这些概念纳入了新的个体技术适应框架,以用于生物统计接口技术,该框架源于有关任务技术适应的文献。关键字用户资料,生物特征用户配置文件,生物特征界面,拟合,个体技术拟合,皮肤电反应,功能近红外,脑机接口

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