Discrimination of Neutral Postures in Computer Based Work.

机译：计算机基础工作中的中立姿态辨析。

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A biometric system recognizes users based on the way they physically interact with the system. In this work, we discover a common behavior that a typist consistently displays in non-trivial computer work. We sought to demonstrate three objectives: first, compelling proof that a user can be actively recognized over the course of a lengthy task via a neutral posture struck multiple times in that task; two, a sensing concept for capturing the neutral posture, and, third, an objective method for determine the level of work performed by each typist. This thesis develops a model for hand tracking using a simple ellipse to describe the neutral posture where a typist pauses before typing. Initial results of a group of 10 users indicate that the neutral posture can be established with only a few seconds of training data and can perform with approximately 92.1% accuracy. Analysis of the typed text determined the complexity of the typists' work using Bloom's Taxonomy - a taxonomy based on verb usage; parsed verb phrases indicated the level of competency that the users endeavored to demonstrate. This competency or expertise may further distinguish users and their performance in their most engaging work.

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作者
A. R. Keith;
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年度 2013
页码 1-96
总页数 96
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Biometric authentication systems; Biometry; Blooms taxonomy; Competency; Computers; Discrimination; Ellipses; Hand tracking; Image processing; Neutral; Neutral positions; Physical properties; Posture(General); Set positions; Taxonomy;

机译：生物识别认证系统;生物测定;绽放分类;能力;计算机;歧视;椭圆;手部跟踪;图像处理;中立;中立位置;物理特性;姿势（一般）;设置位置;分类;

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2. Wavelet-based tachycardia discrimination in ICDs: Impact of posture and electrogram configuration. [J] . Wolber T, Binggeli C, Holzmeister J, PACE: Pacing and clinical electrophysiology . 2006,第11期

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4. Automated Postural Ergonomic Assessment Using a Computer Vision-Based Posture Classification [C] . JoonOh Seo, Kaiqi Yin, SangHyun Lee Construction research congress . 2016

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5. Discrimination between Neutral and Unsafe Stimuli, Return of Fear, and Anxiety [D] . Staples, Lindsay Katharine 2019

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6. The Effect of The Forward Head Posture on Postural Balance in Long Time Computer Based Worker [O] . Jung-Ho Kang, Rae-Young Park, Su-Jin Lee, 2012

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7. EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed TarekShahriar Abstract—An EMD-chaos based approach is proposed todiscriminate EEG signals corresponding to healthy persons,and epileptic patients during seizure-free intervals and seizureattacks. An electroencephalogram (EEG) is first empiricallydecomposed to intrinsic mode functions (IMFs). The nonlineardynamics of these IMFs are quantified in terms of the largestLyapunov exponent (LLE) and correlation dimension (CD).This chaotic analysis in EMD domain is applied to a large groupof EEG signals corresponding to healthy persons as well asepileptic patients (both with and without seizure attacks). It isshown that the values of the obtained LLE and CD exhibitfeatures by which EEG for seizure attacks can be clearlydistinguished from other EEG signals in the EMD domain.Thus, the proposed approach may aid researchers in developingeffective techniques to predict seizure activities. Index Terms—Electroencephalogram (EEG), empiricalmode decomposition (EMD), largest Lyapunov exponent (LLE),correlation dimension (CD), epileptic seizures. The Authors are with the Electrical and Electronic EngineeringDepartment, Bangladesh University of Engineering and Technology,Dhaka-1000, Bangladesh (e-mail: imamul@eee.buet.ac.bd) PDF Cite: S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed Tarek Shahriar, "EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 326-330, 2012. PREVIOUS PAPER Perception of Emotions Using Constructive Learningthrough Speech NEXT PAPER Physical Layer Impairments Aware OVPN Connection Selection Mechanisms Copyright © 2008-2013. International Association of Computer Science and Information Technology Press (IACSIT Press) [O] . S. M. Shafiul Alam, Syed TarekShahriar 2012

机译：EEG信号在EMD域S. S. Shafiul Alam，S中的非线性动力学使用非线性动力学。 M. Shafiul Alam，Aurangozeb和Syed Tarekshahriar摘要 - 基于EMD Chaos的方法，提出了对应于健康人的EEG信号，癫痫发作期间的癫痫患者和Seizureattacks。脑电图（EEG）首先被凭经上分解为内在模式功能（IMF）。这些IMF的非线性动力学在最大范围的指数（LLE）和相关尺寸（CD）方面是量化的。本域中的混沌分析应用于与健康人相对应的大型脑电图（Asepileptic患者）（两者都有癫痫发作）。因此，所获得的LLE和CD表展的价值可以从EMD领域的其他EEG信号中清晰地区分脑电图的表达展示。本拟议的方法可以帮助研究人员以预测癫痫发作的癫痫发作技术。索引术语 - 脑电图（EEG），仿真态分解（EMD），最大的Lyapunov指数（LLE），相关维度（CD），癫痫发作。作者与电气电子和电子工程公司，孟加拉国工程和技术大学，孟加拉国达卡 - 1000（电子邮件：imamul@eee.buet.ac.bd）pdf cite：s. m. shafiul Alam，s。 M. Shafiul Alam，Aurangozeb和Syed Tarek Shahriar，“EEG信号歧视在EMD领域的非线性动态，”计算机电气工程卷国际杂志。 4，不。 3，pp。326-330,2012，上一篇论文对情绪的看法，使用建设性的学习言论下一篇论文物理层障碍意识到OVPN连接选择机制版权所有©2008-2013。国际计算机科学与信息技术协会出版社（IACSIT Press）

Discrimination of Neutral Postures in Computer Based Work.

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