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首页> 外文期刊>American journal of applied sciences >EGRONOMIC FINGERPRINT SCANNER DESIGN FOR PEOPLE WITH MOTOR NEURON DISEASES | Science Publications
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EGRONOMIC FINGERPRINT SCANNER DESIGN FOR PEOPLE WITH MOTOR NEURON DISEASES | Science Publications

机译:人体工程学指纹扫描仪,专为运动神经元疾病患者设计科学出版物

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> Fingerprint devices have evolved with time for authentication and identification purposes. It is used in generic security and social applications where identification and logging is required when entering that premises. In some circumstances the lag time increases due to increase in human entrees such as at immigration points, airports, random security checkups, attendance loggers. The increase in overall time due to individual human delay factors present a major hindrance in smooth security as well as organizational operations. The delay could occur due to non-technical factor such as not placing the fingers firmly in the surface of the device. This is a major cause of concern for senior citizens and people with motor neuron diseases such as Parkinson?s, Huntington?s and Alzheimer?s disease. Therefore, a design is proposed in this research which can help the scanner to acquire fast and precise fingerprint scan of senior citizens and people with motor neuron diseases. This design uses ergonomically designed cover head for the scanner whose working is based on the Poka Yoke principle which assists firm finger placement on the scanner. In this research, 250 fingerprint scans were taken for statistical analysis using a normal fingerprint scanner and our proposed model scanner. Statistical comparison between the two results shows that our proposed model performs much better in terms of time consumption and accuracy.
机译: >出于身份验证和识别目的,指纹设备已经随着时间发展。它用于一般安全和社交应用程序中,当进入该场所时需要进行识别和记录。在某些情况下,滞后时间会由于诸如进入移民点,机场,随机安全检查,出勤记录仪等人员的增加而增加。由于个人的人为延迟因素而导致的总时间增加,对平稳的安全性和组织运营构成了重大障碍。延迟可能是由于非技术因素(例如未将手指牢固地放置在设备表面)而发生的。这是老年人和患有运动神经元疾病如帕金森氏病,亨廷顿氏病和阿尔茨海默氏病的人们关注的主要原因。因此,本研究提出了一种设计,可以帮助扫描仪对老年人和运动神经元疾病患者进行快速,精确的指纹扫描。此设计使用符合人体工程学的扫描仪盖头,其工作原理基于Poka Yoke原理,可帮助手指牢固地放在扫描仪上。在这项研究中,使用普通指纹扫描仪和我们提出的模型扫描仪进行了250次指纹扫描以进行统计分析。两种结果之间的统计比较表明,我们提出的模型在时间消耗和准确性方面表现更好。

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