Glove based wearable devices for sign language-GloSign

Q2 Decision Sciences
Soly Mathew Biju, Obada Al-Khatib, H. Sheikh, F. Oroumchian
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引用次数: 0

Abstract

Loss of the capability to talk or hear has psychological and social effects onthe affected individuals due to the absence of appropriate interaction. SignLanguage is used by such individuals to assist them in communicating witheach other. This paper proposes a glove called GloSign that can convertAmerican sign language to characters. This glove consists of flex and inertialmeasurement unit (IMU) sensors to identify gestures. The data from glove isuploaded on IoT platform, which makes the glove portable and wireless. Thedata from gloves is passed through a k-nearest neighbors (KNN) Algorithmmachine learning algorithm to improve the accuracy of the system. Thesystem was able to achieve an accuracy of 96.8%. The glove can also be usedto form sentences. The output is displayed on the screen or is converted tospeech. This glove can be used in communicating with people who don’t knowsign language.
基于手套的可穿戴手语设备——glosign
由于缺乏适当的互动,说话或听力的丧失对患者的心理和社会产生了影响。这些人使用手语来帮助他们彼此交流。本文提出了一种名为GloSign的手套,它可以将美国手语转换为文字。这款手套由弯曲和惯性测量单元(IMU)传感器组成,用于识别手势。手套的数据上传到物联网平台,使手套具有便携性和无线性。来自手套的数据通过k近邻(KNN)算法(机器学习算法)传递,以提高系统的准确性。该系统能够达到96.8%的准确率。手套也可以用来造句。输出显示在屏幕上或转换为语音。这只手套可以用来和不懂手语的人交流。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IAES International Journal of Artificial Intelligence
IAES International Journal of Artificial Intelligence Decision Sciences-Information Systems and Management
CiteScore
3.90
自引率
0.00%
发文量
170
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