Alphabetical Gesture Recognition of American Sign Language using E-Voice Smart Glove

Amin, Muhammad Saad; Amin, Muhammad Talha; Latif, Muhammad Yasir; Jathol, Ali Asghar; Ahmed, Nisar; Tarar, M. Irtaza Nawaz

doi:10.1109/inmic50486.2020.9318185

Cited by 14 publications

(8 citation statements)

References 12 publications

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“…This solution will not detect the gesture if there is a slight difference in the sensor readings. In [47]- [49] and [50] the sensor values were obtained and passed through multiple algorithms to evaluate the accuracy. The glove was able to achieve more accuracy than previous experiments.…”

Section: Resultsmentioning

confidence: 99%

A review of factors that impact the design of a glove based wearable devices

Al-Khatib

Sheikh

2023

IJ-AI

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Loss of the capability to talk or hear applies psychological and social effects on the affected individuals due to the absence of appropriate interaction. Sign Language is used by such individuals to assist them in communicating with each other. The paper aims to report details of various aspects of wearable healthcare technologies designed in recent years based on the aim of the study, the types of technologies being used, accuracy of the system designed, data collection and storage methods, technology used to accomplish the task, limitations and future research suggested for the study. The aim of the study is to compare the differences between the papers. There is also comparison of technology used to determine which wearable device is better, which is also done with the help of accuracy. The limitations and future research help in determining how the wearable devices can be improved. A systematic review was performed based on a search of the literature. A total of 23 articles were retrieved. The articles are study and design of various wearable devices, mainly the glove-based device, to help you learn the sign language.

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Section: Resultsmentioning

confidence: 99%

A review of factors that impact the design of a glove based wearable devices

Al-Khatib

Sheikh

2023

IJ-AI

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“…With the advent of time, recent studies have shown the latest framework for sign recognition. [41] Chin-Hao proposed an American Sign Language recognition system with motion sensors that considered to be better than a cyber glove embedded with Kinect camera . [42] In close with the progression of time and the new advancements of wearable innovation, it is currently possible to actualize valuable and incredibly innovative methods to help humanity in meaningful ways.…”

Section: Figure 7 Sign Language Convertormentioning

confidence: 99%

The Sign Language Interpreting Gloves

Burhani¹,

Prasetyo²

2023

J. of App. Sci. & Adv. Eng.

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This report’s primary purpose is to provide a detailed overview of the sign language interpreting gloves project. It starts with an introduction, background and history of the deaf community to better understand the needs and issues of the D/deaf community. In the following literature review, the reader will have the chance to learn about the modern-days challenges faced by hearing-impaired people, broadly explained and elaborated. The psychosocial impact of assistive technology and its effectiveness in improving life quality is discussed next. A lack of new technologies assisting the D/deaf community is not hardly noticed. As elaborated in the previously mentioned chapters, sign language interpreting services are expensive and sign language interpreters cannot be easily booked. These and other findings gathered from the research and also by a survey conducted on a group of deaf individuals indicate that sign language interpreting gloves are the new free interpreters-to-be, and the answer to acquiring the so-wanted independence. Evaluated to have such a significant impact, building this assistive technology that can be easily accessed is the project's focus. The working principles, block diagram and flowchart are also described in the methodology section, where building, not one but a pair of gloves is also documented step by step. Finally, results, discussion and future work will tell us more about the importance of interpreting gloves to close the gap between both hearing and deaf communities.

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“…2) Correlational Analysis In addition to data cleaning, correlational analysis is performed by generating a correlation matrix to identify linear relationships between dataset attributes [16] [17]. The plotted correlation matrix for the dataset is illustrated in Figure 3 using various colors to depict the strength of the correlation between the features.…”

Section: Data Preprocessing 1) Data Cleaningmentioning

confidence: 99%

Intelligent Sign Multi-Language Real-Time Prediction System with Effective Data Preprocessing

Elmatary,

Maher,

Ibrahim

2023

JCC

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A multidisciplinary approach for developing an intelligent sign multi-language recognition system to greatly enhance deaf-mute communication will be discussed and implemented. This involves designing a low-cost glove-based sensing system, collecting large and diverse datasets, preprocessing the data, and using efficient machine learning models. Furthermore, the glove is integrated with a user-friendly mobile application called "Lifesign" for this system. The main goal of this work is to minimize the processing time of machine learning classifiers while maintaining higher accuracy performance. This is achieved by using effective preprocessing algorithms to handle noisy and inconsistent data. Testing and iterating approaches have been applied to various classifiers to refine and improve their accuracy in the recognition process. Additionally, the Extra Trees (ET) classifier has been identified as the best algorithm, with results proving successful gesture prediction at an average accuracy of about 99.54%. A smart optimization feature has been implemented to control the size of data transferred via Bluetooth, allowing for fast recognition of consecutive gestures. Real-time performance has been measured through extensive experimental testing on various consecutive gestures, specifically referring to Arabic Sign Language (ArSL). The results have demonstrated that the system guarantees consecutive gesture recognition with a lower delay of 50 milliseconds.

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Alphabetical Gesture Recognition of American Sign Language using E-Voice Smart Glove

Cited by 14 publications

References 12 publications

A review of factors that impact the design of a glove based wearable devices

A review of factors that impact the design of a glove based wearable devices

The Sign Language Interpreting Gloves

Intelligent Sign Multi-Language Real-Time Prediction System with Effective Data Preprocessing

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