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Appl. Sci. 2017, 7(12), 1296; doi:10.3390/app7121296

Wearable Vibration Based Computer Interaction and Communication System for Deaf

1
Department of Computer Engineering, Faculty of Engineering, Ataturk University, 25240 Erzurum, Turkey
2
Department of Computer Engineering, Faculty of Engineering, Karadeniz Technical University, 61080 Trabzon, Turkey
*
Author to whom correspondence should be addressed.
Academic Editor: Stefania Serafin
Received: 29 September 2017 / Revised: 25 November 2017 / Accepted: 11 December 2017 / Published: 13 December 2017
(This article belongs to the Special Issue Sound and Music Computing)
View Full-Text   |   Download PDF [1683 KB, uploaded 13 December 2017]   |  

Abstract

In individuals with impaired hearing, determining the direction of sound is a significant problem. The direction of sound was determined in this study, which allowed hearing impaired individuals to perceive where sounds originated. This study also determined whether something was being spoken loudly near the hearing impaired individual. In this manner, it was intended that they should be able to recognize panic conditions more quickly. The developed wearable system has four microphone inlets, two vibration motor outlets, and four Light Emitting Diode (LED) outlets. The vibration of motors placed on the right and left fingertips permits the indication of the direction of sound through specific vibration frequencies. This study applies the ReliefF feature selection method to evaluate every feature in comparison to other features and determine which features are more effective in the classification phase. This study primarily selects the best feature extraction and classification methods. Then, the prototype device has been tested using these selected methods on themselves. ReliefF feature selection methods are used in the studies; the success of K nearest neighborhood (Knn) classification had a 93% success rate and classification with Support Vector Machine (SVM) had a 94% success rate. At close range, SVM and two of the best feature methods were used and returned a 98% success rate. When testing our wearable devices on users in real time, we used a classification technique to detect the direction and our wearable devices responded in 0.68 s; this saves power in comparison to traditional direction detection methods. Meanwhile, if there was an echo in an indoor environment, the success rate increased; the echo canceller was disabled in environments without an echo to save power. We also compared our system with the localization algorithm based on the microphone array; the wearable device that we developed had a high success rate and it produced faster results at lower cost than other methods. This study provides a new idea for the benefit of deaf individuals that is preferable to a computer environment. View Full-Text
Keywords: wearable computing system; vibrating speaker for deaf; human–computer interaction; feature extraction; speech processing wearable computing system; vibrating speaker for deaf; human–computer interaction; feature extraction; speech processing
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Yağanoğlu, M.; Köse, C. Wearable Vibration Based Computer Interaction and Communication System for Deaf. Appl. Sci. 2017, 7, 1296.

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