This paper describes the development of a prototype speech-controlled cloud-based wheelchair platform. The control of the platform is implemented using a low-cost WebKit Speech API in the cloud. The description of the...
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This paper describes the development of a prototype speech-controlled cloud-based wheelchair platform. The control of the platform is implemented using a low-cost WebKit Speech API in the cloud. The description of the cloud-based wheelchair control system is provided. In addition to the voice control, a GUI is implemented, which works in a web browser as well as on mobile devices providing live video streaming. Development was done in two phases: first, a small, initial prototype was developed and, second, a full size prototype was build. The accuracy of the speech recognition system was estimated as ranging from approximately 60% to up to 97%, dependent on the speaker. The speech-controlled system latency was measured as well as the latency when the control is provided via touch on a so-called smart device. Measured latencies ranged from 0.4 s to 1.3 s. The platform was also clinically tested, providing promising results of cloud-based speech recognition for further implementation. The developed platform is based on a Quad Core ARM Mini PC GK802 running Ubuntu Linux and an Arduino UNO Microcontroller. Software development was done in Javascript/ecma script, applying ***. (C) 2015 Elsevier B.V. All rights reserved.
The paper describes the development of prototype wheelchair platform controlled by the gestures. Leap Motion Controller is used to acquire data while changing the hand position. The novel user interface was developed,...
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ISBN:
(纸本)9781479989997
The paper describes the development of prototype wheelchair platform controlled by the gestures. Leap Motion Controller is used to acquire data while changing the hand position. The novel user interface was developed, which shows the hand position to the user and combines the classical button GUI switchboard. The developed system is cloud based and integrates speech recognition to engage the motion controller as well as to control the entire platform if needed. The entire software was developed with Javascript/ecma script.
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