Low-Cost Effective Hands-Free Control Devices for Quadriplegia

Hands-free control devices are very beneficial for people with quadriplegia. By using these devices, severely disabled people can obtain much more independence and significantly reduce the assistance from relatives. Hands-free devices can be developed based on head movement detection, eye blinking detection, and speech recognition. For many years, these hands-free devices have been very costly and even ineffective for many users. In addition, they cannot adapt to different kinds of users. In this study, low-cost, efficient, hands-free devices have been proposed with the use of inexpensive hardware and software. Firstly, a head-direction-based control system is formed by using an ADXL335 accelerometer and an Arduino Uno board. In this system, intentional head movement can be detected by using a feedforward neural network. An eye-blink-based system can be developed by using a MindWave mobile headset and an Arduino Uno board. Finally, an effective speech recognition system has been developed using an Arduino Nano 33 BLE Sense board with a speech recognition technique that does not require any learning model. Finally, these hands-free control devices are not only effective but also very affordable for various kinds of severely disabled users.

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Publication Details

Journal
Smart Systems and Devices
Published
2024-09-15
DOI
https://doi.org/10.51316/jst.176.ssad.2024.34.3.7
Primary Topic
Mobile Learning in Education
Type
article
Field-Weighted Citation Impact
0.00

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article

Low-Cost Effective Hands-Free Control Devices for Quadriplegia

Smart Systems and Devices
Mobile Learning in Education
article

Low-Cost Effective Hands-Free Control Devices for Quadriplegia

article en

Abstract

Hands-free control devices are very beneficial for people with quadriplegia. By using these devices, severely disabled people can obtain much more independence and significantly reduce the assistance from relatives. Hands-free devices can be developed based on head movement detection, eye blinking detection, and speech recognition. For many years, these hands-free devices have been very costly and even ineffective for many users. In addition, they cannot adapt to different kinds of users. In this study, low-cost, efficient, hands-free devices have been proposed with the use of inexpensive hardware and software. Firstly, a head-direction-based control system is formed by using an ADXL335 accelerometer and an Arduino Uno board. In this system, intentional head movement can be detected by using a feedforward neural network. An eye-blink-based system can be developed by using a MindWave mobile headset and an Arduino Uno board. Finally, an effective speech recognition system has been developed using an Arduino Nano 33 BLE Sense board with a speech recognition technique that does not require any learning model. Finally, these hands-free control devices are not only effective but also very affordable for various kinds of severely disabled users.

Smart Systems and DevicesVol. 34(3)
Hanoi University of Science and Technology (VN)
Trường Đại học Bách Khoa Hà Nội
Openalex Percentile: Top 74%
Mobile Learning in Education
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