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.
Keyword
Quadriplegia, hands-free control devices, head movement-based control, eyeblink-based control, speech recognition-based control