Wheelchair control system based on electro-oculogram

Abstract

The invention discloses a wheelchair control system based on electro-oculogram. The system comprises an electro-oculogram signal collecting module, a blinking detecting unit, a decision making unit and a wheelchair executing unit. The electro-oculogram signal collecting module is used for signal collection and amplifying and filtering, and then is used for transmitting collected electro-oculogram signals to the blinking detecting unit. The blinking detecting unit extracts waveform feature parameters from the electro-oculogram signals and checks whether the waveform feature parameters meet a threshold value condition or not, and therefore whether blinking occurs or not is judged. The decision making unit outputs an instruction to the wheelchair executing unit according to the result of the blinking detecting unit. The wheelchair executing unit controls a wheelchair to execute corresponding actions according to the recognized instruction result. Blinking signals can be detected fast and located on a certain specified key accurately, and therefore the wheelchair control instruction can be provided safely, fast, accurately and fully through only one eye action.

Description

technical field [0001] The invention relates to an electric wheelchair control system, in particular to an electric wheelchair control system based on eye electricity. Background technique [0002] Wheelchairs are one of the common disability devices used to help people who have lost motor function in their legs regain the ability to walk. Human machine interface (human machine interface, HMI) converts human intentions into control commands, and establishes direct communication and control channels between human and external equipment. Therefore, human-machine interface technology is widely used in wheelchair control, and common ones include joysticks and keyboards. However, most of the existing human-machine interfaces for wheelchair control are manual, requiring users to have good upper limb motor functions. However, some diseases (such as amyotrophic lateral sclerosis ALS, spinal cord injury SCI, etc.) will cause deep paralysis of patients and loss of motor function of ...

AI Technical Summary

Problems solved by technology

P300 and SSVEP can provide a wealth of control commands, but their response time is relatively long, the accuracy is not high, and they are prone to fatigue, so they are not suitable for long-term control

In addition, the effect of motor imagery varies greatly among individuals, so a relatively large amount of training data is required, which is time-consuming

[0004] The current human-machine interface based on oculometry has the following disadvantages: first, it cannot quickly and accurately identify conscious eye movements and unconscious eye movements; second, the accuracy of distinguishing different eye movements needs to be improved; third, more The use of such eye movements leads to more complicated control and easy to cause eye fatigue

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