Abstract
People with quadriplegia cannot move their body and limbs freely, making them unable to interact normally with their environment. This article aims to improve the life quality of quadriplegia patients through a development of a system to help them interact with their surroundings. A novel algorithm to classify human gestures is proposed in this article. The algorithm is developed as the core of an assistive technology system in the form of a human interface device, which utilizes electromyograph as its sensor. The system utilizes a wearable electromyograph with a custom software as the signal capturing and processing tool. The electrodes of the electromyograph are placed on certain positions on the face, corresponding to the locations of the major muscles that govern certain facial gestures. The signals are then processed using a novel algorithm that employs hidden Markov model and improved particle swarm optimization to classify the gesture. Based on the gestures, a custom command can be assigned for different conditions. The accuracy of the system is 96.25% for five gestures classification.
Highlights
Spinal cord injury (SCI)[1] is inflicted upon between 250,000 and 500,000 people around the world annually, from which 54.1% have suffered cervical injuries.[2]
It can be seen that the proposed system has better accuracy compared to other methods in this experiment
With the implementation of improved swarm wavelet optimization (ISWO), we achieve an average calculation time of 0.05 s. Both Hidden Markov model (HMM) and particle swarm optimization (PSO) are classical algorithms, the result of our work shows that with proper implementation, the synergy can boost the accuracy by 13.5% compared to HMM-only algorithm
Summary
Spinal cord injury (SCI)[1] is inflicted upon between 250,000 and 500,000 people around the world annually, from which 54.1% have suffered cervical injuries.[2]. People with cervical SCI have high tendency to develop quadriplegia, a loss of sensory and motoric capability in their arms, body, and legs. This condition prohibits them to interact normally with their surroundings, including to operate human interface devices (HIDs) such as mouse and keyboard. They may have to rely on their caregivers, which in turn can lead to depression, impacting their overall health.[1] An assistive technology (AT) in form of a novel HID might be able help to improve their condition. Using the AT, that the users will be able to get connected with the world through the use of personal computer (PC), but it is
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