This report entails a literature review on the progress of control of a wheelchair through brainwave recognition. The review examines the extent to which innovation of brain controlled wheelchair has succeeded in achieving the motive of providing an opportunity for ease of movement to individuals faced by movement impairment. The review examines the efforts and initiatives that have been undertaken in the quest to achieve this goal. The first section provides a brief background on innovation of brain controlled wheelchair. This is achieved by evaluating the application of brain computer interfacing technology in the development of brainwave controlled wheelchair. The review further examines the gaps, weaknesses and problems associated with application of the brain controlled technology in the wheelchair. Amongst the flaws identified include difficulty in isolating and detecting the right signal generated by the brain. In conclusion, the review underlines the need for innovators in this sector to focus on dealing with the identified gaps in order to expedite development of the technology considering its value in promoting mobility to individuals who have been rendered immobile by cases of certain diseases or injury.
Table of Contents
Certain types of diseases or injury can lead to complete loss movement or muscle control in spite of an individual being conscious of his or her surroundings. Carlson (2013) affirms that ‘millions of people around the world suffer from mobility impairments and hundreds of them depend upon powered wheelchairs to get on with their daily activities’ (p. 1). Folane and Autee (2016) affirm that development in robotics have become a critical component of in both industrial and human life. One of the areas of human life in which robotics have been utilised entails assisting individuals suffering from different forms of impairments.
In spite of the previous development in robotics, there have been significant gaps that innovators have over the past years been committed to addressing. For example, the use of powered wheelchairs is limited to patients who are capable of controlling the wheelchair using conventional interface (Carlson 2013). Thus, the use of such wheelchairs deemed impossible to individuals who have lost the capability to control the powered chairs manually. It is estimated that approximately 1.4 and 2.1 individuals within this category still experience a mobility challenges, which presents an opportunity for technological innovation.
Development of the Brain-Computer-Interfacing (BCI) technology is one of the notable technological innovations that have enabled innovators to overcome the challenges associated with conventional communication process (Wang & Li 2012). The BCI technology is capable of bypassing the limitations associated with conventional communication methods by establishing a direct interface between a human’s brain and the communication device (Falone & Autee 2016). According to Nisar, Balasubramaniam and Malik (2013), the BCI technology provides an alternative approach through which the brain communicates with the environment, which gives an individual the capability to control objects without physical contact using their brain.
Advancement in the brain-computer interfacing (BCI) technology has presented patients suffering complete movement as a result of injuries or disease an opportunity for movement through development of a new wheelchair interface that is capable of sensing a patient’s thoughts.
Development of brain-controlled wheelchair has been achieved through three main phases, which include extracting brain waves, processing the signals and classification of signals into actions or control thoughts (Yazdani et al. 2010). To be effective, the brain-controlled wheelchair must be capable of recognising four main movement signals viz. forward, backward, left and right.
Furber (2015) affirms that there has been a considerable growth of interest in funding research projects on brain function. Some of the notable research initiatives include the Brain Research through Advancing Innovative Neurotechologies (BRAIN) and the European € 1billion ICT Flagship Human Brain Project amongst others (Furber 2015). Moreover, independent organisations have also invested in development of brain controlled wheelchair (BCW). Toyota Motors Corporation is one of the organisations that have invested in development of BCW through its Brain Science Institute Toyota Collaboration Centre (Illumin 2016). The new wheelchair has the capacity to detect brain waves and follow instructions (Reznik 2016). The wheelchair is a new innovation and an improvement of the previous innovation, which took a considerably longer duration to recognise brain wave and take the intended action. In its new innovation, Toyota has significantly reduced the time that its BCW requires to respond to brain waves to 125 milliseconds (Reznik 2016), which according to Illumin (2016) is a reasonably fast rate of transmission.
By reducing the amount between transmission of the brain wave and the response of the computer technology, Toyota Motors has been able to enhance the effectiveness of the brain controlled wheelchair by eliminating delays (Illumin 2016). Therefore, the brain controlled wheelchair is able to respond to brain wave in real time (Carlson 2012). As one of the firm’s that are commitment to improve the quality of individuals life, Toyota Motors affirms that its brain controlled wheelchair is 95% accurate (Illumin 2016). Despite the fact that the progress by Toyota indicates a high degree of confidence on the viability of the brainwave controlled wheelchair, there is still a significant gap that investors should consider addressing.
Innovation of brain controlled wheelchair further entail integration of new devices such as a cap, which enhances one’s ability to read brain signals. The new innovation is based on the Electroencephalogram (EEG) technology, which entails a technique of detecting brain activity along the scalp (Falone & Autee 2016; Carlson 2012). The computer analysis the data generated and takes the right action. Development of the new wheelchair is in line with Toyota’s commitment to promote transportation. Similarly, Honda Motors Corporation commenced a project aimed at developing a new wheelchair controlled by brain waves in 2015 (Reznik 2015). However, Honda is to fully develop the brain wave controlled wheelchair. Moreover, there are still gaps in Honda’s brainwave controlled wheelchair that need to be addressed. Similarly, the new innovation by Toyota Motors Corporation is still in its research and development phase (Reznik 2015). This shows that there is a significant need for further development in brain wave controlled wheelchair in order to achieve perfection.
Progress in innovation of wheelchair controlled through brainwave has further focused on integration of visual capability (Illumin 2016). In entrenching visual capability into the brain controlled wheelchair, the Swiss Federal Institute of Technology incorporated the use of webcam software, which increases the capability to process visual information. This wheelchair is significantly different from that of Toyota in that it is not only capable of taking action out of an individual’s brainwave but also uses webcam software to control the direction of the wheelchair by detecting obstacles, hence steering the wheelchair away from such obstacles.
Despite the efforts made, Furber (2015) argues that there is still need for more initiatives into this field in order to achieve the intended goal. Nevertheless, application of computer technology in simulating brain function still remains a challenge. Furber (2015) identifies two main reasons that explain the challenge. First, in spite of the advancements in computer technology, Furber (2015) argues that ‘computer technology is now (and only now) approaching the capability required to contemplate constructing large-scale computer models of the brain’ (p.299). The second source of challenge is that computer technology development is facing physical limits. Folane and Autee (2016) assert that the brain is itself considered to be the source of ideas on how to improve computer technologies. Thus, it has become relatively difficult to understand how the brain works (Furber 2015).
In spite of the relevance of EEG in enhancing functionality of brain controlled wheelchair, the accuracy of this technology is limited. Carlson (2013) asserts that the development of brain controlled wheelchair might be limited by the fact that the BCI technology is comparatively new and in its research phase. Wang and Li (2012) assert that the accuracy computer technology in effectively reading brain signals is limited. According to Illumin (2016), the human body generates billions of neurons at a particular time hence generating different signals. This element makes it difficult for computerised technologies to effectively read the signals. Additionally, the electric activity generated by an individual is characterised by a low voltage, which makes it substantially difficult to read the electric signals with a high degree of accuracy. Graham-Rowe (2010) asserts that ‘EEG technology can only detect a few different commands’ (para. 2). In addition to the above aspects, reliability of the computer technology in reading brain signals might be affected by environmental conditions. For example, noise emanating from the external environment might lead to generation of a high voltage hence affecting the efficacy with which precise signals generated from the brain are detected.
The literature review indicates that innovation of the brain controlled wheelchair is a major milestone in improving mobility of individuals facing mobility impairment. Significant effort towards achieving this end have been made, which is evidenced by development of various types of brain controlled wheelchair by different organisations amongst them Toyota and Honda Motors. Nevertheless, the technology is still in its research and development phase. Considering the value of the technology in resolving mobility impairment problems, it is imperative for innovators in this sector to enhance their initiative in achieving the intended goal.
In the quest to achieve this goal, it is imperative for innovators to address the identified limitations of EEG technology in reading brain signals. The limitations identified may have a negative impact on the success with which brainwave recognition technology is employed in wheelchairs. This presents a significant gap that computer technology innovators should consider focusing on. Amongst the fundamental areas of interest that innovators should take into consideration entails how to use computer technology in isolating precise brainwaves in order to improve the effectiveness with which the right action is implemented. Effective isolation of brain signals will reduce misinterpretation of signals that might emanate from environmental effects such as noise. Additionally innovation on control of wheelchair through brainwave recognition should further take into consideration the functionality of such technology in crowded environment. These aspects indicate that there is a significant issues that innovators in brainwave recognition technologies should take into consideration in the quest to improve the functionality of the technology.
Carlson, T 2013, ‘Brain controlled wheelchairs; a robotic architecture’, IEEE Robotics and Automation Magazine, vol. 20, no. 1, pp. 65-73.
Falone, N & Autee, R 2016, ‘EEG based brain controlled wheelchair for physically challenged people’, International Journal of Innovative Research in Computer and Communication Engineering, vol. 4, no. 1.
Furber, S 2015, ‘Brain inspired computing’, IET Journals, vol. 10, no. 10, pp. 299-305.
Graham-Rowe, D 2010, Wheelchair makes the most of brain control. [Online]. Available at: https://www.technologyreview.com/s/420756/wheelchair-makes-the-most-of-brain-control/ (Accessed November 9, 2016)
Illumin: Thought controlled wheelchair 2016. [Online]. Available at: http://illumin.usc.edu/240/thought-controlled-wheelchair/ (Accessed November 9, 2016)
Nisar, H, Balasubramaniam, H & Malik, A 2013, ‘Brain computer interface for operating a robot’, International Symposium on Computational Models for Life Sciences, vol. 1159, pp. 37-47.
Reznik, R 2016, Toyota technology allows brainwave to move wheelchair. [Online]. Available at: http://kdsmartchair.com/blogs/news/toyota-technology-allows-brain-waves-to-move-wheelchair (Accessed November 9, 2016)
Wang, H & Li, T 2012, ‘Brain-actuated wheelchair based on mixture model brain computer interfaces’, Electronic Letters, vol. 48, no. 5, pp. 256-257.
Yazdani, N, Khazab, F, Fitzgibbon, S, Luerssen, M & Powers, D 2010, Towards a brain controlled wheelchair prototype. [Online]. Available at: http://ewic.bcs.org/upload/pdf/ewic_hci10_paper53.pdf (Accessed November 9, 2016)