Dr Mohamed Sakel
Dr. Sakel is the Director/Consultant Neuro-Rehabilitation and Director R& D at the East Kent University Foundation Hospitals Trust (EKHUFT) and is working closely on a number of joint projects with staff of the School of Engineering and Digital Arts. More information is available on Dr. Sakel's personal web page.
Gallagher, M., Wilkinson, D. and Sakel, M. (2013). Hemispatial Neglect: Clinical Features, Assessment and Treatment. British Journal of Neuroscience Nursing [Online] 9:273-277. Available at: http://dx.doi.org/10.12968/bjnn.2013.9.6.273.Hemispatial neglect is a disorder of attention which commonly follows from damage to the right side of the brain. Patients with neglect show symptoms of lateralised inattention, failing to acknowledge or report information on the left side. Neglect is a poor prognostic indicator for general functional recovery from stroke, and is associated with a range of co-morbid conditions including denial or indifference to the brain injury, hemiplegia and visual field loss. Mild to moderate cases can be over-shadowed by the more gross symptoms that accompany brain injury, however assessment and diagnosis is relatively quick and simple. Current treatment guidelines suggest that patients should be taught compensatory strategies, but these are largely ineffective. Although recent research has identified more promising treatment approaches, investigations are still preliminary. Given the prevalence and debilitating nature of neglect, there is a clear need to raise awareness and understanding of the condition amongst carers and healthcare professionals.
Conference or workshop item
Guness, S., Deravi, F., Sirlantzis, K., Pepper, M. and Sakel, M. (2013). A Novel Depth-based Head Tracking and Gesture Recognition System. In: 12th European AAATE (Association for the Advancement of Assistive Technology in Europe) Conference. IOS Press EBooks, pp. 1021-1026. Available at: http://dx.doi.org/10.3233/978-1-61499-304-9-1021.This paper presents the architecture for a novel RGB-D based assistive device that incorporates depth as well as RGB data to enhance head tracking and facial gesture based control for severely disabled users. Using depth information it is possible to remove background clutter and therefore achieve a more accurate and robust performance. The system is compared with the CameraMouse, SmartNav and our previous 2D head tracking system. For the RGB-D system, the effective throughput of dwell clicking increased by a third (from 0.21 to 0.30 bits per second) and that of blink clicking doubled (from 0.15 to 0.28 bits per second) compared to the 2D system.
Guness, S., Deravi, F., Sirlantzis, K., Pepper, M. and Sakel, M. (2012). Developing a vision based gesture recognition system to control assistive technology in neuro-disability. In: 2012 Annual Conference, American Congress of Rehabilitation Medicine (2012 ACRM-ASNR). Elsevier Science B.V., p. e1. Available at: http://dx.doi.org/doi:10.1016/j.apmr.2012.08.202.