By Lau Bee Theng
Learn on assistive applied sciences is present process many advancements in its effectiveness in assisting people with various impairments. New applied sciences are consistently being created, researched, and applied in the event you want those technological aides in day-by-day life.
Assistive applied sciences for actual and Cognitive Disabilities combines world wide instances on individuals with actual and cognitive disabilities with the newest purposes in assistive applied sciences. This reference paintings brings various researchers jointly lower than one name to debate present findings, advancements, and ongoing examine within the region of rehabilitative expertise. This reference booklet is of serious use to execs, researchers, healthcare practitioners, caretakers, academicians, and scholars.
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Extra resources for Assistive Technologies for Physical and Cognitive Disabilities
W. (2009). Robotic neurorehabilitation: A computational motor learning perspective. Journal of Neuroengineering and Rehabilitation, 6. PMID:19243614 Huang, Y. , Hudgins, B. , & Chan, A. D. C. (2005). A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses. IEEE Transactions on Bio-Medical Engineering, 52(11), 1801–1811. , & Scott, R. (1994). Control of artificial limbs using myoelectric pattern recognition. Medical & Life Sciences Engineering, 13, 21–38.
Compared to the approaches described above, the use of depth sensors has been recently affirmed as an effective and affordable solution to the problem of monitoring older adults in a nonobtrusive way, even in the presence of cognitive impairments, and respecting the privacy requirements of the users. Choosing a depth sensor allows, differently from wearable systems, the complete independence of the person doing everyday op- 25 Depth Cameras in AAL Environments erations. , 2014) because it is directly connected to the electrical power supply and can work 24/7.
Monitoring and surveillance based on computer vision and pattern recognition techniques applied to images and videos are developed and implemented since a long time (Cucchiara, Grana, Prati & Vezzani, 2005; Pham, Dhome, Gond & Sayd, 2008). In AAL applications, it is of interest to integrate vision-based systems and other technologies, such as sensor networks, to either reduce the complexity of each processing element, and improve reliability of the outcome provided. e. to create a safe home environment that is able to automatically react to the user’s behaviors, and to anticipate his needs.