Title :
Pruning a Decision Tree for Selecting Computer-Related Assistive Devices for People With Disabilities
Author :
Chi, Chia-Fen ; Tseng, Li-Kai ; Jang, Yuh
Author_Institution :
Dept. of Ind. Manage., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
fDate :
7/1/2012 12:00:00 AM
Abstract :
Many disabled individuals lack extensive knowledge about assistive technology, which could help them use computers. In 1997, Denis Anson developed a decision tree of 49 evaluative questions designed to evaluate the functional capabilities of the disabled user and choose an appropriate combination of assistive devices, from a selection of 26, that enable the individual to use a computer. In general, occupational therapists guide the disabled users through this process. They often have to go over repetitive questions in order to find an appropriate device. A disabled user may require an alphanumeric entry device, a pointing device, an output device, a performance enhancement device, or some combination of these. Therefore, the current research eliminates redundant questions and divides Anson´s decision tree into multiple independent subtrees to meet the actual demand of computer users with disabilities. The modified decision tree was tested by six disabled users to prove it can determine a complete set of assistive devices with a smaller number of evaluative questions. The means to insert new categories of computer-related assistive devices was included to ensure the decision tree can be expanded and updated. The current decision tree can help the disabled users and assistive technology practitioners to find appropriate computer-related assistive devices that meet with clients´ individual needs in an efficient manner.
Keywords :
decision trees; handicapped aids; Anson decision tree; alphanumeric entry device; assistive technology; computer-related assistive devices; disabilities; occupational therapists; output device; performance enhancement device; pointing device; pruning; redundant question elimination; Appraisal; Computers; Decision trees; Keyboards; Mice; Performance evaluation; Redundancy; Assistive technology; decision tree; production rule; Algorithms; Artificial Intelligence; Decision Support Systems, Clinical; Decision Support Techniques; Disabled Persons; Humans; Self-Help Devices; Technology Assessment, Biomedical; Therapy, Computer-Assisted;
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
DOI :
10.1109/TNSRE.2012.2193419