An Intelligent Infrared LED-Based Prosthesis Training System
Chenn‐Jung Huang, Chih-Tai Guan, Heng-Ming Chen, Yu‐Wu Wang, Sheng-Yuan Chien, Ching-Yu Li · Applied Artificial Intelligence · 2014
In the past, the utilization of limb prostheses has improved the daily life of both amputees and patients with movement disorders. However, prior to achieving this improvement, a leg amputee must undertake a series of training sessions while wearing a limb prosthesis whereby the training results determine whether a patient will be able to use the limb prosthesis correctly in her/his daily life. Limb prostheses vendors therefore desire to offer the leg amputee a complete and well-organized training procedure, but they often fail to do so owing to factors related to limited human resource support and the financial constraints of the amputee. This work proposes a prosthesis training system that amputees can borrow or buy from the limb prostheses vendors to enable independent training at home. In this prosthesis training system, 3D positioning information is obtained via infrared LEDs. Four features are extracted and fed into a classifier to determine the actual conditions for the leg-amputee during training. Experimental results exhibited the effectiveness and practicality of the proposed prosthesis training system.