Applications of machine learning techniques to a sensor-network-based prosthesis training system

Abstract

a b s t r a c tIn the past, the utilization of the limb prosthesis has improved the daily life of amputees or patients with movement disorders. However, a leg-amputee has to take a series of training after wearing a limb prosthesis, and the training results determine whether a patient can use the limb prosthesis correctly in her/his daily life. Limb prosthesis vendors thus desire to offer the leg-amputee a complete and wellorganized training process, but they often fail to do so owing to the factors such as the limited support of human resource and financial condition of the amputee. This work proposes a prosthesis training system that the amputees can borrow or buy from the limb prosthesis vendors and train themselves at home. Instant feedback messages provided by the prosthesis training system are used to correct their walking postures during the self-training process. An embedded chip is used as a core to establish a body area sensor network for the prosthesis training system. RFID readers and tags are employed to acquire the 3D positioning information of the amputee's limbs in this work to assist in diagnosing the amputee's walking problem. A series of simulations were conducted and the simulation results exhibit the effectiveness and practicability of the proposed prosthesis training system.

Use of machine learning in the field of prosthetics and orthotics: A systematic narrative review

“…In 2011, Huang et al 16 developed a prosthesis training system for supporting patients who underwent an amputation to independently participate in the training on prosthetic use. To obtain 3D location information on their amputated limbs during movement, prostheses were outfitted with radio frequency identification (RFID) readers, which can detect the motions of patients participating in the training.…”

“…The SVM has an advantage of being effective when dealing with high-dimensional data. 47 Huang et al 16 also developed a training model by applying the Lagrangian function to solve an issue related to optimization of the SVM. The Lagrangian function is used to identify the maximum or minimum value of a certain function under constraint conditions.…”

Rede de atenção à saúde à pessoa amputada

“…They also demonstrate knowledge of the network of assistance offered to people who depend on these services. In this sense, studies discuss (11,12) the importance of highly specialized training professionals, who are focused on educating the people with amputation throughout their rehabilitation process that is aimed at rehabilitating in an adequate time and optimizing the treatment costs. By the logic of the authors, professionals trained on how and when to rehabilitate help the service that pays the treatment for preparing a limb for prosthetic placement.…”

New Classifier Design for Static Security Evaluation Using Artificial In-telligence Techniques

“…Therefore, the decision tree is simple to be understood and interpreted. Besides, it can handle nominal and categorical data and perform well with large data set in a short time [15]. In C4.5 training, the decision tree is built in a topdown recursive way.…”