Postural kyphosis detection using intelligent shoes

Postural kyphosis as one of the most common kinds of kyphosis is usually diagnosed in adolescents and young adults. Long-term kyphosis will not only affect the persons' appearance, but also result in thoracic deformity accompanied by pain. In this paper, we introduce a cost-effective shoe-integrated system which mainly consists of 8 force sensing resistors (FSRs) for gathering the pressure information under the 8 bony prominences. Based on the gathered plantar pressure information, the methodology of Cascade Neural Networks with Node-Decoupled Extended Kalman Filtering (CNN-NDEKF) is applied for training the model of detecting the gait pattern associated with postural kyphosis. Experimental results demonstrate that the proposed approach is efficient. This device is of particular significance to provide feedback in the application of postural kyphosis rectification.