Towards a Virtual Coach for manual wheelchair users

We introduce the concept of a Virtual Coach (VC) for providing advice to manual wheelchair users to help them avoid damaging forms of locomotion. The primary form of context for this system is the user´s propulsion pattern. The contexts of self vs. external propulsion and the surface over which propulsion is occurring can be used to improve the accuracy of the system´s propulsion pattern classifications. To obtain these forms of context, we explore the use of both wearable and wheelchair-mounted accelerometers. We show achievable accuracy rates of up to 80-90% for all desired contextual information using two common machine learning techniques: k-nearest neighbor (kNN) and support vector machines (SVM).