Research database

Inertial measurement units (IMUs) represent a suitable solution for human motion capture during wheelchair mobility in activities of daily living (ADL), because they are portable, lightweight, easy to wear, minimally invasive, low-cost, and applicable in ecological conditions [1], [2]. Some authors attached IMUs to the wheelchair, generating sportspecific information about the interaction between the wheelchair user and the wheelchair-basketball, -rugby and - tennis environment [3-5]. However, the absence of capturing trunk and upper extremity (UE) movements leaves the complex UE/trunk/wheelchair/environment interactions unexplored. Furthermore, applications to ADL are sparse and limited to only a selection of tasks [1]. The current project will develop IMU-algorithms to provide insight in how people with neuromusculoskeletal impairments use their remaining function to perform a representative set of ADLtasks in ecological conditions.