Our ability to navigate in our environment depends on the condition of the musculoskeletal and nervous systems. Any deterioration of a component of these two systems can cause instability or disability of body movements. Such deterioration can happen as a consequence of natural age-related changes, injuries and/or diseases. The ability to objectively and quantitatively assess different functional tasks such as postural control, gait or hand movements can be useful for preventing falls, following disease progression, assessing the effectiveness of medical care and interventions, and ultimately improving the accuracy of clinical decisions. The benefits are clear. However, current metrics, algorithms and tools are not enough to analyze and understand the infinite complexity of human movements. In this thesis, I developed visualizations and a novel method to assess human movement in real-time using data collected from tracking devices such as Kinect and inertial measurement units. This method was used to assess balance performance on data from exergames, digital games controlled by body movements, and to classify young and older adults achieving more than 85% accuracy. This kind of assessment can also be used to provide meaningful feedback and to automatically adapt the difficulty of exergames, which in turn could increase motivation to play and improve balance control among older adults. Additionally, the method was used to classify healthy participants and patients with a coordination disorder during a hand movement task achieving 84% accuracy. In conclusion, this thesis presents a promising method that can be used for assessing and understanding human movement.
|Vertaalde titel van de bijdrage||Visuele analyse en kwantitatieve beoordeling van menselijke beweging|
|Kwalificatie||Doctor of Philosophy|
|Datum van toekenning||19-mrt-2018|
|Plaats van publicatie||[Groningen]|
|Status||Published - 2018|