This chapter describes how serious games can be used to improve the rehabilitation of stroke patients. Determining ideal training conditions for rehabilitation is difficult, as no objective measures exist and the psychological state of patients during therapy is often neglected. What is missing is a way to vary the difficulty of the tasks during a therapy session in response to the patient needs, in order to adapt the training specifically to the individual. In this chapter, we describe such a method. A serious game is used to present challenges to the patient, including motor and cognitive tasks. The psychological state of the patient is inferred from measures computed from heart rate variability (HRV) as well as breathing frequency, skin conductance response, and skin temperature. Once the psychological state of the patient can be determined from these measures, it is possible to vary the tasks in real time by adjusting parameters of the game. The serious game aspect of the training allows the virtual environment to become adaptive in real time, leading to improved matching of the activity to the needs of the patient. This is likely to lead to improved training outcomes and has the potential to lead to faster and more complete recovery, as it enables training that is challenging yet does not overstress the patient.
|Title of host publication||Serious games analytics|
|Editors||Yanyan Sheng, Dirk Ifenthaler, Christian Sebastian Loh|
|Place of Publication||Switzerland|
|Number of pages||22|
|ISBN (Print)||9783319058337, 9783319382197|
|Publication status||Published - 2015|
|Name|| Advances in Game-Based Learning|