Optimising control algorithms in biofeedback-systems
by , ,
Abstract:
We explore the potential of model identification adaptive controllers (MIAC) within a biofeedback system. Through the application of an adaptive control algorithm, the system performance could be optimised with respect to time. In a series of experiments the galvanic skin resistance of test subjects playing a computer game was recorded. On this data, a system identification was performed, utilising an Adaptive-Network-based Fuzzy Inference System (ANFIS). The results serve as a basis for the development of the adaption laws of the MIAC and allow conclusions about suitable controllers
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PDF URL: http://dx.doi.org/10.5220/0003771702070212
Reference:
Optimising control algorithms in biofeedback-systems (C. Zschippig, C. Rachuy, K. Schill), In Proceedings of the International Conference on Health Informatics, Scitepress, 2012.
Bibtex Entry:
@InProceedings{Zschippig2012,
  author    = {C. Zschippig and C. Rachuy and K. Schill},
  title     = {Optimising control algorithms in biofeedback-systems},
  booktitle = {Proceedings of the International Conference on Health Informatics},
  year      = {2012},
  pages     = {207-212},
  month     = {feb},
  publisher = {Scitepress},
  abstract  = {We explore the potential of model identification adaptive controllers (MIAC) within a biofeedback system. Through the application of an adaptive control algorithm, the system performance could be optimised with respect to time. In a series of experiments the galvanic skin resistance of test subjects playing a computer game was recorded. On this data, a system identification was performed, utilising an Adaptive-Network-based Fuzzy Inference System (ANFIS). The results serve as a basis for the development of the adaption laws of the MIAC and allow conclusions about suitable controllers},
  doi       = {10.5220/0003771702070212},
  url       = {10.5220/0003771702070212">http://dx.doi.org/10.5220/0003771702070212},
}