System identification of biomedical systems from short transients using space methods.
System identification technology has been a popular tool to analysis the dynamic behavior of biomedical systems. A segment of data with enough information must be collected in order to obtain unbiased estimate of the systems. However, some biomedical systems have short transients, such as Vestibulo-Ocular Reflex (VOR). Systems often cannot be identified from the short transients collected in one experiment. Thus, the experiments must be repeated, and an ensemble of input and output recorded. This paper presents a subspace method to identify Multiple Input and Multiple Output (MIMO) state space models for biomedical systems from short transients using ensemble data. A simulating ankle joint stiffness experiment demonstrates that the algorithm provides accurate results.
Zhao
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Department of Biomedical Engineering, McGill University, Montreal, QC, Canada, H3A 2B4. yong.zhao@mcgill.ca
Kearney
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D000465:Algorithms; D000843:Ankle Joint / Q000502:physiology*; D003198:Computer Simulation; D055119:Elastic Modulus / Q000502:physiology; D005246:Feedback / Q000502:physiology; D006801:Humans; D008954:Models, Biological; D009119:Muscle Contraction / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D012018:Reflex / Q000502:physiology*; D049490:Systems Biology / Q000379:methods*