ORTHONORMAL (FOURIER AND WALSH) MODELS OF TIME-VARYING EVOKED-POTENTIALS IN NEUROLOGICAL INJURY

Estimation of time-varying changes in evoked potentials (EP's) has imp ortant applications, such as monitoring high-risk. neurosurgical proce dures. We test the hypothesis that injury related changes in EP signal s may be modeled by orthonormal basis functions. We evaluate two model s of time-varying EP signals: the Fourier series model (FSM) and the W alsh function model (WFM). We estimate the Fourier and Walsh coefficie nts with the aid of an adaptive least-mean-squares technique. Results from computer simulations illustrate how selection of model order and of the adaptation rate of the estimator affect the signal-to-noise rat io (SNR). The FSM results in a somewhat higher steady-state SNR than d oes the WFM; however, the WFM is less computationally complex than is the FSM. We apply these two orthonormal functions to evaluate transien t response to hypoxic hypoxia in anesthetized cats. Trends of the firs t five frequencies (Fourier) and sequencies (Walsh) show that the lowe r frequencies and sequencies may be sensitive indicators of hypoxic ne urological injury.