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This paper contains results on the design of electrical signals for delivering charge through electrodes to achieve neural stimulation while reducing the peak electrode voltage. A generalization of the usual constant current stimulation phase to a stepped current waveform is presented. Techniques based on optimization and linear dynamic system theory are then applied to design the magnitude of each current segment in such a way as to minimize the maximum electrode voltage, while transferring a designated quantity of charge in a specified time. Experimental results are provided which validate the approach in saline and in neural tissue.

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We introduce a class of linear discrete-time systems called &superstable'. For the SISO case this means that the absolute value of the constant term of the characteristic polynomial is greater than the sum of absolute values of all other coe$cients, while superstable MIMO systems have a state matrix with l norm less than one. Such systems have many special features. First, non-asymptotic bounds for the output of such systems with bounded input can be easily obtained. In particular, for small enough initial conditions, we get the equalized performance property, recently introduced for the SISO case by Blanchini and Sznaier (36th CDC, San Diego, 1997, pp. 1540}1545). Second, the same bounds can be obtained for LTV systems, provided all the frozen LTI systems are super stable. This makes the notion well suited for adaptive control.These bounds can be used as the performance index for optimal controller design, as proposed by Blanchini and Sznaier for the SISO case. Then to obtain disturbance rejection in SISO or MIMO systems, we design a controller which guarantees super stability of the closed-loop system and minimizes the proposed performance index ( -optimality). This problem happens to be quasiconvex with respect to the controller coe$cients and can be solved via parametric linear programming. Compared with the wellknown l optimization-based design technique, the approach allows low-order controllers to be designed (while l optimal controllers may have high order) and can take into account non-asymptotic time-domain behaviour of the system with non-zero initial conditions. For unbounded controller orders we prove the existence and "nite dimensionality of -optimal designs. We also address the robustness issues for transfer functions with coprime factor uncertainty bounded in l norm. A robust performance problem can be formulated and similarly solved via linear programming. Numerous examples are provided to compare the proposed design with optimal l and H controllers.

Delivering power to an implanted device located deep inside the body is not trivial. This problem is made more challenging if the implanted device is in constant motion. This paper describes two methods of transferring power wirelessly by means of magnetic induction coupling. In the first method, a pair of transmit and receive coils is used for power transfer over a large distance (compared to their diameter). In the second method, an intermediate pair of coils is inserted in between transmit and receive coils. Comparison between the power transfer efficiency with and without the intermediate coils shows power transfer efficiency to be 11.5 % and 8.8 %, respectively. The latter method is especially suitable for powering implanted devices in the eye due to immunity to movements of the eye and ease of surgery. Using this method, we have demonstrated wireless power delivery into an animal eye.