HYBRID COMPUTER TECHNIQUES FOR PHYSIOLOGY.
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Recent upsurge in the use of physiologic data for medical diagnostic and treatment procedures has prompted the medical profession to use the computer to automate and reduce the time required for data processing. Although the digital computer has traditionally been used to perform these tasks, a hybrid computer (combined analog and digital) has been found to provide many advantages over the digital computer, especially where on-line data processing is concerned. As a result, the Bio-Medical Engineering Center has installed a centrally located hybrid computer system at Ohio State University. One of the applications of this system has been processing cardiac catheterization data. Data is transmitted between the hospital and computer via infrared optics. The data can be analyzed in real time, with the results immediately available to the physician.
We outline a hybrid analog-digital scheme for computing with three important features that enable it to scale to systems of large complexity: First, like digital computation, which uses several one-bit precise logical units to collectively compute a precise answer to a computation, the hybrid scheme uses several moderate-precision analog units to collectively compute a precise answer to a computation. Second, frequent discrete signal restoration of the analog information prevents analog noise and offset from degrading the computation. And, third, a state machine enables complex computations to be created using a sequence of elementary computations. A natural choice for implementing this hybrid scheme is one based on spikes because spike-count codes are digital, while spike-time codes are analog. We illustrate how spikes afford easy ways to implement all three components of scalable hybrid computation. First, as an important example of distributed analog computation, we show how spikes can create a distributed modular representation of an analog number by implementing digital carry interactions between spiking analog neurons. Second, we show how signal restoration may be performed by recursive spike-count quantization of spike-time codes. And, third, we use spikes from an analog dynamical system to trigger state transitions in a digital dynamical system, which reconfigures the analog dynamical system using a binary control vector; such feedback interactions between analog and digital dynamical systems create a hybrid state machine (HSM). The HSM extends and expands the concept of a digital finite-state-machine to the hybrid domain. We present experimental data from a two-neuron HSM on a chip that implements error-correcting analog-to-digital conversion with the concurrent use of spike-time and spike-count codes. We also present experimental data from silicon circuits that implement HSM-based pattern recognition using spike-time synchrony. We outline how HSMs may be used to perform learning, vector quantization, spike pattern recognition and generation, and how they may be reconfigured.
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A computationally efficient hybrid ray-physical optics (HRPO) model is presented for the analysis and synthesis of multiple-focus ultrasound heating patterns through the human rib cage. In particular, a ray method is used to propagate the ultrasound fields from the source to the frontal plane of the rib cage. The physical-optics integration method is then employed to obtain the intensity pattern inside the rib cage. The solution of the matrix system is carried out by using the pseudo inverse technique to synthesize the desired heating pattern. The proposed technique guides the fields through the intercostal spacings between the solid ribs and, thus, minimal intensity levels are observed over the solid ribs. This simulation model allows for the design and optimization of large-aperture phased-array applicator systems for noninvasive ablative thermal surgery in the heart and liver through the rib cage.