Analogue implementation of motion estimators for digital video encoding

Image compression is a vital technology in the realisation of the information highway and motion estimation (ME) is a key aspect of image compression systems. Although simple in principle, real-time ME processors are notoriously difficult and expensive to realise because of their huge computational requirements. As a result, the ME processor is the most complex and power hungry component of a digital video codec. This project is concerned with the application of analogue circuits to ease the implementation complexity of ME processors for digital video encoding. Using a new architecture for ME processor design and current-mode analogue circuits, large reductions in size, power dissipation and implementation cost can be achieved compared to digital implementations. To demonstrate the new approach, a compact, low power, analogue ME processor will be designed, built and evaluated which could be readily extended to meet the requirements of commercial digital video encoding. Such a ME processor is particularly important in portable video systems where size and power dissipation are incompatible with digital implementations.

Analogue implementation of convolutional decoders using a new decoding algorithm

Convolutional decoders have long been important in applications where very noisy channels are encountered. The technique has recently become more significant with the advent of new application areas such as satellite and mobile radio systems of various types and digital magnetic recording systems. The most commonly employed convolutional decoding technique is the Viterbi algorithm (VA). This provides an optimum method for realising a convolutional decoder, but requires a large amount of digital path memory, typically up to 50% of the total chip area. This project is concerned with the design and implementation of convolutional decoders based on a new alternative approach called the modified feedback decoding algorithm (MFDA). This algorithm requires no digital path memory and so can be implemented using almost entirely analogue components, which offers the potential for the construction of miniature low power convolutional decoders. The MFDA approach trades implementation complexity and power dissipation against operating speed. Such trade-offs are very important for a number of  portable applications such as emerging and future wireless systems and low power implantable biomedical systems employing radio communication with external sources.

An implant for controlling neurogenic incontinence by combining neuromodulation with stimulation

We propose to design an implant system which can be used by clinical researchers to investigate new methods for treating neurogenic incontinence. The implant will allow both ENG recording from, and selective stimulation of the afferent and efferent pathways of the sacral nerve roots. Our proposed implant will avoid the need to cut the sensory nerves by using conditional neuromodulation. In addition to being more popular with patients with complete spinal cord lesions, successful use of neuromodulation will widen the user group to include incomplete-lesion patients. The latter will also benefit to the extent that pain can be prevented. All patients may benefit from improved defecation. It is also possible that the device could benefit some patients with other neurological conditions (eg. Multiple Sclerosis). The two major parts of the project are the design of a 4-channel ENG amplifier integrated circuit and the design of the complete implant system. Prototype implants will be produced.

Bi-directional interfacing of Electronics and Cultured Neurons

The overall aim is to advance our understanding of how mammalian nerve cells can be optimally connected to integrated electronic circuitry for neurobiological research and medical applications. Current methods for directly measuring neural activity use patch clamps or optical recording. Th first method is bi-directional, but does not have the ability to make reliable one-to-one connections to single neurones over an extended period as it is intrusive. The second method allows only recording and requires imaging technology if an automatic system is to be used. This implies a large amc of storage and the development of software to interpret the firing patterns. Like patch clamping, the fluorescent dyes used for optical imaging are not suitable for long-term measurements: the lifespan of treated cells is measured in hours. In this proposal we describe an alternative method which has the potential to overcome many of the problems described above. The method involve; connecting mammalian nerve cells to integrated electronic circuitry using extracellular electrodes. Although in principle this is not a new idea, use of technique to date has required a high level of experimental expertise and of specialized silicon processing. The non-invasive nature of extracellular electrodes allows long-term measurements to be made.