VLSI Implementation in Biomedical Applications

In the past decade, knowledge of the way to use computers within the health care field has rapidly advanced. Recent disastrous incidents in health care system have disturbed the continual process of care, leaving the health care sector in a ‘state of emergency’. This structure can be constructed using very large-scale integration (VLSI) concept which is acceptable for biogenic applications. VLSI circuit is employed in medical image processing is to supply richer information than that exists within the original medical images.VLSI will improve the value effectiveness of medical devices through advanced, smaller-sized circuitry, which provides increased sophistication and enhanced function.

VLSI design in biomedicine produces reduction in size of the chips, range, and speed enhancement. During this analysis, various proposals are scrutinized for VLSI employment of neural networks which is stated as CMOS fabrication technique, architecture of medical implant communication system (MICS) receiver for critical medical operations, field programmable gate array (FPGA) execution of semantic networks, neuro-fuzzy system, neuromorphic computing approach, neural net performance in analog hardware and digital network.
There are wireless devices available present day that are implanted in patients body with the accurate technology for monitoring patients and their medical conditions. The data access is incredibly easy, cost is minimized and bed space is saved. Multi-objective optimization problem is the streamlining of assorted functions instantaneously and attaining a solution which is best in regard to all of the target functions. These problems are present at various levels of VLSI circuit optimization.
Neurology is that the medical field worried with the detection and therapy of ailments of the system, which includes the brain, the nerves and structure . There are over 600 diseases of the nervous systems, which include brain tumors, epilepsy, Parkinson’s disease. Artificial neural networks (ANNs) are computing systems virtually stimulated by the biological neurons that constitute animal brains.
The integrated neural network operating VLSI design having low cost, low power and low area are highly necessary in biomedical systems. The extra techniques of VLSI design include FPGA implementation, neuromorphic computing and neuro-fuzzy approach, which are demanding in the biomedical application. FPGA performs multiprocessing with a faster rate. Neuromorphic computing has the key feature of excellent durability.