Adaptive Application-Specific Instrumentation and Control Microsystems - Ekekwe, Ndubuisi
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Many applications in motorcontrollers, bio-acquisition systems and energy cells balancers require reconfigurable and adaptive architectures to mitigate environmental perturbations in real time. The complexity of designing such systems is challenging, requiring robust architectures. This book provides a multimode paradigm, such that performance parameters can be adjusted using closed loop adaptation driven on sensory data from the environment. It presents mixed signal integrated System-on-Chip microsystems, which combine on-chip reconfigurable and adaptive circuit capabilities to deliver…mehr

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Produktbeschreibung
Many applications in motorcontrollers, bio-acquisition systems and energy cells balancers require reconfigurable and adaptive architectures to mitigate environmental perturbations in real time. The complexity of designing such systems is challenging, requiring robust architectures. This book provides a multimode paradigm, such that performance parameters can be adjusted using closed loop adaptation driven on sensory data from the environment. It presents mixed signal integrated System-on-Chip microsystems, which combine on-chip reconfigurable and adaptive circuit capabilities to deliver precise control signals to driver networks/electrodes. A broad applicable concept, is demonstrated by realizing controllers for surgical robots that provide performance metrics needed to manipulate delicate tissues while minimizing damage during minimal invasive surgery. Also, a single-chip/biochip for biosignals like EEG (brain), EOG (eye), ECG (heart), EMG (muscle) and neural recordings, and precision analog front-ends that support cells monitoring, variation detection, overcurrent protection and equalization are presented. The book is written for professionals and the entire academic community.
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Autorenporträt
Ndubuisi Ekekwe, PhD: Obtained PhD in Electrical & Computer Engineering with specialization on microelectronics and medical robotics at the Johns Hopkins University, Baltimore. Currently works as a Mixed Signal Design Engineer at Analog Devices Inc, Massachusetts. He co-invented an ASIC for control of high dexterity robots and motion sensors.