Woradorn Wattanapanitch

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This paper describes an ultralow-power neural recording amplifier. The amplifier appears to be the lowest power and most energy-efficient neural recording amplifier reported to date. We describe low-noise design techniques that help the neural amplifier achieve input-referred noise that is near the theoretical limit of any amplifier using a differential(More)
This paper presents work on ultra-low-power circuits for brain-machine interfaces with applications for paralysis prosthetics, stroke, Parkinson's disease, epilepsy, prosthetics for the blind, and experimental neuroscience systems. The circuits include a micropower neural amplifier with adaptive power biasing for use in multi-electrode arrays; an analog(More)
We report the design of an ultra-low-power 32-channel neural-recording integrated circuit (chip) in a 0.18 μ m CMOS technology. The chip consists of eight neural recording modules where each module contains four neural amplifiers, an analog multiplexer, an A/D converter, and a serial programming interface. Each amplifier can be programmed to record either(More)
Algorithmically and energetically efficient computational architectures that operate in real time are essential for clinically useful neural prosthetic devices. Such devices decode raw neural data to obtain direct control signals for external devices. They can also perform data compression and vastly reduce the bandwidth and consequently power expended in(More)
The ability to decode neural activity into meaningful control signals for prosthetic devices is critical to the development of clinically useful brain- machine interfaces (BMIs). Such systems require input from tens to hundreds of brain-implanted recording electrodes in order to deliver robust and accurate performance; in serving that primary function they(More)
In this thesis, I present the design of a wireless neural stimulation system. The system consists of an external transmitter, controllable through a computer interface, and a miniature, implantable wireless receiver and stimulator. The implant is tailored for use in zebra finches-small birds weighing just 12-15g-as part of ongoing research into the neural(More)
The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract The ability to decode neural activity into meaningful control signals for prosthetic devices is critical to the development of clinically useful brain– machine interfaces (BMIs). Such systems require input from tens to hundreds of(More)
The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters. Abstract The ability to decode neural activity into meaningful control signals for prosthetic devices is critical to the development of clinically useful brain– machine interfaces (BMIs). Such systems require input from tens to(More)