In this talk, we will take a look at ultra-low power, low area sensor interfaces. First, the SAR ADC is reviewed as the core digitizing block for these interfaces. While limited in resolution and accuracy, the SAR ADC offers advantages in terms of chip area, scalable power consumption vs frequency, as well as scalability with technology. Next, it is discussed how capacitive and resistive sensors can be connected to such an ADC while keeping the SAR ADC benefits. Various sensor interface implementations will be presented, including versatile SAR-based interfaces and temperature sensors. On top of that, analog versus digital correction strategies for circuit imperfections are reviewed and an example of a temperature sensor with analog correction for offset, gain, and distortion is given.
MEMS-based Inertial Measurement Units (IMUs) have found wide application in consumer-electronic devices such as smartphones, tablets, remote controls, earbuds, and drones, for gesture recognition, context awareness, navigation, and optical image stabilization. Advances in miniaturization, accuracy, and power efficiency of MEMS gyroscopes, the dominant component of MEMS-based IMUs, have been instrumental in enabling the near ubiquity of these sensors. In this talk, I will highlight some of the challenges raised by the conflicting goals of miniaturization, accuracy, and power efficiency, and how the readout architecture and circuits have evolved to address those challenges in several generations of consumer-electronic gyroscopes developed at Bosch.
Molecular electronics is the concept of using single molecules as functional circuit elements. This work reports the first CMOS molecular electronics chip. It is configured as a biosensor, where the primary sensor element is a single molecule “molecular wire” consisting of a ~100 GΩ, 25 nm long alpha-helical peptide integrated into a current monitoring circuit. The engineered peptide contains a central conjugation site for the attachment of various probe molecules, such as DNA, proteins, enzymes, or antibodies, which program the biosensor to detect interactions with a specific target molecule.
Clinicians and engineers are collaborating actively to design neural interfaces for treating neurological disorders. Optimizing the interface between electronics and the nervous system raises several interesting challenges for circuit designers. I will highlight three themes of interest to the sensing community: designing robust sensing interfaces in the presence of physiological and man-made artifacts, optimal partitioning of algorithms in "smart devices" (e.g. closed loop) that are heavily constrained by power and communication bandwidth, and implementing risk mitigation approaches to ensure patient safety. To summarize, we will discuss the opportunities and limitations of applying the internet of of things to the "intranet of the nervous system" for treating disease.
As sensors become ubiquitous in personal electronics, automobile and industrial settings, the need for them to do complex functions in tiny form factors is growing. The power management blocks within a sensor system play an important role not just in extending the lifespan of sensors but in making them smaller, more precise and in certain cases completely energy autonomous. This talk will go over the recent advances in materials, architectures and circuit techniques related to power management to advance the efficiency, density and accuracy of sensors.
Large-scale neural interfacing is needed to provide better understanding of the brain at the cellular level and to develop more advanced prosthetic devices and brain-machine interfaces. Conventional neuroscience tools do not provide yet the level of density and functionality required to achieve such large-scale electrophysiology, but many ongoing efforts are significantly impacting the field. In this talk, I will review the latest advances on implantable sensors for brain interfaces, with a focus on the readout electronics and the different challenges to further improve and scale this technology.
Thermal management becomes a demanding task in modern SoCs: In order to control and optimize computing performance, it requires tiny but smart sensors which can fit into highly constrained digital areas. Ideally those sensors can operate at low power and with a decent raw precision, since effective trimming is hardly feasible during production test. A specific challenge arises in recent FinFET technologies, where the conventional transducer – the parasitic PNP bipolar device - suffers from serious linearity issues.