Current Research
The Internet of Things (IoT) has gained significant importance due to its versatile applications in various domains, including smart homes, wearable technology, and industrial automation. However, a common challenge faced by IoT devices is the need for high-speed, short-range communication that is also power-efficient. In this research, our focus is to address this challenge by designing and developing an energy-efficient serial link system specifically tailored for near-sensor applications, with an emphasis on achieving a minimal absolute power consumption.
Contact: Sina Arjmandpour
Neurological disorders in patients have become an increasing burden in societies and the research field attracts more attention. A better understanding of the brain and neuro system is needed. Since the number of electrophysiological signals generated by neurons are normally massive, a large scale, high accuracy, intense density and robust artificial device is needed. Through the recording of optical or electrical signals generated by neurons, such as action potentials (APs) and local-field potentials (LFPs), single-neuron behaviour and neural signalling in neuronal networks can be studied.
Microelectrode Array (MEA) has been one of the most efficient ways of acquiring neural signals from a large number of neurons in terms of number of recording sites, temporal resolution, spatial resolution, and signal-to-noise ratio. MEAs are devices that contain multiple microelectrodes that can be used to obtain or deliver neural signals and serve as a neural interface that connect neurons to detecting devices. They play an important role in understanding the electrophysiological activity of the nervous system, allowing reading and stimulating multiple cells simultaneously. MEAs can be practical in studying pharmacological effects on dissociated cultures, electrical activity from extracellular networks of cardiac cells, and neurons in organs such as the heart and brain.
In this doctorate, my focus will be on designing a neural interface using a new neural signal detecting scheme with a novel cross coupled MEA that senses the electrical double layer (EDL) capacitance as a function of the ion concentration released by neurons.
Contact Yiyang Chen
For wearable and implantable devices, reliable biopotential recording should be ensured even under large artifacts caused by the user’s motion or concurrent electrical stimulation, which can be larger than 100mVPP at the recording IC input. A wide dynamic range (DR) is required for such an artifact-tolerant biopotential-acquisition IC. In addition, ZIN should be large enough to minimize input signal attenuation and common-mode-to-differential-mode conversion of artifacts occurring at the electrode interface. The recording IC should also consume low power for long-time operation with a limited-size battery. In this context, this paper presents an input-impedance-boosted NS-SAR-nested DSM with high DR and power efficiency.
Contact Dr. Kyeongwon Jeong
Recently, All digital phased locked loops (ADPLL) are becoming popular in wireless communication applications because of their small size, reconfigurability, and scalability. For a better performance in case of their output spectrum, a power-hungry time-to-digital converter (TDC) is required. Besides in multi-bit TDC, calibration is mandatory to alleviate the non-linearity effects on the spectral purity. On the other hand, the Bang-bang phase detector can be used as an alternative for power-hungry TDC in ADPLLs and eliminates TDC nonlinearity issues. Furthermore, Digital-to-time-converters (DTC) enables Fractional-N synthesis in Bang-bang PLLs. However, due to the hard non-linear behavior of the phase detector and DTC non-idealities, Bang-bang PLLs suffers from spurious tones in their spectrum. In this research a new technique is going to be used to purify PLL output spectrum and generate an accurate signal for wireless communication circuits.
Contact Long He
To overcome the limitations of the traditional silicon CIS such as pixel size, dynamic range, sensitivity, and manufacturing cost, we are developing next-generation CIS using special photodetector made of new material with optimized readout circuit
Contact Kyuik Cho
Tim works in collaboration with the Spine Biomechanics group of ETH on the development of an implantable platform that can sense, process and transmit certain body parameters to monitor patients’ recovery after spine-fusion surgeries. Given the challenge of battery replacement inside human bodies, his main research interests are in the field of ultra-low-power circuit techniques and systems for the Internet-of-Things.
Contact Tim Keller
High spectral purity frequency synthesis is indispensable to key modern wireless communication, sensor interface and computation systems where new Phase-Locked-Loop (PLL) architectures are being developed to push forward the system performance metrics and power efficiency figures. In this context, the suppression of integrated phase noise and spur levels while maintaining the power efficiency in PLLs has become a major design challenge.
To address this main design challenge, a new sub-sampling PLL (SSPLL) architecture has been proposed and verified in [1] where the in-band noise level has been suppressed with the help of a new phase detection scheme. Nevertheless, due to the periodic perturbation of the VCO at the sampling instances, the reference spur level of the SSPLLs needs further attention with certain approaches already being developed to alleviate the spur issue [2].
In our laboratory, we are investigating new methods for reducing the spurs in SSPLLs while benefiting from their low in-band noise levels targeting very high purity frequency synthesis with low power figures.
Contact Can Livanelioglu
Sound activity detection is a hot topic in consumer and smart city applications. One of the main applications in this area is keyword spotting of human sound that can serve as a natural user interface with IoT devices.
To achieve this goal, we are designing an analog front end of the acoustic sensor to detect the sound if existed and wake up the circuit for further processing of the sound and its detection. Our main challenges in this project besides from the power consumption and accuracy, which are the two most important targets, is the time of detection that shows the agility of our sensor.
Contact Hesam Omdeh Ghiasi
Contact Yiyang Chen