Lei Yao

Bio: Lei Yao is an academic researcher from Agency for Science, Technology and Research. The author has contributed to research in topics: CMOS & Signal. The author has an hindex of 13, co-authored 51 publications receiving 464 citations. Previous affiliations of Lei Yao include McGill University.

A 100-Channel 1-mW Implantable Neural Recording IC

Abstract: This paper presents a fully implantable 100-channel neural interface IC for neural activity monitoring. It contains 100-channel analog recording front-ends, 10 multiplexing successive approximation register ADCs, digital control modules and power management circuits. A dual sample-and-hold architecture is proposed, which extends the sampling time of the ADC and reduces the average power per channel by more than 50% compared to the conventional multiplexing neural recording system. A neural amplifier (NA) with current-reuse technique and weak inversion operation is demonstrated, consuming 800 nA under 1-V supply while achieving an input-referred noise of 4.0 μVrms in a 8-kHz bandwidth and a NEF of 1.9 for the whole analog recording chain. The measured frequency response of the analog front-end has a high-pass cutoff frequency from sub-1 Hz to 248 Hz and a low-pass cutoff frequency from 432 Hz to 5.1 kHz, which can be configured to record neural spikes and local field potentials simultaneously or separately. The whole system was fabricated in a 0.18-μm standard CMOS process and operates under 1 V for analog blocks and ADC, and 1.8 V for digital modules. The number of active recording channels is programmable and the digital output data rate changes accordingly, leading to high system power efficiency. The overall 100-channel interface IC consumes 1.16-mW total power, making it the optimum solution for multi-channel neural recording systems.

Independent Mobility Achieved through a Wireless Brain-Machine Interface

Abstract: Individuals with tetraplegia lack independent mobility, making them highly dependent on others to move from one place to another. Here, we describe how two macaques were able to use a wireless integrated system to control a robotic platform, over which they were sitting, to achieve independent mobility using the neuronal activity in their motor cortices. The activity of populations of single neurons was recorded using multiple electrode arrays implanted in the arm region of primary motor cortex, and decoded to achieve brain control of the platform. We found that free-running brain control of the platform (which was not equipped with any machine intelligence) was fast and accurate, resembling the performance achieved using joystick control. The decoding algorithms can be trained in the absence of joystick movements, as would be required for use by tetraplegic individuals, demonstrating that the non-human primate model is a good pre-clinical model for developing such a cortically-controlled movement prosthetic. Interestingly, we found that the response properties of some neurons differed greatly depending on the mode of control (joystick or brain control), suggesting different roles for these neurons in encoding movement intention and movement execution. These results demonstrate that independent mobility can be achieved without first training on prescribed motor movements, opening the door for the implementation of this technology in persons with tetraplegia.

A Sub- ${\mu}$ W/Ch Analog Front-End for $\Delta $ -Neural Recording With Spike-Driven Data Compression

Abstract: We present a fully implantable neural recording IC with a spike-driven data compression scheme to improve the power efficiency and preserve crucial data for monitoring brain activities. A difference between two consecutive neural signals, $\Delta $ -neural signal, is sampled in each channel to reduce the full dynamic range and the required resolution of an analog-to-digital converter (ADC), enabling the whole analog chain to be operated at a 0.5-V supply. A set of multiple $\Delta $ -signals are stored in analog memory to extract the magnitude and frequency features of the incoming neural signals, which are utilized to discriminate spikes in these signals instantaneously after the acquisition in the analog domain. The energy- and area-efficient successive approximation ADC is implemented and only converts detected spikes, decreasing the power dissipation and the amount of neural data. A prototype 16-channel neural interface IC was fabricated using a 0.18-μm CMOS process, and each component in the analog front-end was fully characterized. We successfully demonstrated precise spike detection through both in vitro and in vivo acquisition of the neural signal. The prototype chip consumed 0.88 μW/channel at a 0.5-V supply for the recording and compressed about 89% of neural data, saving the power consumption and bandwidth in the system.

CMOS Conductometric System for Growth Monitoring and Sensing of Bacteria

Abstract: We present the design and implementation of a prototype complementary metal-oxide semiconductor (CMOS) conductometric integrated circuit (IC) for colony growth monitoring and specific sensing of Escherichia coli (E. coli) bacteria. The detection of E. coli is done by employing T4 bacteriophages as receptor organisms. The conductometric system operates by measuring the resistance of the test sample between the electrodes of a two-electrode electrochemical system (reference electrode and working electrode). The CMOS IC is fabricated in a TSMC 0.35-μm process and uses a current-to-frequency (I to F) conversion circuit to convert the test sample resistance into a digital output modulated in frequency. Pulsewidth control (one-shot circuit) is implemented on-chip to control the pulsewidth of the output digital signal. The novelty in the current work lies in the ability of the CMOS sensor system to monitor very low initial concentrations of bacteria (4×102 to 4×104 colony forming unit (CFU)/mL). The CMOS system is also used to record the interaction between E. coli and its specific receptor T4 bacteriophage. The prototype CMOS IC consumes an average power of 1.85 mW with a 3.3-V dc power supply.

100-Channel wireless neural recording system with 54-Mb/s data link and 40%-efficiency power link

Abstract: For real-time monitoring of brain activities, a highdata-rate, low-power, and highly mobile neural recording system is desirable. This paper presents a complete chipset for a 100-channel wireless neural recording system, which consists of 3 ICs - a neural interface (NI) IC and a wireless power RX and data TX IC for an implant unit (IU), and a wireless data RX IC for an external head unit (EHU). With a dual S/H NI architecture and a burst-mode (BM) wideband (WB) FSK TX, the IU achieves a 100-channel recording and wireless transmission at 54.24Mb/s while consuming only 6.6mW. Using power coupling with optimal resonant load transformation and high-efficiency rectifier and LDO circuits, the whole wireless power link achieves 40% efficiency over 1cm distance with 0.5cm tissue in between. The EHU needs to transmit the RF power lower than 30mW to operate the IU. The EHU is implemented using a crystal-less BM WB FSK RX consuming only 14.4mW at 27.12Mb/s.

Optical methods for sensing and imaging oxygen: materials, spectroscopies and applications

Abstract: We review the current state of optical methods for sensing oxygen. These have become powerful alternatives to electrochemical detection and in the process of replacing the Clark electrode in many fields. The article (with 694 references) is divided into main sections on direct spectroscopic sensing of oxygen, on absorptiometric and luminescent probes, on polymeric matrices and supports, on additives and related materials, on spectroscopic schemes for read-out and imaging, and on sensing formats (such as waveguide sensing, sensor arrays, multiple sensors and nanosensors). We finally discuss future trends and applications and summarize the properties of the most often used indicator probes and polymers. The ESI† (with 385 references) gives a selection of specific applications of such sensors in medicine, biology, marine and geosciences, intracellular sensing, aerodynamics, industry and biotechnology, among others.

Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation

Abstract: Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links bet...

Novel electrode technologies for neural recordings.

Abstract: Neural recording electrode technologies have contributed considerably to neuroscience by enabling the extracellular detection of low-frequency local field potential oscillations and high-frequency action potentials of single units. Nevertheless, several long-standing limitations exist, including low multiplexity, deleterious chronic immune responses and long-term recording instability. Driven by initiatives encouraging the generation of novel neurotechnologies and the maturation of technologies to fabricate high-density electronics, novel electrode technologies are emerging. Here, we provide an overview of recently developed neural recording electrode technologies with high spatial integration, long-term stability and multiple functionalities. We describe how these emergent neurotechnologies can approach the ultimate goal of illuminating chronic brain activity with minimal disruption of the neural environment, thereby providing unprecedented opportunities for neuroscience research in the future.

Optical oxygen sensors for applications in microfluidic cell culture.

Abstract: The presence and concentration of oxygen in biological systems has a large impact on the behavior and viability of many types of cells, including the differentiation of stem cells or the growth of tumor cells. As a result, the integration of oxygen sensors within cell culture environments presents a powerful tool for quantifying the effects of oxygen concentrations on cell behavior, cell viability, and drug effectiveness. Because microfluidic cell culture environments are a promising alternative to traditional cell culture platforms, there is recent interest in integrating oxygen-sensing mechanisms with microfluidics for cell culture applications. Optical, luminescence-based oxygen sensors, in particular, show great promise in their ability to be integrated with microfluidics and cell culture systems. These sensors can be highly sensitive and do not consume oxygen or generate toxic byproducts in their sensing process. This paper presents a review of previously proposed optical oxygen sensor types, materials and formats most applicable to microfluidic cell culture, and analyzes their suitability for this and other in vitro applications.