Implantable Low-Noise Fiberless Optoelectrodes for Optogenetic Control of Distinct Neural Populations

The mammalian brain is often compared to an electrical circuit, and its dynamics and function are governed by communication across different types neurons. To treat neurological disorders like Alzheimer’s and Parkinson’s, which are characterized by inhibition or amplification of neural activity in a particular region or lack of communication between different regions of the brain, there is a need to understand troubleshoot neural networks at cellular or local circuit level. In this work, we introduce a novel implantable optoelectrode that can manipulate more than one neuron type at a single site, independently and simultaneously. By delivering multi-color light using a scalable optical waveguide mixer, we demonstrate manipulation of multiple neuron types at precise spatial locations in vivo for the first time. We report design, micro-fabrication and optoelectronic packaging of a fiber-less, multicolor optoelectrode. The compact optoelectrode design consists of a 7 μm x 30 μm dielectric optical waveguide mixer and eight electrical recording sites monolithically integrated on each shank of a 22 μm-thick four-shank silicon neural probe. The waveguide mixers are coupled to eight side-emitting injection laser diodes (ILDs) via gradient-index (GRIN) lenses assembled on the probe backend. GRIN-based optoelectrode enables efficient optical coupling with large alignment tolerance to provide wide optical power range (10 to 3000 mW/mm2 irradiance) at stimulation ports. It also keeps thermal dissipation and electromagnetic interference generated by light sources sufficiently far from the sensitive neural signals, allowing thermal and electrical noise management on a multilayer printed circuit board. We demonstrated device verification and validation in CA1 pyramidal layer of mice hippocampus in both anesthetized and awake animals. The packaged devices were used to manipulate variety of multi-opsin preparations in vivo expressing different combinations of Channelrhodopsin-2, Archaerhodopsin and ChrimsonR in pyramidal and parvalbumin interneuron cells. We show effective stimulation, inhibition and recording of neural spikes at precise spatial locations with less than 100 μV stimulation-locked transients on the recording channels, demonstrating novel use of this technology in the functional dissection of neural circuits.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137171/1/kkomal_1.pd

Electronics for Sensors

The aim of this Special Issue is to explore new advanced solutions in electronic systems and interfaces to be employed in sensors, describing best practices, implementations, and applications. The selected papers in particular concern photomultiplier tubes (PMTs) and silicon photomultipliers (SiPMs) interfaces and applications, techniques for monitoring radiation levels, electronics for biomedical applications, design and applications of time-to-digital converters, interfaces for image sensors, and general-purpose theory and topologies for electronic interfaces

A Novel Power-Efficient Wireless Multi-channel Recording System for the Telemonitoring of Electroencephalography (EEG)

This research introduces the development of a novel EEG recording system that is modular, batteryless, and wireless (untethered) with the supporting theoretical foundation in wireless communications and related design elements and circuitry. Its modular construct overcomes the EEG scaling problem and makes it easier for reconfiguring the hardware design in terms of the number and placement of electrodes and type of standard EEG system contemplated for use. In this development, portability, lightweight, and applicability to other clinical applications that rely on EEG data are sought. Due to printer tolerance, the 3D printed cap consists of 61 electrode placements. This recording capacity can however extend from 21 (as in the international 10-20 systems) up to 61 EEG channels at sample rates ranging from 250 to 1000 Hz and the transfer of the raw EEG signal using a standard allocated frequency as a data carrier. The main objectives of this dissertation are to (1) eliminate the need for heavy mounted batteries, (2) overcome the requirement for bulky power systems, and (3) avoid the use of data cables to untether the EEG system from the subject for a more practical and less restrictive setting. Unpredictability and temporal variations of the EEG input make developing a battery-free and cable-free EEG reading device challenging. Professional high-quality and high-resolution analog front ends are required to capture non-stationary EEG signals at microvolt levels. The primary components of the proposed setup are the wireless power transmission unit, which consists of a power amplifier, highly efficient resonant-inductive link, rectification, regulation, and power management units, as well as the analog front end, which consists of an analog to digital converter, pre-amplification unit, filtering unit, host microprocessor, and the wireless communication unit. These must all be compatible with the rest of the system and must use the least amount of power possible while minimizing the presence of noise and the attenuation of the recorded signal A highly efficient resonant-inductive coupling link is developed to decrease power transmission dissipation. Magnetized materials were utilized to steer electromagnetic flux and decrease route and medium loss while transmitting the required energy with low dissipation. Signal pre-amplification is handled by the front-end active electrodes. Standard bio-amplifier design approaches are combined to accomplish this purpose, and a thorough investigation of the optimum ADC, microcontroller, and transceiver units has been carried out. We can minimize overall system weight and power consumption by employing battery-less and cable-free EEG readout system designs, consequently giving patients more comfort and freedom of movement. Similarly, the solutions are designed to match the performance of medical-grade equipment. The captured electrical impulses using the proposed setup can be stored for various uses, including classification, prediction, 3D source localization, and for monitoring and diagnosing different brain disorders. All the proposed designs and supporting mathematical derivations were validated through empirical and software-simulated experiments. Many of the proposed designs, including the 3D head cap, the wireless power transmission unit, and the pre-amplification unit, are already fabricated, and the schematic circuits and simulation results were based on Spice, Altium, and high-frequency structure simulator (HFSS) software. The fully integrated head cap to be fabricated would require embedding the active electrodes into the 3D headset and applying current technological advances to miniaturize some of the design elements developed in this dissertation

Low Power Circuits for Smart Flexible ECG Sensors

Cardiovascular diseases (CVDs) are the world leading cause of death. In-home heart condition monitoring effectively reduced the CVD patient hospitalization rate. Flexible electrocardiogram (ECG) sensor provides an affordable, convenient and comfortable in-home monitoring solution. The three critical building blocks of the ECG sensor i.e., analog frontend (AFE), QRS detector, and cardiac arrhythmia classifier (CAC), are studied in this research. A fully differential difference amplifier (FDDA) based AFE that employs DC-coupled input stage increases the input impedance and improves CMRR. A parasitic capacitor reuse technique is proposed to improve the noise/area efficiency and CMRR. An on-body DC bias scheme is introduced to deal with the input DC offset. Implemented in 0.35m CMOS process with an area of 0.405mm2, the proposed AFE consumes 0.9W at 1.8V and shows excellent noise effective factor of 2.55, and CMRR of 76dB. Experiment shows the proposed AFE not only picks up clean ECG signal with electrodes placed as close as 2cm under both resting and walking conditions, but also obtains the distinct -wave after eye blink from EEG recording. A personalized QRS detection algorithm is proposed to achieve an average positive prediction rate of 99.39% and sensitivity rate of 99.21%. The user-specific template avoids the complicate models and parameters used in existing algorithms while covers most situations for practical applications. The detection is based on the comparison of the correlation coefficient of the user-specific template with the ECG segment under detection. The proposed one-target clustering reduced the required loops. A continuous-in-time discrete-in-amplitude (CTDA) artificial neural network (ANN) based CAC is proposed for the smart ECG sensor. The proposed CAC achieves over 98% classification accuracy for 4 types of beats defined by AAMI (Association for the Advancement of Medical Instrumentation). The CTDA scheme significantly reduces the input sample numbers and simplifies the sample representation to one bit. Thus, the number of arithmetic operations and the ANN structure are greatly simplified. The proposed CAC is verified by FPGA and implemented in 0.18m CMOS process. Simulation results show it can operate at clock frequencies from 10KHz to 50MHz. Average power for the patient with 75bpm heart rate is 13.34W

Development of a Portable CMOS Time-Domain Fluorescence Lifetime Imager

Modern laboratory equipments to measure the excited-state lifetime of fluorophores usually include an expensive picosecond pulsed-laser excitation source, a fragile photomultiplier tube, and a large instrument body for optics. A portable and robust device to make fluorescence lifetime measurement in nanosecond scale is of great attraction for chemists and biologists. This dissertation reports the development of a portable LED time-domain fluorimeter from an all-solid-state discrete-component prototype to its advanced CMOS integrated circuit implementation. The motivation of the research is to develop a multiplexed fluorimeter for point-of-care diagnosis. Instruments developed by this novel method have higher fill factor, are more portable, and are fabricated at lower cost

Biomedical Engineering

Biomedical engineering is currently relatively wide scientific area which has been constantly bringing innovations with an objective to support and improve all areas of medicine such as therapy, diagnostics and rehabilitation. It holds a strong position also in natural and biological sciences. In the terms of application, biomedical engineering is present at almost all technical universities where some of them are targeted for the research and development in this area. The presented book brings chosen outputs and results of research and development tasks, often supported by important world or European framework programs or grant agencies. The knowledge and findings from the area of biomaterials, bioelectronics, bioinformatics, biomedical devices and tools or computer support in the processes of diagnostics and therapy are defined in a way that they bring both basic information to a reader and also specific outputs with a possible further use in research and development

Thin-film Lithium Niobate Photonics for Electro-optics, Nonlinear Optics, and Quantum Optics on Silicon

Ion-sliced thin-film lithium niobate (LN) compact waveguide technology has facilitated the resurgence of integrated photonics based on lithium niobate. These thin-film LN waveguides offer over an order of magnitude improvement in optical confinement, and about two orders of magnitude reduction in waveguide bending radius, compared to conventional LN waveguides. Harnessing the improved confinement, a variety of miniaturized and efficient photonic devices are demonstrated in this work. First, two types of compact electrooptic modulators are presented – microring modulators, and Mach-Zehnder modulators. Next, two distinct approaches to nonlinear optical frequency converters are implemented – periodically poled lithium niobate, and mode shape modulation (grating assisted quasi-phase matching). Following this, stochastic variations are added to the mode shape modulation approach to demonstrate random quasi-phase matching. Afterward, broadband photon-pair generation is demonstrated in the miniaturized periodically poled lithium niobate, and spectral correlations of the biphoton spectrum are reported. Finally, extensions of the aforementioned results suitable for future work are discussed

Optical Communication

Optical communication is very much useful in telecommunication systems, data processing and networking. It consists of a transmitter that encodes a message into an optical signal, a channel that carries the signal to its desired destination, and a receiver that reproduces the message from the received optical signal. It presents up to date results on communication systems, along with the explanations of their relevance, from leading researchers in this field. The chapters cover general concepts of optical communication, components, systems, networks, signal processing and MIMO systems. In recent years, optical components and other enhanced signal processing functions are also considered in depth for optical communications systems. The researcher has also concentrated on optical devices, networking, signal processing, and MIMO systems and other enhanced functions for optical communication. This book is targeted at research, development and design engineers from the teams in manufacturing industry, academia and telecommunication industries

Advances in Solid State Circuit Technologies

This book brings together contributions from experts in the fields to describe the current status of important topics in solid-state circuit technologies. It consists of 20 chapters which are grouped under the following categories: general information, circuits and devices, materials, and characterization techniques. These chapters have been written by renowned experts in the respective fields making this book valuable to the integrated circuits and materials science communities. It is intended for a diverse readership including electrical engineers and material scientists in the industry and academic institutions. Readers will be able to familiarize themselves with the latest technologies in the various fields

Energy Harvesters and Self-powered Sensors for Smart Electronics

This book is a printed edition of the Special Issue “Energy Harvesters and Self-Powered Sensors for Smart Electronics” that was published in Micromachines, which showcases the rapid development of various energy harvesting technologies and novel devices. In the current 5G and Internet of Things (IoT) era, energy demand for numerous and widely distributed IoT nodes has greatly driven the innovation of various energy harvesting technologies, providing key functionalities as energy harvesters (i.e., sustainable power supplies) and/or self-powered sensors for diverse IoT systems. Accordingly, this book includes one editorial and nine research articles to explore different aspects of energy harvesting technologies such as electromagnetic energy harvesters, piezoelectric energy harvesters, and hybrid energy harvesters. The mechanism design, structural optimization, performance improvement, and a wide range of energy harvesting and self-powered monitoring applications have been involved. This book can serve as a guidance for researchers and students who would like to know more about the device design, optimization, and applications of different energy harvesting technologies