Improving the mechanistic study of neuromuscular diseases through the development of a fully wireless and implantable recording device

Neuromuscular diseases manifest by a handful of known phenotypes affecting the peripheral nerves, skeletal muscle fibers, and neuromuscular junction. Common signs of these diseases include demyelination, myasthenia, atrophy, and aberrant muscle activity—all of which may be tracked over time using one or more electrophysiological markers. Mice, which are the predominant mammalian model for most human diseases, have been used to study congenital neuromuscular diseases for decades. However, our understanding of the mechanisms underlying these pathologies is still incomplete. This is in part due to the lack of instrumentation available to easily collect longitudinal, in vivo electrophysiological activity from mice. There remains a need for a fully wireless, batteryless, and implantable recording system that can be adapted for a variety of electrophysiological measurements and also enable long-term, continuous data collection in very small animals. To meet this need a miniature, chronically implantable device has been developed that is capable of wirelessly coupling energy from electromagnetic fields while implanted within a body. This device can both record and trigger bioelectric events and may be chronically implanted in rodents as small as mice. This grants investigators the ability to continuously observe electrophysiological changes corresponding to disease progression in a single, freely behaving, untethered animal. The fully wireless closed-loop system is an adaptable solution for a range of long-term mechanistic and diagnostic studies in rodent disease models. Its high level of functionality, adjustable parameters, accessible building blocks, reprogrammable firmware, and modular electrode interface offer flexibility that is distinctive among fully implantable recording or stimulating devices. The key significance of this work is that it has generated novel instrumentation in the form of a fully implantable bioelectric recording device having a much higher level of functionality than any other fully wireless system available for mouse work. This has incidentally led to contributions in the areas of wireless power transfer and neural interfaces for upper-limb prosthesis control. Herein the solution space for wireless power transfer is examined including a close inspection of far-field power transfer to implanted bioelectric sensors. Methods of design and characterization for the iterative development of the device are detailed. Furthermore, its performance and utility in remote bioelectric sensing applications is demonstrated with humans, rats, healthy mice, and mouse models for degenerative neuromuscular and motoneuron diseases

소형동물의 뇌신경 자극을 위한 완전 이식형 신경자극기

학위논문(박사)--서울대학교 대학원 :공과대학 전기·정보공학부,2020. 2. 김성준.In this study, a fully implantable neural stimulator that is designed to stimulate the brain in the small animal is described. Electrical stimulation of the small animal is applicable to pre-clinical study, and behavior study for neuroscience research, etc. Especially, behavior study of the freely moving animal is useful to observe the modulation of sensory and motor functions by the stimulation. It involves conditioning animal's movement response through directional neural stimulation on the region of interest. The main technique that enables such applications is the development of an implantable neural stimulator. Implantable neural stimulator is used to modulate the behavior of the animal, while it ensures the free movement of the animals. Therefore, stable operation in vivo and device size are important issues in the design of implantable neural stimulators. Conventional neural stimulators for brain stimulation of small animal are comprised of electrodes implanted in the brain and a pulse generation circuit mounted on the back of the animal. The electrical stimulation generated from the circuit is conveyed to the target region by the electrodes wire-connected with the circuit. The devices are powered by a large battery, and controlled by a microcontroller unit. While it represents a simple approach, it is subject to various potential risks including short operation time, infection at the wound, mechanical failure of the device, and animals being hindered to move naturally, etc. A neural stimulator that is miniaturized, fully implantable, low-powered, and capable of wireless communication is required. In this dissertation, a fully implantable stimulator with remote controllability, compact size, and minimal power consumption is suggested for freely moving animal application. The stimulator consists of modular units of surface-type and depth-type arrays for accessing target brain area, package for accommodating the stimulating electronics all of which are assembled after independent fabrication and implantation using customized flat cables and connectors. The electronics in the package contains ZigBee telemetry for low-power wireless communication, inductive link for recharging lithium battery, and an ASIC that generates biphasic pulse for neural stimulation. A dual-mode power-saving scheme with a duty cycling was applied to minimize the power consumption. All modules were packaged using liquid crystal polymer (LCP) to avoid any chemical reaction after implantation. To evaluate the fabricated stimulator, wireless operation test was conducted. Signal-to-Noise Ratio (SNR) of the ZigBee telemetry were measured, and its communication range and data streaming capacity were tested. The amount of power delivered during the charging session depending on the coil distance was measured. After the evaluation of the device functionality, the stimulator was implanted into rats to train the animals to turn to the left (or right) following a directional cue applied to the barrel cortex. Functionality of the device was also demonstrated in a three-dimensional maze structure, by guiding the rats to navigate better in the maze. Finally, several aspects of the fabricated device were discussed further.본 연구에서는 소형 동물의 두뇌를 자극하기 위한 완전 이식형 신경자극기가 개발되었다. 소형 동물의 전기자극은 전임상 연구, 신경과학 연구를 위한 행동연구 등에 활용된다. 특히, 자유롭게 움직이는 동물을 대상으로 한 행동 연구는 자극에 의한 감각 및 운동 기능의 조절을 관찰하는 데 유용하게 활용된다. 행동 연구는 두뇌의 특정 관심 영역을 직접적으로 자극하여 동물의 행동반응을 조건화하는 방식으로 수행된다. 이러한 적용을 가능케 하는 핵심기술은 이식형 신경자극기의 개발이다. 이식형 신경자극기는 동물의 움직임을 방해하지 않으면서도 그 행동을 조절하기 위해 사용된다. 따라서 동물 내에서의 안정적인 동작과 장치의 크기가 이식형 신경자극기를 설계함에 있어 중요한 문제이다. 기존의 신경자극기는 두뇌에 이식되는 전극 부분과, 동물의 등 부분에 위치한 회로부분으로 구성된다. 회로에서 생산된 전기자극은 회로와 전선으로 연결된 전극을 통해 목표 지점으로 전달된다. 장치는 배터리에 의해 구동되며, 내장된 마이크로 컨트롤러에 의해 제어된다. 이는 쉽고 간단한 접근방식이지만, 짧은 동작시간, 이식부위의 감염이나 장치의 기계적 결함, 그리고 동물의 자연스러운 움직임 방해 등 여러 문제점을 야기할 수 있다. 이러한 문제의 개선을 위해 무선통신이 가능하고, 저전력, 소형화된 완전 이식형 신경자극기의 설계가 필요하다. 본 연구에서는 자유롭게 움직이는 동물에 적용하기 위하여 원격 제어가 가능하며, 크기가 작고, 소모전력이 최소화된 완전이식형 자극기를 제시한다. 설계된 신경자극기는 목표로 하는 두뇌 영역에 접근할 수 있는 표면형 전극과 탐침형 전극, 그리고 자극 펄스 생성 회로를 포함하는 패키지 등의 모듈들로 구성되며, 각각의 모듈은 독립적으로 제작되어 동물에 이식된 뒤 케이블과 커넥터로 연결된다. 패키지 내부의 회로는 저전력 무선통신을 위한 지그비 트랜시버, 리튬 배터리의 재충전을 위한 인덕티브 링크, 그리고 신경자극을 위한 이상성 자극파형을 생성하는 ASIC으로 구성된다. 전력 절감을 위해 두 개의 모드를 통해 사용률을 조절하는 방식이 장치에 적용된다. 모든 모듈들은 이식 후의 생물학적, 화학적 안정성을 위해 액정 폴리머로 패키징되었다. 제작된 신경자극기를 평가하기 위해 무선 동작 테스트가 수행되었다. 지그비 통신의 신호 대 잡음비가 측정되었으며, 해당 통신의 동작거리 및 데이터 스트리밍 성능이 검사되었고, 장치의 충전이 수행될 때 코일간의 거리에 따라 전송되는 전력의 크기가 측정되었다. 장치의 평가 이후, 신경자극기는 쥐에 이식되었으며, 해당 동물은 이식된 장치를 이용해 방향 신호에 따라 좌우로 이동하도록 훈련되었다. 또한, 3차원 미로 구조에서 쥐의 이동방향을 유도하는 실험을 통하여 장치의 기능성을 추가적으로 검증하였다. 마지막으로, 제작된 장치의 특징이 여러 측면에서 심층적으로 논의되었다.Chapter 1 : Introduction 1 1.1. Neural Interface 2 1.1.1. Concept 2 1.1.2. Major Approaches 3 1.2. Neural Stimulator for Animal Brain Stimulation 5 1.2.1. Concept 5 1.2.2. Neural Stimulator for Freely Moving Small Animal 7 1.3. Suggested Approaches 8 1.3.1. Wireless Communication 8 1.3.2. Power Management 9 1.3.2.1. Wireless Power Transmission 10 1.3.2.2. Energy Harvesting 11 1.3.3. Full implantation 14 1.3.3.1. Polymer Packaging 14 1.3.3.2. Modular Configuration 16 1.4. Objectives of This Dissertation 16 Chapter 2 : Methods 18 2.1. Overview 19 2.1.1. Circuit Description 20 2.1.1.1. Pulse Generator ASIC 21 2.1.1.2. ZigBee Transceiver 23 2.1.1.3. Inductive Link 24 2.1.1.4. Energy Harvester 25 2.1.1.5. Surrounding Circuitries 26 2.1.2. Software Description 27 2.2. Antenna Design 29 2.2.1. RF Antenna 30 2.2.1.1. Design of Monopole Antenna 31 2.2.1.2. FEM Simulation 31 2.2.2. Inductive Link 36 2.2.2.1. Design of Coil Antenna 36 2.2.2.2. FEM Simulation 38 2.3. Device Fabrication 41 2.3.1. Circuit Assembly 41 2.3.2. Packaging 42 2.3.3. Electrode, Feedthrough, Cable, and Connector 43 2.4. Evaluations 45 2.4.1. Wireless Operation Test 46 2.4.1.1. Signal-to-Noise Ratio (SNR) Measurement 46 2.4.1.2. Communication Range Test 47 2.4.1.3. Device Operation Monitoring Test 48 2.4.2. Wireless Power Transmission 49 2.4.3. Electrochemical Measurements In Vitro 50 2.4.4. Animal Testing In Vivo 52 Chapter 3 : Results 57 3.1. Fabricated System 58 3.2. Wireless Operation Test 59 3.2.1. Signal-to-Noise Ratio Measurement 59 3.2.2. Communication Range Test 61 3.2.3. Device Operation Monitoring Test 62 3.3. Wireless Power Transmission 64 3.4. Electrochemical Measurements In Vitro 65 3.5. Animal Testing In Vivo 67 Chapter 4 : Discussion 73 4.1. Comparison with Conventional Devices 74 4.2. Safety of Device Operation 76 4.2.1. Safe Electrical Stimulation 76 4.2.2. Safe Wireless Power Transmission 80 4.3. Potential Applications 84 4.4. Opportunities for Further Improvements 86 4.4.1. Weight and Size 86 4.4.2. Long-Term Reliability 93 Chapter 5 : Conclusion 96 Reference 98 Appendix - Liquid Crystal Polymer (LCP) -Based Spinal Cord Stimulator 107 국문 초록 138 감사의 글 140Docto

Coupled resonator based wireless power transfer for bioelectronics

Implantable and wearable bioelectronics provide the ability to monitor and modulate physiological processes. They represent a promising set of technologies that can provide new treatment for patients or new tools for scientific discovery, such as in long-term studies involving small animals. As these technologies advance, two trends are clear, miniaturization and increased sophistication i.e. multiple channels, wireless bi-directional communication, and responsiveness (closed-loop devices). One primary challenge in realizing miniaturized and sophisticated bioelectronics is powering. Integration and development of wireless power transfer (WPT) technology, however, can overcome this challenge. In this dissertation, I propose the use of coupled resonator WPT for bioelectronics and present a new generalized analysis and optimization methodology, derived from complex microwave bandpass filter synthesis, for maximizing and controlling coupled resonator based WPT performance. This newly developed set of analysis and optimization methods enables system miniaturization while simultaneously achieving the necessary performance to safely power sophisticated bioelectronics. As an application example, a novel coil to coil based coupled resonator arrangement to wirelessly operate eight surface electromyography sensing devices wrapped circumferentially around an able-bodied arm is developed and demonstrated. In addition to standard coil to coil based systems, this dissertation also presents a new form of coupled resonator WPT system built of a large hollow metallic cavity resonator. By leveraging the analysis and optimization methods developed here, I present a new cavity resonator WPT system for long-term experiments involving small rodents for the first time. The cavity resonator based WPT arena exhibits a volume of 60.96 x 60.96 x 30.0 cm3. In comparison to prior state of the art, this cavity resonator system enables nearly continuous wireless operation of a miniature sophisticated device implanted in a freely behaving rodent within the largest space. Finally, I present preliminary work, providing the foundation for future studies, to demonstrate the feasibility of treating segments of the human body as a dielectric waveguide resonator. This creates another form of a coupled resonator system. Preliminary experiments demonstrated optimized coupled resonator wireless energy transfer into human tissue. The WPT performance achieved to an ultra-miniature sized receive coil (2 mm diameter) is presented. Indeed, optimized coupled resonator systems, broadened to include cavity resonator structures and human formed dielectric resonators, can enable the effective use of coupled resonator based WPT technology to power miniaturized and sophisticated bioelectronics

A self-powered single-chip wireless sensor platform

Internet of things” require a large array of low-cost sensor nodes, wireless connectivity, low power operation and system intelligence. On the other hand, wireless biomedical implants demand additional specifications including small form factor, a choice of wireless operating frequencies within the window for minimum tissue loss and bio-compatibility This thesis describes a low power and low-cost internet of things system suitable for implant applications that is implemented in its entirety on a single standard CMOS chip with an area smaller than 0.5 mm2. The chip includes integrated sensors, ultra-low-power transceivers, and additional interface and digital control electronics while it does not require a battery or complex packaging schemes. It is powered through electromagnetic (EM) radiation using its on-chip miniature antenna that also assists with transmit and receive functions. The chip can operate at a short distance (a few centimeters) from an EM source that also serves as its wireless link. Design methodology, system simulation and optimization and early measurement results are presented

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

Electronic Skin in Robotics and Healthcare: Towards Multimodal Sensing and Intelligent Analysis

Skin-interfaced electronics is gradually transforming robotic and medical fields by enabling noninvasive and continuous monitoring of physiological and biochemical information. Despite their promise, current wearable technologies face challenges in several disciplines: Physical sensors are prone to motion-induced noise and lack the capability for effective disease detection, while existing wearable biochemical sensors suffer from operational instability in biofluids, limiting their practicality. Conventional electronic skin contains only a limited category of sensors that are not sufficient for practical applications, and conventional data processing methods for these wearables necessitate manual intervention to filter noise and decipher health-related information. This thesis presents advances in electronic skin within robotics and healthcare, emphasizing multimodal sensing and data analysis through machine intelligence. Chapter 1 introduces the concept of electronic skin, outlining the emerging sensor technologies and a general machine learning pipeline for data processing. Chapter 2 details the development of multimodal physiological and biochemical sensors that enable long-term continuous monitoring with high sensitivity and stability. Chapter 3 explores the application of integrated electronic skin in robotics, prosthetics, and human machine interactions. Chapter 4 showcases practical implementations of integrated electronic skin with robust sensors for wound monitoring and treatment. Chapter 5 highlights the transformative deployment of artificial intelligence in deconvoluting health profiles on mental health. The last chapter, Chapter 6, delves into the challenges and prospects of artificial intelligence-powered electronic skins, offering predictions for the evolution of smart electronic skins. We envision that multimodal sensing and machine intelligence in electronic skin could significantly advance the field of human machine interactions and personalized healthcare.</p

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

Shifting gazes with visual prostheses: Long-term hand-camera coordination

Purpose: Prosthetic vision is young, and many aspects of its use remain unexplored. Hand-camera coordination, the prosthetic correlate of hand-eye coordination, relies heavily on how the camera is aligned with the eye. It is unknown whether users of prostheses can adapt to using misaligned cameras, or whether requirements for proper alignment remain constant over time. Methods: Four blind subjects implanted with Argus II retinal prostheses participated in this study. Each subject attempted to touch a single 4°–7° white target that was randomly located on an otherwise black touchscreen in a target localization task. Touch response accuracy was used to determine the necessary adjustment to eye-camera alignment, the optimal camera alignment position (OCAP). Subjects attended over 100 sessions across up to 5.3 years. S1–S3 were given misaligned cameras for over 1 year. Adaptation was measured through changes in localization errors. Outside that period of intentional misalignment, cameras were aligned to maximize localization accuracy. During the final year, localization tasks were performed in alternation with eye tracking. S2–S4 also participated in 1-day experiments with simultaneous eye tracking and target localization. Results: Subjects were not able to significantly reduce localization error when cameras were misaligned. When trying to maximize localization accuracy, necessary OCAPs changed significantly over time. OCAP trend directions within days and trial runs matched changes between the beginnings of days and runs. Changes between the end of a day or run and the beginning of the next tended to point in the opposite direction of the previous trend, indicating a reset of OCAP changes. Changes in eye orientations correlated significantly with changes in OCAPs. Eye-orientation trends displayed the same reset behavior between days and runs as OCAPs. Simultaneous eye tracking and localization showed agreement between eye-orientation and localization-error trend directions. Adjusting camera alignment with eye-tracking data slowed changes in localization errors. Conclusions: Users of current visual prostheses cannot passively adapt to camera misalignments. OCAPs are not constant with time. Prosthesis users who desire maximum pointing accuracy will require regular camera realignments. Camera alignments based on eye tracking can reduce both transient and long-term changes in localization that are related to eye movements

2015 Oklahoma Research Day Full Program

This document contains all abstracts from the 2015 Oklahoma Research Day held at Northeastern State University

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed