An implantable micro-system for neural prosthesis control and sensory feedback restoration in amputees

In this work, the prototype of an electronic bi-directional interface between the Peripheral Nervous System (PNS) and a neuro-controlled hand prosthesis is presented. The system is composed of two Integrated Circuits (ICs): a standard CMOS device for neural recording and a High Voltage (HV) CMOS device for neural stimulation. The integrated circuits have been realized in two different 0.35μm CMOS processes available fromAustriaMicroSystem(AMS). The recoding IC incorporates 8 channels each including the analog front-end and the A/D conversion based on a sigma delta architecture. It has a total area of 16.8mm2 and exhibits an overall power consumption of 27.2mW. The neural stimulation IC is able to provide biphasic current pulses to stimulate 8 electrodes independently. A voltage booster generates a 17V voltage supply in order to guarantee the programmed stimulation current even in case of high impedances at the electrode-tissue interface in the order of tens of k­. The stimulation patterns, generated by a 5-bit current DAC, are programmable in terms of amplitude, frequency and pulse width. Due to the huge capacitors of the implemented voltage boosters, the stimulation IC has a wider area of 18.6mm2. In addition, a maximum power consumption of 29mW was measured. Successful in-vivo experiments with rats having a TIME electrode implanted in the sciatic nerve were carried out, showing the capability of recording neural signals in the tens of microvolts, with a global noise of 7μVrms , and to selectively elicit the tibial and plantarmuscles using different active sites of the electrode. In order to get a completely implantable interface, a biocompatible and biostable package was designed. It hosts the developed ICs with the minimal electronics required for their proper operation. The package consists of an alumina tube closed at both extremities by two ceramic caps hermetically sealed on it. Moreover, the two caps serve as substrate for the hermetic feedthroughs to enable the device powering and data exchange with the external digital controller implemented on a Field-Programmable Gate Array (FPGA) board. The package has an outer diameter of 7mm and a total length of 26mm. In addition, a humidity and temperature sensor was also included inside the package to allow future hermeticity and life-time estimation tests. Moreover, a wireless, wearable and non-invasive EEG recording system is proposed in order to improve the control over the artificial limb,by integrating the neural signals recorded from the PNS with those directly acquired from the brain. To first investigate the system requirements, a Component-Off-The-Shelf (COTS) device was designed. It includes a low-power 8- channel acquisition module and a Bluetooth (BT) transceiver to transmit the acquired data to a remote platform. It was designed with the aimof creating a cheap and user-friendly system that can be easily interfaced with the nowadays widely spread smartphones or tablets by means of a mobile-based application. The presented system, validated through in-vivo experiments, allows EEG signals recording at different sample rates and with a maximum bandwidth of 524Hz. It was realized on a 19cm2 custom PCB with a maximum power consumption of 270mW

Reconfigurable Receiver Front-Ends for Advanced Telecommunication Technologies

The exponential growth of converging technologies, including augmented reality, autonomous vehicles, machine-to-machine and machine-to-human interactions, biomedical and environmental sensory systems, and artificial intelligence, is driving the need for robust infrastructural systems capable of handling vast data volumes between end users and service providers. This demand has prompted a significant evolution in wireless communication, with 5G and subsequent generations requiring exponentially improved spectral and energy efficiency compared to their predecessors. Achieving this entails intricate strategies such as advanced digital modulations, broader channel bandwidths, complex spectrum sharing, and carrier aggregation scenarios. A particularly challenging aspect arises in the form of non-contiguous aggregation of up to six carrier components across the frequency range 1 (FR1). This necessitates receiver front-ends to effectively reject out-of-band (OOB) interferences while maintaining high-performance in-band (IB) operation. Reconfigurability becomes pivotal in such dynamic environments, where frequency resource allocation, signal strength, and interference levels continuously change. Software-defined radios (SDRs) and cognitive radios (CRs) emerge as solutions, with direct RF-sampling receivers offering a suitable architecture in which the frequency translation is entirely performed in digital domain to avoid analog mixing issues. Moreover, direct RF- sampling receivers facilitate spectrum observation, which is crucial to identify free zones, and detect interferences. Acoustic and distributed filters offer impressive dynamic range and sharp roll off characteristics, but their bulkiness and lack of electronic adjustment capabilities limit their practicality. Active filters, on the other hand, present opportunities for integration in advanced CMOS technology, addressing size constraints and providing versatile programmability. However, concerns about power consumption, noise generation, and linearity in active filters require careful consideration.This thesis primarily focuses on the design and implementation of a low-voltage, low-power RFFE tailored for direct sampling receivers in 5G FR1 applications. The RFFE consists of a balun low-noise amplifier (LNA), a Q-enhanced filter, and a programmable gain amplifier (PGA). The balun-LNA employs noise cancellation, current reuse, and gm boosting for wideband gain and input impedance matching. Leveraging FD-SOI technology allows for programmable gain and linearity via body biasing. The LNA's operational state ranges between high-performance and high-tolerance modes, which are apt for sensitivityand blocking tests, respectively. The Q-enhanced filter adopts noise-cancelling, current-reuse, and programmable Gm-cells to realize a fourth-order response using two resonators. The fourth-order filter response is achieved by subtracting the individual response of these resonators. Compared to cascaded and magnetically coupled fourth-order filters, this technique maintains the large dynamic range of second-order resonators. Fabricated in 22-nm FD-SOI technology, the RFFE achieves 1%-40% fractional bandwidth (FBW) adjustability from 1.7 GHz to 6.4 GHz, 4.6 dB noise figure (NF) and an OOB third-order intermodulation intercept point (IIP3) of 22 dBm. Furthermore, concerning the implementation uncertainties and potential variations of temperature and supply voltage, design margins have been considered and a hybrid calibration scheme is introduced. A combination of on-chip and off-chip calibration based on noise response is employed to effectively adjust the quality factors, Gm-cells, and resonance frequencies, ensuring desired bandpass response. To optimize and accelerate the calibration process, a reinforcement learning (RL) agent is used.Anticipating future trends, the concept of the Q-enhanced filter extends to a multiple-mode filter for 6G upper mid-band applications. Covering the frequency range from 8 to 20 GHz, this RFFE can be configured as a fourth-order dual-band filter, two bandpass filters (BPFs) with an OOB notch, or a BPF with an IB notch. In cognitive radios, the filter’s transmission zeros can be positioned with respect to the carrier frequencies of interfering signals to yield over 50 dB blocker rejection

Algorithm and Hardware Co-design for Learning On-a-chip

abstract: Machine learning technology has made a lot of incredible achievements in recent years. It has rivalled or exceeded human performance in many intellectual tasks including image recognition, face detection and the Go game. Many machine learning algorithms require huge amount of computation such as in multiplication of large matrices. As silicon technology has scaled to sub-14nm regime, simply scaling down the device cannot provide enough speed-up any more. New device technologies and system architectures are needed to improve the computing capacity. Designing specific hardware for machine learning is highly in demand. Efforts need to be made on a joint design and optimization of both hardware and algorithm. For machine learning acceleration, traditional SRAM and DRAM based system suffer from low capacity, high latency, and high standby power. Instead, emerging memories, such as Phase Change Random Access Memory (PRAM), Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM), and Resistive Random Access Memory (RRAM), are promising candidates providing low standby power, high data density, fast access and excellent scalability. This dissertation proposes a hierarchical memory modeling framework and models PRAM and STT-MRAM in four different levels of abstraction. With the proposed models, various simulations are conducted to investigate the performance, optimization, variability, reliability, and scalability. Emerging memory devices such as RRAM can work as a 2-D crosspoint array to speed up the multiplication and accumulation in machine learning algorithms. This dissertation proposes a new parallel programming scheme to achieve in-memory learning with RRAM crosspoint array. The programming circuitry is designed and simulated in TSMC 65nm technology showing 900X speedup for the dictionary learning task compared to the CPU performance. From the algorithm perspective, inspired by the high accuracy and low power of the brain, this dissertation proposes a bio-plausible feedforward inhibition spiking neural network with Spike-Rate-Dependent-Plasticity (SRDP) learning rule. It achieves more than 95% accuracy on the MNIST dataset, which is comparable to the sparse coding algorithm, but requires far fewer number of computations. The role of inhibition in this network is systematically studied and shown to improve the hardware efficiency in learning.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Degradation in FPGAs: Monitoring, Modeling and Mitigation

This dissertation targets the transistor aging degradation as well as the associated thermal challenges in FPGAs (since there is an exponential relation between aging and chip temperature). The main objectives are to perform experimentation, analysis and device-level model abstraction for modeling the degradation in FPGAs, then to monitor the FPGA to keep track of aging rates and ultimately to propose an aging-aware FPGA design flow to mitigate the aging

Integrated Electronics to Control and Readout Electrochemical Biosensors for Implantable Applications

Biosensors can effectively be used to monitor multiple metabolites such as glucose, lactate, ATP and drugs in the human body. Continuous monitoring of these metabolites is essential for patients with chronic or critical conditions. Moreover, this can be used to tune the dosage of a drug for each individual patient, in order to achieve personalized therapy. Implantable medical devices (IMDs) based on biosensors are emerging as a valid alternative for blood tests in laboratories. They can provide continuous monitoring while reduce the test costs. The potentiostat plays a fundamental role in modern biosensors. A potentiostat is an electronic device that controls the electrochemical cell, using three electrodes, and runs the electrochemical measurement. In particular the IMDs require a low-power, fully-integrated, and autonomous potentiostats to control and readout the biosensors. This thesis describes two integrated circuits (ICs) to control and readout multi-target biosensors: LOPHIC and ARIC. They enable chronoamperometry and cyclic voltammetrymeasurements and consume sub-mW power. The design, implementation, characterisation, and validation with biosensors are presented for each IC. To support the calibration of the biosensors with environmental parameters, ARIC includes circuitry to measure the pHand temperature of the analyte through an Iridiumoxide pH sensor and an off-chip resistor-temperature detector (RTD). In particular, novel circuits to convert resistor value into digital are designed for RTD readout. ARIC is integrated into two IMDs aimed for health-care monitoring and personalized therapy. The control and readout of the embedded sensor arrays have been successfully achieved, thanks to ARIC, and validated for glucose and paracetamol measurements while it is remotely powered through an inductive link. To ensure the security and privacy of IMDs, a lightweight cryptographic system (LCS) is presented. This is the first ASIC implementation of a cryptosystem for IMDs, and is integrated into ARIC. The resulting system provides a unique and fundamental capability by immediately encrypting and signing the sensor data upon its creation within the body. Nano-structures such as Carbon nanotubes have been widely used to improve the sensitivity of the biosensors. However, in most of the cases, they introduce more noise into the measurements and produce a large background current. In this thesis the noise of the sensors incorporating CNTs is studied for the first time. The effect of CNTs as well as sensor geometry on the signal to noise ratio of the sensors is investigated experimentally. To remove the background current of the sensors, a differential readout scheme has been proposed. In particular, a novel differential readout IC is designed and implemented that measures inputcurrents within a wide dynamic range and produces a digital output that corresponds to the -informative- redox current of the biosensor

Wearable estimation of central aortic blood pressure.

Arterial hypertension affects a third of the world's population and is a significant risk factor for cardiovascular disease. Blood pressure (BP) is one of the most relevant parameters used for monitoring of possible hypertension states in patients at risk of cardiovascular disease. Hence, there exists a need for new monitoring solutions, which allow to increase the frequency between BP assessments, but also allow to reduce the level of occlusion in the attempts. Moens-Korteweg equation is among the main principles to estimate BP by dispensing of any inflatable cuff. This principle might lead to an indirect estimation of BP by measuring the time it takes the pressure pulse to propagate between two pre-established vascular points, accordingly the pulse transit time (PTT) method. This thesis proposes a wearable PTT-based method to estimate central aortic BP (CABP) and, the main milestones of this work included: proof of concept of the proposed method (pilot work), the development of a wearable device (including two stages of validation), the proposition of a miniaturized version (integrated circuit) of the analog front-end of the wearable hardware, and, the development of a novel PTT-based model (PTTBM, i.e., the mathematical relationship between measured variables and estimated BP) suitable for the proposed wearable methodology to estimate BP. The main contributions found at each milestone are presented. One of the contributions of this thesis is the use of the PTT-principle for estimating CABP instead of the peripheral BP (PBP) (as typically used in the literature). The pilot work showed the feasibility of CABP estimation from the PTT principle by using electrocardiogram (ECG) and ballistocardiogram (BCG) recordings from off-the-shelf equipment. Results showed that CABP was more correlated with the proposed methodology in comparison to all PBP variables assessed; confirming our hypothesis that the CABP is the most suitable parameter to collate through the time elapsed from ECG R-wave to the BCG J-wave. That is, considered featured time (RJ-interval) includes the time of a pulse pressure propagating at an aortic district. Bland-Altman plots showed an almost zero mean error (\u\ < 0.02mmHg) and bounded standard deviation o < 5mmHg for all systolic and mean central BP readings. Pilot work provided a landmark in order to develop a compact device that allows the integration of wireless blood pressure monitoring into a wearable system. Another contribution of this thesis is the proposition of a wearable device for PTT-computing by also including design considerations for the signal conditioning chains for ECG and BCG signals. The proposed design procedure takes care of minimizing the impact of spurious delays between physiological signals, which eventually degrade the PTT computation. Further, such a procedure could be suitable for any PTT-acquisition. Filtering with low and controlled delay is required for this biomedical application, and proposed conditioning chains provide less than 2ms group-delay, showing the effectiveness of the proposed approach. In order to provide the methodology with higher autonomy and integration, a highly miniaturized implementation of the filtering approach was also proposed. It includes the design of proposed architectures in CMOS technology to implement the particular low-delay filtering at reduced bandwidth featuring ultra-low-power characteristics. Results show that less than 2ms delay for the ECG QRS-complex can be achieved with a total current consumption of IDD = 2:1nA at VDD = 1:2V of power supply. Such development meant another significant contribution of this work in the conception of highly autonomous wearable devices for PTT acquisition. The first stage of validations on the wearable CABP estimation showed that, when considering data from one volunteer, results achieved with off-the-shelf equipment could be replicated by using a proposed wearable device, and the method could be further validated by using the wearable version. Additionally, CABP estimation from the proposed wearable device could be feasible by using three feature times (FTs) as CABP surrogates; that is, RI, RJ, and IJ intervals (from ECG and BCG wearable recordings). The first validation of the method also showed that CABP could be accurately predicted by the proposed methodology when in the order of daily calibrations are performed. The second stage of validations involved a study with a group of volunteers, and new alternatives were explored (twentyseven: nine PTTBMs along the three FTs) for the CABP estimation. We found that CABP could be accurately estimated (inside AAMI requirements) through the presented methodology by using four of the explored alternatives, whereas the RI interval, an FT lacking any PTT assessment, emerged as the best surrogate for the CABP estimation. Hence, a principle different from the traditional PTT-based method arises as a more advantageous method for the CABP estimation in the light of evidence reported in this validation, and, to our knowledge, this is the first time that CABP has been successfully estimated from a wearable device. The final significant contribution of this thesis meant the last chain-link in the process to achieve an utterly original method to estimate CABP. A novel PTTBM to estimate CABP is proposed, which uses a ow-driven two-element Windkesel network constructed from FTs extracted from the wearable recordings. When classic PTTBMs are applied, the fitting of parameters often leads to values without a physiological basis. Opposite to that in the proposed PTTBM, the parameters have a clear physiological meaning, and the parameter fitting led to values that are consistent with this meaning and more stable throughout calibrations. In conclusion, this thesis introduces a novel device that exploits an alternative and indirect method for CABP estimation. Variants of the principle used, accordingly, PTT method, have been previously explored to estimate PBP but not for central aortic BP. Additionally, the device was designed to be wearable; that is, it is attached to the clothes, causing low discomfort for the user during the measurement, thus, allowing continuous and ambulatory monitoring of aortic pressure. The developed wearable system, validated in a series of volunteers, showed promising results towards the continuous CABP monitoring.Se estima que casi un tercio de la población adulta mundial sufre de algún grado de hipertensión, siendo esto un factor de riesgo significativo para la enfermedad cardiovascular. La presión arterial (PA) es el parámetro utilizado para evaluar estos posibles estados de hipertensión; actualmente existe una necesidad de generación de nuevas tecnologías que permitan aumentar la frecuencia entre medidas de PA, pero al mismo tiempo de reducir el nivel de oclusión de éstas (técnicas aceptadas están mayoritariamente basadas en la oclusión y son de acceso limitado). El modelo Moens-Korteweg podría proveer los argumentos para la creación de nuevas técnicas para estimar la PA prescindiendo de cualquier brazalete inflable. Más específicamente, podría obtenerse una estimación indirecta de la PA a través de la medición del tiempo que tarda el pulso de presión en propagarse entre dos puntos vasculares predefinidos, método conocido como tiempo de tránsito del pulso (PTT). En la presente tesis se desarrolló un dispositivo vestible que explota este método alternativo e indirecto para la estimación de la PA pero a nivel central, es decir, busca estimar la PA en la aorta (CABP), la principal arteria de la red vascular. Para ello, los principales desarrollos de este trabajo incluyeron : prueba de concepto del método propuesto basado en PTT para estimar CABP, el desarrollo de un dispositivo vestible (incluyendo dos etapas de validaciones para la estimación de la PA), la propuesta de un circuito integrado para el hardware vestible y el desarrollo de un nuevo modelo para la estimación de la PA (PTTBM, es decir, la relación matemática que vincula las variables medidas con el hardware diseñado y la estimación de la PA). A continuación se presentan las principales contribuciones resultantes de cada frente de trabajo. Una de las contribuciones de esta tesis es el uso del principio PTT para estimar CABP en lugar de la BP periférica (PBP) (como se usa típicamente en la literatura). La prueba de concepto mostró la viabilidad de la estimación de CABP a partir del principio PTT mediante la adquisición de señales electrocardiograma (ECG) y balistocardiograma (BCG) utilizando equipos comerciales. Los resultados mostraron que CABP estaba más correlacionado con la metodología propuesta en comparación con todas las variables de PBP evaluadas; confirmando nuestra hipótesis de que la CABP sería la variable más adecuada para estimar a partir del tiempo transcurrido desde la onda R del ECG hasta la onda J del BCG. Es decir, el tiempo considerado (intervalo RJ) incluye un tiempo de propagación del pulso de presión a través de un segmento aórtico. Las gráficas de Bland-Altman mostraron un error medio casi nulo (\u\ < 0.02mmHg) y una precisión o < 5mmHg para las variables de presión sistólica y media centrales. La prueba de concepto proporcionó un hito para desarrollar un dispositivo vestible apuntando a la monitorización inalámbrica de la presión arterial en un sistema imperceptible para el usuario. Otra contribución de esta tesis es la propuesta de este dispositivo vestible para la adquisición de la PTT. El desarrollo incluye consideraciones de instrumentación necesarias para el correcto acondicionamiento de las señales ECG y BCG, de las cuales se obtiene la PTT. En particular, el procedimiento de diseño propuesto busca minimizar el impacto de los retrasos espurios entre las señales fisiológicas, que eventualmente degradan la computación de la PTT. Además, dicho procedimiento podría ser aprovechado por otros desarrolladores del método sin importar las definiciones de PTT que éstos usen. La limitación de banda con bajo retardo es necesario para esta aplicación biomédica, y el hardware de acondicionamiento propuesto proporciona menos de 2 ms de retraso en las se~nales (ECG y BCG) mientras consigue limitar sus bandas a decenas de Hz, lo que muestra la efectividad de la metodología propuesta. Adicionalmente, con el fin de proporcionar a la metodología de una mayor autonomía e integración, se propone una implementación altamente miniaturizada de la sección de filtrado con bajo retraso. Se incluye el diseño de nuevas topologías propuestas en tecnología CMOS para implementar el particular filtro de bajo retraso con reducido ancho de banda, y con características de ultra bajo consumo de potencia. El diseño integrado consigue obtener resultados similares al obtenido anteriormente (con componentes discretos) alcanzando un retraso de menos de 2 ms para el complejo QRS del ECG, pero con un consumo de IDD = 2:1 nA a un VDD = 1:2 V . Tal desarrollo significó otra contribución de este trabajo en el área de circuitos altamente autónomos para instrumentación biomédica. La primera etapa de validaciones en la estimación vestible de la CABP se basó en experimentaciones con un voluntario, mostrando que, la estimación vestible podría alcanzar los mismos resultados que los alcanzados utilizando equipos de investigación, permitiendo así avanzar en la validación del método propuesto utilizando el equipamiento vestible diseñado. Además de esto, se encontró que la estimación de CABP a partir del dispositivo vestible podría ser factible utilizando varios tiempos característicos (FT) extraídos de las señales vestibles ECG y BCG (intervalos RI, RJ e IJ) junto con un popular PTTBM. La primera validación del método también arrojó que la metodología propuesta podría estimar con precisión la CABP cuando el tiempo entre calibraciones es del orden de un día. La segunda etapa de validación implicó un estudio con un grupo de voluntarios, nuevas alternativas se exploraron esta vez (veintisiete: nueve PTTBM con tres FT) para la estimación de CABP. Descubrimos que CABP podría estimarse con precisión (dentro de los requisitos de AAMI) a través de la metodología presentada mediante el uso de cuatro de las alternativas exploradas, mientras que el intervalo RI, siendo un FT que a priori no tiene ninguna vinculación con un PTT, surge como el mejor estimador de la CABP. Se concluye entonces, que un principio diferente del método tradicional basado en PTT podría ser más ventajoso para la estimación de CABP a la luz de la evidencia encontrada en esta validación y, adicionalmente, a nuestro entender, esta es la primera vez que CABP se estima con éxito a partir de un dispositivo vestible. La contribución final de esta tesis significó el último eslabón de la cadena en el proceso de lograr un método completamente original para estimar CABP de punta a punta. Se propone un nuevo PTTBM para estimar CABP, éste es basado en una red Windkesel de dos elementos bajo una excitación de flujo. Estos elementos del PTTBM son construidos a partir de cantidades extraídas a través de procesamiento de las señales vestibles ECG y BCG. Cuando se aplican los PTTBM clásicos, el ajuste de sus parámetros (en calibración) a menudo conducen a valores sin base fisiológica, mostrando a su vez, una dispersión en sus valores a lo largo de distintas calibraciones que podrían ser inaceptables en la práctica. En contraposición, los parámetros del PTTBM propuesto convergen a cantidades con significado fisiologico claro y estable a lo largo de las calibraciones. En conclusión, esta tesis presenta un dispositivo novedoso que explota un método alternativo e indirecto para la estimación de CABP. El método propuesto es basado en la metodología de PTT, que si bien ha sido previamente explotado para estimar PBP, no se ha dirigido éste hacia el monitoreo vestible de la PA aórtica central. En este marco se desarrolla un dispositivo vestible, causando baja molestia en el usuario durante las mediciones, lo que permitiría un monitoreo continuo y ambulatorio real de la presión aórtica central. El sistema vestible desarrollado, validado en una serie de voluntarios, ha mostrado resultados prometedores hacia el monitoreo continuo de CABP

Advanced CMOS Integrated Circuit Design and Application

The recent development of various application systems and platforms, such as 5G, B5G, 6G, and IoT, is based on the advancement of CMOS integrated circuit (IC) technology that enables them to implement high-performance chipsets. In addition to development in the traditional fields of analog and digital integrated circuits, the development of CMOS IC design and application in high-power and high-frequency operations, which was previously thought to be possible only with compound semiconductor technology, is a core technology that drives rapid industrial development. This book aims to highlight advances in all aspects of CMOS integrated circuit design and applications without discriminating between different operating frequencies, output powers, and the analog/digital domains. Specific topics in the book include: Next-generation CMOS circuit design and application; CMOS RF/microwave/millimeter-wave/terahertz-wave integrated circuits and systems; CMOS integrated circuits specially used for wireless or wired systems and applications such as converters, sensors, interfaces, frequency synthesizers/generators/rectifiers, and so on; Algorithm and signal-processing methods to improve the performance of CMOS circuits and systems

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

MEMS Accelerometers

Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc