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

Low Power Personalized ECG Based System Design Methodology for Remote Cardiac Health Monitoring

This paper describes a mixed-signal ECG system for personalized and remote cardiac health monitoring. The novelty of this work is four-fold. Firstly, a low power analog front end with an efficient automatic gain control mechanism, maintaining the input of the ADC to a level rendering optimum SNR and the enhanced recyclic folded cascode opamp used as an integrator for ADC. Secondly, a novel on-the-fly PQRST Boundary Detection (BD) methodology is formulated for finding the boundaries in continuous ECG signal. Thirdly, a novel low-complexity ECG feature extraction architecture is designed by reusing the same module present in the proposed BD methodology. Fourthly, the system is having the capability to reconfigure the proposed Low power ADC for low (8 bits) and high (12 bits) resolution with the use of the feedback signal obtained from the digital block when it is in processing. The proposed system has been tested and validated on patient’s data from PTBDB, CSEDB and in-house IIT Hyderabad DB (IITHDB) and we have achieved an accuracy of 99% upon testing on various normal and abnormal ECG signals. The whole system is implemented in 180 nm technology resulting in 9.47W (@ 1 MHz) power consumption and occupying 1.74mm2 silicon area

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

PROCESS AWARE ANALOG-CENTRIC SINGLE LEAD ECG ACQUISITION AND CLASSIFICATION CMOS FRONTEND

The primary objective of this research work is the development of a low power single-lead ECG analog front-end (AFE) architecture which includes acquisition, digitization, process aware efficient gain and frequency control mechanism and a low complexity classifier for the detecting asystole, extreme bardycardia and tachycardia. Recent research on ECG recording systems focuses on the design of a compact single-lead wearable/portable devices with ultra-low-power consumption and in-built hardware for diagnosis and prognosis. Since, the amplitude of the ECG signal varies from hundreds of µV to a few mV, and has a bandwidth of DC to 250 Hz, conventional front-ends use an instrument amplifier followed by a programmable gain amplifier (PGA) to amplify the input ECG signal appropriately. This work presents an mixed signal ECG fronted with an ultra-low power two-stage capacitive-coupled signal conditioning circuit (or an AFE), providing programmable amplification along with tunable 2nd order high pass and lowpass filter characteristics. In the contemporary state-of-the-art ECG recording systems, the gain of the amplifier is controlled by external digital control pins which are in turn dynamically controlled through a DSP. Therefore, an efficient automatic gain control mechanism with minimal area overhead and consuming power in the order of nano watts only. The AGC turns the subsequent ADC on only after output of the PGA (or input of the ADC) reaches a level for which the ADC achieves maximum signal-to-noise-ratio (SNR), hence saving considerable startup power and avoiding the use of DSP. Further, in any practical filter design, the low pass cut-off frequency is prone to deviate from its nominal value across process and temperature variations. Therefore, post-fabrication calibration is essential, before the signal is fed to an ADC, to minimize this deviation, prevent signal degradation due to aliasing of higher frequencies into the bandwidth for classification of ECG signals, to switch to low resolution processing, hence saving power and enhances battery lifetime. Another short-coming noticed in the literature published so far is that the classification algorithm is implemented in digital domain, which turns out to be a power hungry approach. Moreover, Although analog domain implementations of QRS complexes detection schemes have been reported, they employ an external micro-controller to determine the threshold voltage. In this regard, finally a power-efficient low complexity CMOS fully analog classifier architecture and a heart rate estimator is added to the above scheme. It reduces the overall system power consumption by reducing the computational burden on the DSP. The complete proposed scheme consists of (i) an ultra-low power QRS complex detection circuit using an autonomous dynamic threshold voltage, hence discarding the need of any external microcontroller/DSP and calibration (ii) a power efficient analog classifier for the detection of three critical alarm types viz. asystole, extreme bradycardia and tachycardia. Additionally, a heart rate estimator that provides the number of QRS complexes within a period of one minute for cardiac rhythm (CR) and heart rate variability (HRV) analysis. The complete proposed architecture is implemented in UMC 0.18 µm CMOS technology with 1.8 V supply. The functionality of each of the individual blocks are successfully validated using postextraction process corner simulations and through real ECG test signals taken from the PhysioNet database. The capacitive feedback amplifier, Σ∆ ADC, AGC and the AFT are fabricated, and the measurement results are discussed here. The analog classification scheme is successfully validated using embed NXP LPC1768 board, discrete peak detector prototype and FPGA software interfac

Data Conversion Within Energy Constrained Environments

Within scientific research, engineering, and consumer electronics, there is a multitude of new discrete sensor-interfaced devices. Maintaining high accuracy in signal quantization while staying within the strict power-budget of these devices is a very challenging problem. Traditional paths to solving this problem include researching more energy-efficient digital topologies as well as digital scaling.;This work offers an alternative path to lower-energy expenditure in the quantization stage --- content-dependent sampling of a signal. Instead of sampling at a constant rate, this work explores techniques which allow sampling based upon features of the signal itself through the use of application-dependent analog processing. This work presents an asynchronous sampling paradigm, based off the use of floating-gate-enabled analog circuitry. The basis of this work is developed through the mathematical models necessary for asynchronous sampling, as well the SPICE-compatible models necessary for simulating floating-gate enabled analog circuitry. These base techniques and circuitry are then extended to systems and applications utilizing novel analog-to-digital converter topologies capable of leveraging the non-constant sampling rates for significant sample and power savings

CMOS Hyperbolic Sine ELIN filters for low/audio frequency biomedical applications

Hyperbolic-Sine (Sinh) filters form a subclass of Externally-Linear-Internally-Non- Linear (ELIN) systems. They can handle large-signals in a low power environment under half the capacitor area required by the more popular ELIN Log-domain filters. Their inherent class-AB nature stems from the odd property of the sinh function at the heart of their companding operation. Despite this early realisation, the Sinh filtering paradigm has not attracted the interest it deserves to date probably due to its mathematical and circuit-level complexity. This Thesis presents an overview of the CMOS weak inversion Sinh filtering paradigm and explains how biomedical systems of low- to audio-frequency range could benefit from it. Its dual scope is to: consolidate the theory behind the synthesis and design of high order Sinh continuous–time filters and more importantly to confirm their micro-power consumption and 100+ dB of DR through measured results presented for the first time. Novel high order Sinh topologies are designed by means of a systematic mathematical framework introduced. They employ a recently proposed CMOS Sinh integrator comprising only p-type devices in its translinear loops. The performance of the high order topologies is evaluated both solely and in comparison with their Log domain counterparts. A 5th order Sinh Chebyshev low pass filter is compared head-to-head with a corresponding and also novel Log domain class-AB topology, confirming that Sinh filters constitute a solution of equally high DR (100+ dB) with half the capacitor area at the expense of higher complexity and power consumption. The theoretical findings are validated by means of measured results from an 8th order notch filter for 50/60Hz noise fabricated in a 0.35μm CMOS technology. Measured results confirm a DR of 102dB, a moderate SNR of ~60dB and 74μW power consumption from 2V power supply

Design and implementation of ultra-low-power sensor interface circuits for ECG acquisition

Master'sMASTER OF ENGINEERIN

Investigation of an ultra wideband noise sensor for health monitoring

Quick on-scene assessment and early intervention is the key to reduce the mortality of stroke and trauma patients, and it is highly desirable to develop ambulance-based diagnostic and monitoring devices in order to provide additional support to the medical personnel. We developed a compact and low cost ultra wideband noise sensor for medical diagnostics and vital sign monitoring in pre-hospital settings. In this work, we demonstrated the functionality of the sensor for respiration and heartbeat monitoring. In the test, metronome was used to manipulate the breathing pattern and the heartbeat rate reference was obtained with a commercial electrocardiogram (ECG) device. With seventeen tests performed for respiration rate detection, sixteen of them were successfully detected. The results also show that it is possible to detect the heartbeat rate accurately with the developed sensor

Low-Power Wireless Medical Systems and Circuits for Invasive and Non-Invasive Applications

Approximately 75% of the health care yearly budget of public health systems around the world is spent on the treatment of patients with chronic diseases. This, along with advances on the medical and technological fields has given rise to the use of preventive medicine, resulting on a high demand of wireless medical systems (WMS) for patient monitoring and drug safety research. In this dissertation, the main design challenges and solutions for designing a WMS are addressed from system-level, using off-the-shell components, to circuit implementation. Two low-power oriented WMS aiming to monitor blood pressure of small laboratory animals (implantable) and cardiac-activity (12-lead electrocardiogram) of patients with chronic diseases (wearable) are presented. A power consumption vs. lifetime analysis to estimate the monitoring unit lifetime for each application is included. For the invasive/non-invasive WMS, in-vitro test benches are used to verify their functionality showing successful communication up to 2.1 m/35 m with the monitoring unit consuming 0.572 mA/33 mA from a 3 V/4.5 V power supply, allowing a two-year/ 88-hour lifetime in periodic/continuous operation. This results in an improvement of more than 50% compared with the lifetime commercial products. Additionally, this dissertation proposes transistor-level implementations of an ultra-low-noise/low-power biopotential amplifier and the baseband section of a wireless receiver, consisting of a channel selection filter (CSF) and a variable gain amplifier (VGA). The proposed biopotential amplifier is intended for electrocardiogram (ECG)/ electroencephalogram (EEG)/ electromyogram (EMG) monitoring applications and its architecture was designed focused on improving its noise/power efficiency. It was implemented using the ON-SEMI 0.5 µm standard process with an effective area of 360 µm2. Experimental results show a pass-band gain of 40.2 dB (240 mHz - 170 Hz), input referred noise of 0.47 Vrms, minimum CMRR of 84.3 dBm, NEF of 1.88 and a power dissipation of 3.5 µW. The CSF was implemented using an active-RC 4th order inverse-chebyshev topology. The VGA provides 30 gain steps and includes a DC-cancellation loop to avoid saturation on the sub-sequent analog-to-digital converter block. Measurement results show a power consumption of 18.75 mW, IIP3 of 27.1 dBm, channel rejection better than 50 dB, gain variation of 0-60dB, cut-off frequency tuning of 1.1-2.29 MHz and noise figure of 33.25 dB. The circuit was implemented in the standard IBM 0.18 µm CMOS process with a total area of 1.45 x 1.4 mm^(2). The presented WMS can integrate the proposed biopotential amplifier and baseband section with small modifications depending on the target signal while using the low-power-oriented algorithm to obtain further power optimization