Low noise and low power ECG amplifier using cmos 0.13μm technology

Through the scaling down of modern VLSI technologies, the realization of CMOS based electrocardiogram (ECG) device becoming wearable to its user is possible. Yet, this transition introduces more constraints to its analog circuits. This is due to the measured electrical signal of ECG devices, or known as ECG signal possessed characteristics that are low in frequency (0.1 to 150Hz) and amplitude (<5mV), thus it lead to every ECG devices suffered from flicker noise for low frequency cardiac signal acquisition at the front-end of its sensor, 50 Hz power line electromagnetic interference, and the large unstable input offsets due to the improper attachment of electrode-skin interface. Therefore, to encounter this problem, the frontend of ECG devices, which is amplifier needed to be enhance so it able to accurately detect the ECG signals. Besides that, the amplifier must able to operate at low voltage and less power consumption so that it can be used in wearable device. In this work, a high performance CMOS amplifier for ECG sensors that improves the noise issue and suitable for low power wearable cardiac screening is designed. The designed circuit adopts the folded cascode topology to achieve high gain and less susceptible to noise. This work uses 0.13 μm CMOS process technology from Silterra and Mentor Graphics Pyxis as the design tool. This successfully achieve high CMRR which is 160dB. Besides that, this work also able to reduce the noise at the front-end amplifier system down to 1.28nV/√Hz. The power consumption of the designed amplifier is 3 μW, which is low and suitable to be implemented on design for wearable ECG devices

Brain computer interfaces: an engineering view. Design, implementation and test of a SSVEP-based BCI.

This thesis presents the realization of a compact, yet flexible BCI platform, which, when compared to most commercially-available solution, can offer an optimal trade-off between the following requirements: (i) minimal, easy experimental setup; (ii) flexibility, allowing simultaneous studies on other bio-potentials; (iii) cost effectiveness (e.g. < 1000 €); (iv) robust design, suitable for operation outside lab environments. The thesis encompasses all the project phases, from hardware design and realization, up to software and signal processing. The work started from the development of the hardware acquisition unit. It resulted in a compact, battery-operated module, whose medium-to-large scale production costs are in the range of 300 €. The module features 16 input channels and can be used to acquire different bio-potentials, including EEG, EMG, ECG. Module performance is very good (RTI noise < 1.3 uVpp), and was favourably compared against a commercial device (g.tec USBamp). The device was integrated into an ad-hoc developed Matlab-based platform, which handles the hardware control, as well as the data streaming, logging and processing. Via a specifically developed plug-in, incoming data can also be streamed to a TOBI-interface compatible system. As a demonstrator, the BCI was developed for AAL (Ambient Assisted Living) system-control purposes, having in mind the following requirements: (i) online, self-paced BCI operation (i.e., the BCI monitors the EEG in real-time and must discern between intentional control periods, and non-intentional, rest ones, interpreting the user’s intent only in the first case); (ii) calibration-free approach (“ready-to-use”, “Plug&Play”); (iii) subject-independence (general approach). The choice of the BCI operating paradigm fell on Steady State visual Evoked Potential (SSVEP). Two offline SSVEP classification algorithms were proposed and compared against reference literature, highlighting good performance, especially in terms of lower computational complexity. A method for improving classification accuracy was presented, suitable for use in online, self-paced scenarios (since it can be used to discriminate between intentional control periods and non-intentional ones). Results show a very good performance, in particular in terms of false positives immunity (0.26 min^-1), significantly improving over the state of the art. The whole BCI setup was tested both in lab condition, as well as in relatively harsher ones (in terms of environmental noise and non-idealities), such as in the context of the Handimatica 2014 exhibition. In both cases, a demonstrator allowing control of home appliances through BCI was developed

Ambiente kapazitive EKG-Messung - Elektroden, Systeme und Konzepte

Kapazitive Elektroden sind ein vielversprechender Ansatz für alltagstaugliche EKG-Systeme, da sie Biosignale auch ohne direkten Hautkontakt erfassen können. Im Rahmen der Arbeit werden textile kapazitive Elektroden entwickelt, die für ambiente Szenarien geeignet sind und an 2 Beispielsystemen demonstriert: einem textilintegrierten System zum mobilen EKG-Monitoring, und einem ambienten System zur EKG-Ableitung im Automobil. Daneben werden Konzepte zum Umgang mit Bewegungsartefakten vorgestell

Instrumentación para neuroprótesis vestibles

La tesis pretende contribuir al conocimiento en adquisición de biopotenciales mediante técnicas no invasivas con aplicación a neuroprótesis (NPs). Las NPs son dispositivos que, interactuando con el cuerpo humano, permiten recuperar o reemplazar capacidades perdidas o disminuidas incrementando drásticamente la comodidad e independencia de las personas. Por lo tanto es de interés que las NPs se utilicen de forma muy sencilla y sin asistencia profesional, en correspondencia con el paradigma de los sistemas ``vestibles''. El objetivo general de la tesis es desarrollar etapas de instrumentación que permitan adquirir biopotenciales útiles a las NPs en forma robusta en las condiciones de medida impuestas por los sistemas vestibles. Por lo tanto, se desarrollan sistemas de adquisición de señal mixta en el estado del arte como plataformas para validar los modelos y circuitos de acondicionamiento propuestos, y se diseñan, implementan y verifican experimentalmente circuitos de acondicionamiento analógico que permiten enfrentar este desafío. En primer lugar, se desarrolla un circuito de realimentación de modo común con ganancia aumentada como estrategia general para la robustez frente a interferencia electromagnética. En segundo lugar se proponen electrodos activos para la medición de señales de electromiograma, desarrollando herramientas de análisis e implementando amplificadores para electrodos de múltiples contactos. Finalmente, los electrodos secos son el factor clave del registro de biopotenciales en sistemas vestibles. Por lo tanto, se desarrolla un electrodo activo con impedancia de entrada aumentada utilizando bootstrap de fuente y conservando una topología de baja complejidad.This thesis contributes to the topic of non-invasive biopotential acquisition techniques applied to Neuroprostheses (NPs). NPs are technological devices that, through interaction with the body, allow to recover or replace lost or diminished capabilities, thus dramatically increasing the comfort and independence of a person. It is desirable for NPs to be able to be used in a simple manner without professional assistance, in correspondence with the paradigm of wearable devices. The general objective of the thesis is to develop instrumentation circuits which allow to acquire the biopotential signals that NPs need robustly, even under the measurement conditions imposed by wearable systems. Therefore, state of the art mixed-signal acquisition systems are developed as a platform upon which models and conditioning circuits can be validated, and a set of analog conditioning circuits are designed, implemented, and experimentally tested. First, a common mode feedback circuit with increased gain is developed as a general strategy for increased robustness against electromagnetic interference. Next, active electrodes for electromyography signal measurement are proposed. An analysis tool as well as an implementation alternative for multiple-input electrodes are proposed. Finally, dry-contact electrodes are a key factor in wearable biopotential measurements. Hence, an active electrode with increased input impedance is developed using power supply bootstrapping and a low complexity topology.Facultad de Ingenierí

Améliorer les interactions homme-machine et la présence sociale avec l’informatique physiologique

This thesis explores how physiological computing can contribute to human-computer interaction (HCI) and foster new communication channels among the general public. We investigated how physiological sensors, such as electroencephalography (EEG), could be employed to assess the mental state of the users and how they relate to other evaluation methods. We created the first brain-computer interface that could sense visual comfort during the viewing of stereoscopic images and shaped a framework that could help to assess the over all user experience by monitoring workload, attention and error recognition.To lower the barrier between end users and physiological sensors,we participated in the software integration of a low-cost and open hardware EEG device; used off-the shelf webcams to measure heart rate remotely, crafted we arables that can quickly equip users so that electrocardiography, electrodermal activity or EEG may be measured during public exhibitions. We envisioned new usages for our sensors, that would increase social presence. In a study about human-agent interaction, participants tended to prefer virtual avatars that were mirroring their own internal state. A follow-up study focused on interactions between users to describe how physiological monitoringcould alter our relationships. Advances in HCI enabled us to seam lesslyintegrate biofeedback to the physical world. We developped Teegi, apuppet that lets novices discover by themselves about their brain activity. Finally, with Tobe, a toolkit that encompasses more sensors and give more freedom about their visualizations, we explored how such proxy shifts our representations, about our selves as well as about the others.Cette thèse explore comment l’informatique physiologique peut contribuer aux interactions homme-machine (IHM) et encourager l’apparition de nouveaux canaux de communication parmi le grand public. Nous avons examiné comment des capteurs physiologiques,tels que l’électroencéphalographie (EEG), pourraient être utilisés afin d’estimer l’état mental des utilisateurs et comment ils se positionnent par rapport à d’autres méthodes d’évaluation. Nous avons créé la première interface cerveau-ordinateur capable de discriminer le confort visuel pendant le visionnage d’images stéréoscopiques et nous avons esquissé un système qui peux aider à estimer l’expérience utilisateur dans son ensemble, en mesurant charge mentale, attention et reconnaissance d’erreur. Pour abaisser la barrière entre utilisateurs finaux et capteurs physiologiques, nous avons participé à l’intégration logicielle d’un appareil EEG bon marché et libre, nous avons utilisé des webcams du commerce pour mesurer le rythme cardiaque à distance, nous avons confectionné des wearables dont les utilisateurs peuvent rapidement s’équiper afin qu’électrocardiographie, activité électrodermale et EEG puissent être mesurées lors de manifestations publiques. Nous avons imaginé de nouveaux usages pour nos capteurs, qui augmenteraient la présence sociale. Dans une étude autour de l’interaction humain agent,les participants avaient tendance à préférer les avatars virtuels répliquant leurs propres états internes. Une étude ultérieure s’est concentrée sur l’interaction entre utilisateurs, profitant d’un jeu de plateau pour décrire comment l’examen de la physiologie pourrait changer nos rapports. Des avancées en IHM ont permis d’intégrer de manière transparente du biofeedback au monde physique. Nous avons développé Teegi, une poupée qui permet aux novices d’en découvrir plus sur leur activité cérébrale, par eux-mêmes. Enfin avec Tobe, un toolkit qui comprend plus de capteurs et donne plus de liberté quant à leurs visualisations, nous avons exploré comment un tel proxy décalenos représentations, tant de nous-mêmes que des autres

Innovaciones en sistemas e interfaces humano-máquina: aplicación a las tecnologías de rehabilitación

La presente Tesis Doctoral se ha desarrollado en el entorno de trabajo del Laboratorio de Electrónica y Bioingeniería de la Universidad de Valladolid, que enfoca su actividad en varias líneas de investigación dedicadas a la asistencia de discapacitados mediante la aplicación de Tecnologías de Rehabilitación (TR). Concretamente, la labor investigadora del autor se ha centrado en la implementación de diferentes interfaces persona-máquina, innovadoras y adaptadas a la discapacidad, cuya finalidad es facilitar la interacción del usuario con su entorno. Con objeto de aportar una funcionalidad práctica, el autor de la Tesis ha participado, sustancialmente, en el desarrollo de diferentes dispositivos y sistemas que incorporasen sus innovaciones técnicas. Estos trabajos están orientados a conseguir ayudas para mejorar la autonomía personal, además de entrenadores de rehabilitación para personas con discapacidades severas.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería Telemátic