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

An Ultra-Low-Power RFID/NFC Frontend IC Using 0.18 μm CMOS Technology for Passive Tag Applications

Battery-less passive sensor tags based on RFID or NFC technology have achieved much popularity in recent times. Passive tags are widely used for various applications like inventory control or in biotelemetry. In this paper, we present a new RFID/NFC frontend IC (integrated circuit) for 13.56 MHz passive tag applications. The design of the frontend IC is compatible with the standard ISO 15693/NFC 5. The paper discusses the analog design part in details with a brief overview of the digital interface and some of the critical measured parameters. A novel approach is adopted for the demodulator design, to demodulate the 10% ASK (amplitude shift keying) signal. The demodulator circuit consists of a comparator designed with a preset offset voltage. The comparator circuit design is discussed in detail. The power consumption of the bandgap reference circuit is used as the load for the envelope detection of the ASK modulated signal. The sub-threshold operation and low-supply-voltage are used extensively in the analog design—to keep the power consumption low. The IC was fabricated using 0.18 μ m CMOS technology in a die area of 1.5 mm × 1.5 mm and an effective area of 0.7 m m 2 . The minimum supply voltage desired is 1.2 V, for which the total power consumption is 107 μ W. The analog part of the design consumes only 36 μ W, which is low in comparison to other contemporary passive tags ICs. Eventually, a passive tag is developed using the frontend IC, a microcontroller, a temperature and a pressure sensor. A smart NFC device is used to readout the sensor data from the tag employing an Android-based application software. The measurement results demonstrate the full passive operational capability. The IC is suitable for low-power and low-cost industrial or biomedical battery-less sensor applications. A figure-of-merit (FOM) is proposed in this paper which is taken as a reference for comparison with other related state-of-the-art researches

Wearable and Nearable Biosensors and Systems for Healthcare

Biosensors and systems in the form of wearables and “nearables” (i.e., everyday sensorized objects with transmitting capabilities such as smartphones) are rapidly evolving for use in healthcare. Unlike conventional approaches, these technologies can enable seamless or on-demand physiological monitoring, anytime and anywhere. Such monitoring can help transform healthcare from the current reactive, one-size-fits-all, hospital-centered approach into a future proactive, personalized, decentralized structure. Wearable and nearable biosensors and systems have been made possible through integrated innovations in sensor design, electronics, data transmission, power management, and signal processing. Although much progress has been made in this field, many open challenges for the scientific community remain, especially for those applications requiring high accuracy. This book contains the 12 papers that constituted a recent Special Issue of Sensors sharing the same title. The aim of the initiative was to provide a collection of state-of-the-art investigations on wearables and nearables, in order to stimulate technological advances and the use of the technology to benefit healthcare. The topics covered by the book offer both depth and breadth pertaining to wearable and nearable technology. They include new biosensors and data transmission techniques, studies on accelerometers, signal processing, and cardiovascular monitoring, clinical applications, and validation of commercial devices

Desenvolvimento de um Sistema de Reconhecimento de Atividades Humanas e Monitoramento Remoto Utilizando um Dispositivo Vestível

Fatores como o envelhecimento da população e o consequente aumento do número de pessoas com doenças crônicas implicam um crescimento exponencial dos custos de assistência médica, visto que o sistema de saúde deve ser capaz de atender a um número cada vez maior de pessoas, mantendo a qualidade do atendimento. Visando redução de custos e melhoria da qualidade, seria desejável um sistema de saúde focado no paciente, no qual se poderia detectar precocemente condições médicas, evitando hospitalizações, bem como acompanhá-los remotamente, evitando a permanência destes no hospital. Nesse contexto, dispositivos de monitoramento remoto tornam-se essenciais para coletar informações importantes de pacientes e torná-las disponíveis ao provedor de saúde. O avanço tecnológico conseguido com a miniaturização de sensores e as novas tecnologias de comunicação sem fio de baixo consumo energético impulsionam o desenvolvimento de sistemas de monitoramento remoto de saúde com dispositivos vestíveis. O presente trabalho propõe o desenvolvimento de um sistema de reconhecimento de atividades humanas e de monitoramento remoto, utilizando três diferentes abordagens. Para a primeira abordagem, conseguiu-se uma acurácia de 89,11% e precisão de 91,45% na classificação de seis diferentes atividades. Já para as duas últimas abordagens, construiu-se a estrutura completa de monitoramento remoto da intensidade das atividades realizadas por uma pessoa, desde a coleta dos dados até o envio por e-mail para acompanhamento à distância pelo provedor de saúde. Os resultados obtidos com o sistema desenvolvido demonstram a sua viabilidade tanto para o reconhecimento de atividades humanas quanto para monitoramento remoto. Palavras-chave: Sistemas Embarcados, Dispositivos Vestíveis, Reconhecimento de Padrões, Reconhecimento de Atividades Humanas, Monitoramento Remoto