Jorge Cabral

Smart-Optical Detector CMOS Array for Biochemical Parameters Analysis in Physiological Fluids

This paper describes the implementation of a smart-optical detector array for detection and concentration measurement of biochemical parameters in physiological fluids. Its application is in the low-cost microchip size analytical laboratories that use colorimetric detection, by optical absorption, as the analytical technique. The microlaboratory structure is composed of a microplate cuvette array containing the physiological fluids into analysis and an optical detector array underneath, which quantifies the light absorbed by those fluids. The detectors, together with their analog-to-digital (A/D) conversion, are designed and fabricated using a standard CMOS process. The on-chip A/D conversion is performed, simultaneously, using a 1-b first-order sigma-delta converter for each optical detector. The output signal of the device is a bit stream containing information about the absorbed light, which allows simple microcontroller interfacing. The proposed architecture has the main advantage of performing the simultaneous measurement of the light absorbed by the fluids, which avoids the errors that can be introduced due to light fluctuations in uncontrolled environments. In addition, the architecture allows on-chip calibration during each measurement. This means that the device can be reliably used in environments with noncalibrated light sources, e.g., in a doctors office. The A/D conversion design described here represents significant improvements when compared with the existing designs. Moreover, the microlaboratory application holds great promise, by both improving benefits (quality of health services provided) and reducing costs (of physiological fluid analysis services).

Path loss exponent analysis in Wireless Sensor Networks: Experimental evaluation

Wireless Sensor Networks are an emerging technology which has been recently adopted in many applications. Due to its wireless nature, the analysis of the radio propagation models plays an important role for performance evaluation in both theoretical and practical aspects. In this regards, path loss exponent is one of the most important parameter which has been considered widely in wireless communications analysis. There are several theoretical evaluations of path loss exponent for wireless sensor networks available in the literature. However there is a lack of experimental evaluation of both path loss exponent and the effect of shadowing. In this paper, three environments (free space, in building and industrial), where wireless sensor nodes are widely deployed, have been chosen in order to evaluate the experimental analysis. Path loss and path loss exponent are measured by means of Received Signal Strength Indicator (RSSI) and based on them, the standard deviation of shadowing effect is also calculated. All the measured parameters are compared with the theoretical analysis available in the literatures.

WECO: A wireless platform for monitoring recycling point spots

There is a growing demand for low cost, very low power and reduced size monitoring systems with wireless communications, to be used in different kinds of industrial environments. In several countries waste separation and recycling is a major issue. Consequently, the number of recycling spots has been steadily increasing. In order to ensure that recycle bins are properly maintained, several monitoring solutions have been proposed. These still have several limitations, such as requiring wires for power and/or communications and not being able to fit in all existing types of bins. This paper presents WECO, a wireless embedded solution for monitoring the level of the bins located in recycling spots. The proposed system automatically alerts a remote central station when a bin reaches a programmable filling level, thus avoiding the need to spot check if the bin is full and ensuring that the recycling spot is kept clean. The developed prototype required hardware-software co-design and aimed to meet the above mentioned requirements, resorting to the IEEE 802.15.4 protocol for wireless communications between all nodes in the network, each based on a System-On-Chip (SoC) CC2530 from Texas Instruments. Due to its wireless nature, the architecture requires a battery for power supplying the nodes, with a life time of at least six years. The filling level readings of each bin in a recycling spot is made using an ultrasonic sensor. The data collected by the monitoring platform is then sent to the remote central station that processes it in order to optimize routes and establish a scheduled collection of the recycling spots.

High-Resolution MEMS Inclinometer Based on Pull-In Voltage

High-resolution pull-in-based microelectromechanical system (MEMS) inclinometers are presented in this paper. Pull-in is characterized by the sudden loss of stability in electrostatically actuated parallel-plate structures, and since pull-in voltage is stable and easy to measure, it enables an effective transduction mechanism that does not require complex and stable capacitive readout electronics. The MEMS devices used to test the novel architecture have differential actuation electrodes resulting in two pull-in voltages that change differentially with applied acceleration. Dedicated MEMS microstructures with extra proof mass show high sensitivity; 269 mV/° with a nonlinearity <;0.5% FS (Full Scale of ±23°). The measured noise is limited by the actuation mechanism, setting the sensors resolution at 75

A smart wearable system for sudden infant death syndrome monitoring

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An Open Platform for Seamless Sensor Support in Healthcare for the Internet of Things

°; high above state-of-the-art MEMS devices. [2014-0156].

Towards a lightweight embedded virtualization architecture exploiting ARM TrustZone

Sudden Infant Death Syndrome (SIDS) is one of the major causes of death among infants during their sleep. To increase the safety of the infants, we matched different emergent research fields for the development of Baby Night Watch. This Smart Wearable System (SWS), developed under the context of the European Texas Instruments Innovation Challenge (TIIC) 2015, is composed by the following elements: a Wearable IoT Device, a Gateway and the H Medical Interface. The Wearable IoT Device is a wireless sensor node integrated in a Chest Belt, and it has the capacity to monitor the following parameters: body temperature, heart and breathing rates and body position. After a minimal data processing, this set of information is sent to the Gateway, via ZigBee technology, and it is accessible to the user through the H Medical Interface. If a critical event occurs, the device will trigger an alarm, visible and audible in the proximity, and sends a distress message to a mobile application. The Baby Night Watch is an important tool for medical studies, since it allows the visualization of previous physiological data and export it to different types of datasets. Experimental tests have proven that the SWS has the potential to identify situations that could be potentially life-threatening for an infant.

We-care: An IoT-based health care system for elderly people

Population aging and increasing pressure on health systems are two issues that demand solutions. Involving and empowering citizens as active managers of their health represents a desirable shift from the current culture mainly focused on treatment of disease, to one also focused on continuous health management and well-being. Current developments in technological areas such as the Internet of Things (IoT), lead to new technological solutions that can aid this shift in the healthcare sector. This study presents the design, development, implementation and evaluation of a platform called Common Recognition and Identification Platform (CRIP), a part of the CareStore project, which aims at supporting caregivers and citizens to manage health routines in a seamless way. Specifically, the CRIP offers sensor-based support for seamless identification of users and health devices. A set of initial requirements was defined with a focus on usability limitations and current sensor technologies. The CRIP was designed and implemented using several technologies that enable seamless integration and interaction of sensors and people, namely Near Field Communication and fingerprint biometrics for identification and authentication, Bluetooth for communication with health devices and web services for wider integration with other platforms. Two CRIP prototypes were implemented and evaluated in laboratory during a period of eight months. The evaluations consisted of identifying users and devices, as well as seamlessly configure and acquire vital data from the last. Also, the entire Carestore platform was deployed in a nursing home where its usability was evaluated with caregivers. The evaluations helped assess that seamless identification of users and seamless configuration and communication with health devices is feasible and can help enable the IoT on healthcare applications. Therefore, the CRIP and similar platforms could be transformed into a valuable enabling technology for secure and reliable IoT deployments on the healthcare sector.

A novel seesaw-type RF MEMS switch

Virtualization has been used as the de facto technology to allow multiple operating systems (virtual machines) to run on top of the same hardware platform. In the embedded systems domain, virtualization research has focused on the coexistence of real-time requirements with non-real-time characteristics. However, existent standard software-based virtualization solutions have been shown to negatively impact the overall system, especially in performance, memory footprint and determinism. This work in progress paper presents the implementation of an embedded virtualization architecture through commodity hardware. ARM TrustZone technology is exploited to implement a lightweight virtualization solution with low overhead and high determinism, corroborated by promising preliminary results. Research roadmap is also pointed and discussed.

A customizable and ARINC 653 quasi-compliant hypervisor

In a world with an accelerated population aging, there is an increasingly interest in developing solutions for the elderly living assistance. The Internet of Things is a new reality that is completely changing our everyday life, and promises to revolutionize modern healthcare by enabling a more personalized, preventive and collaborative form of care. Aiming to combine these two important topics, this work presents an IoT-ready solution for the elderly living assistance which is able to monitor and register patients vital information as well as to provide mechanisms to trigger alarms in emergency situations. Its effective low-power/low-cost and wireless characteristics turns this solution suitable to be used anywhere and by anyone, in a discrete and comfortable wristband. Experiments demonstrated a good system performance for the implemented functionalities, and regarding the autonomy we obtained an average battery lifetime of 306 hours (around 12 days). For the working range, the system have proved to perform well within a range of 60 meters before the out-of-range warning being triggered.