Julian Oreggioni

A MOSFET-only voltage source with arbitrary sign adjustable temperature coefficient

A MOS-diode biased by a constant inversion level current source is a simple MOSFET-only circuit that implements a voltage source with a linear temperature dependence. Through adjustment of the inversion level, the temperature slope may be changed from negative to positive, including the constant voltage condition. A test circuit, fabricated on a 0.35μm CMOS technology, was measured from 300K to 375K while sweeping the inversion coefficient from 0.06 to 180. The theoretical model agrees with the measured data, accurately predicting the temperature slope. The presented all-region continuous model is especially useful at and near zero temperature slope operation.

Low-Power Self-Energy Meter for Wireless Sensor Network

Real-time measurement of the energy consumption of wireless sensor network nodes in the field has many interesting applications that range from predicting the remaining battery charge to the energy efficiency assessment of communication protocols. However, designing such a system presents many challenges. In this work we present a measurement method and circuit, named Self-Energy Meter (SEM), that easily adds to a sensor node the capability of measuring its own energy consumption. The SEM developed has very low power consumption, ensuring an almost negligible impact in the battery lifetime. It also solves the problem of handling a dynamic range of five decades. Results from simulations show that the SEM is highly linear, with a coefficient of determination of 0.996, presenting a very low temperature drift, and is almost independent of the power supply.

DC-DC switching converter as on-field self energy meter

A DC-DC switching converter, originally included to reduce the power consumption of a Wireless Sensor Networks (WSN) node, has been proposed as the core of an on-field self-energy meter. In this paper we present a method and circuit that improves the electronics proposed by previous work by conditioning the signal from the switching converter that is connected to the microcontrollers counter. A software module that allows a WSN node to measure its own charge and current consumption was also implemented. The proposed method allows to measure the current consumption in a wide range, from 0 to 30mA, is highly linear and is ultra-low-power (the maximum current consumption is 8μA). Finally, we present a case study in which the proposed method is used to power profile a WSN node. Results show that a time-based estimation (Energest) overestimates the Clear Channel Assessment consumption for more than 10%.

Wearable EEG via lossless compression

This work presents a wearable multi-channel EEG recording system featuring a lossless compression algorithm. The algorithm, based in a previously reported algorithm by the authors, exploits the existing temporal correlation between samples at different sampling times, and the spatial correlation between different electrodes across the scalp. The low-power platform is able to compress, by a factor between 2.3 and 3.6, up to 300sps from 64 channels with a power consumption of 176μW/ch. The performance of the algorithm compares favorably with the best compression rates reported up to date in the literature.This work presents a wearable multi-channel EEG recording system featuring a lossless compression algorithm. The algorithm, based in a previously reported algorithm by the authors, exploits the existing temporal correlation between samples at different sampling times, and the spatial correlation between different electrodes across the scalp. The low-power platform is able to compress, by a factor between 2.3 and 3.6, up to 300sps from 64 channels with a power consumption of 176μW/ch. The performance of the algorithm compares favorably with the best compression rates reported up to date in the literature.

Constraints and design approaches in analog ICs forlmplantable medical devices

Active implantable medical devices (AIMDs) are microsystems requiring ultra low energy operation, which is a characteristic increasingly shared by several other applications. On the other hand, AIMDs must comply with several specific constraints imposed by the medical implantable context. This paper first summarizes, from the point of view of the analog IC designer, the state of the art of AIMDs and their specific constraints. Then, some general design techniques for analog ICs for AIMDs are highlighted and an analog front-end for neural devices is presented to illustrate current circuit and architecture approaches.

Self-energy meter in duty-cycle battery operated sensor nodes

Reduced levels of energy consumption is one of the major goals in Wireless Sensor Networks (WSNs), making the design of a sensor node a challenging task. On-field real-time measurement of the energy consumption of sensor nodes could have a major impact on developing wireless networks. It could be applied to predict the remaining battery charge or to asses the energy efficiency of communication protocols. However, designing such a system presents many challenges that will be discussed in this work. Moreover, we present a measurement method and circuit, named self-energy meter (SEM), that easily adds to a sensor node the capability of measuring its own energy consumption. SEM is a novel approach focused in solving the problem of covering a dynamic range of five decades in duty-cycle battery operated sensor nodes. Experimental results show that SEM has very low power consumption, ensuring an almost negligible impact in the battery lifetime, is highly linear, presents a very low temperature drift, and is almost independent of the power supply.

Integrated programmable analog front-end architecture for physiological signal acquisition

A versatile front-end capable of acquiring a wide range of physiological signals, thus reusing the same design and hardware in different contexts, is a valuable goal both for biomedical research and medical devices. In this work we present such an “all-terrain” programmable integrated front-end architecture and the trade-offs associated to its design. A low noise preamplifier is implemented using a novel architecture based on a differential-difference amplifier which applies gm-C techniques for fixing the cut-off frequencies. Moreover, this architecture is extended to be applied to the other stages of the front-end. The main design trade-offs (noise-power, gain-power, noise-gain and linearity-gain) of the front-end architecture are discussed and their impacts in the design of the processing chain in terms of assignment of gain, noise, linearity and programmability to each stage are shown. The front-end is designed in a 0.5μm CMOS process. The gain is programmable between 57dB and 99dB, the high cut-off frequency is programmable between 116Hz and 5.2kHz, the low cut-off frequency is 18Hz, the maximum power consumption of the front-end is 11.2μA and its maximum equivalent input-referred noise voltage is 1.87μVrms.

Wireless biopotential signals acquisition system

In this paper, we present a low power wireless system based on a MSP430 based system-on-chip for biopotential signals acquisition. The system is capable of recording up to 12 ksps from up to 4 channels with independent gain and a 1 Hz to 5 kHz bandwidth. The gain for each channel may vary from 2.5 kV/V to 68 kV/V, being able to adapt signals in a range of 20 μV to 1 mV, to be digitalized in a 12 bits ADC. The system consists of 2 modules, which communicate wirelessly with each other via a 915 MHz link, with Minimum-shift keying (MSK) modulation. The communication reaches 358 kbps of transmission rate, with less than 2% of packets lost without retransmissions, within a 5 meters range. One of the modules is wired to a PC via a USB cable, reaching 921.6 kbps of transmission rate through UART protocol. The wired module is powered through the USB port, whereas the wireless module is powered with 2 AAA batteries, lasting for more than 24 hours of operation. A Matlab toolbox was developed in order to facilitate the data storage, system configuration as well as collected data analysis.

An analog circuit implementation of a Huber-Braun cold receptor neuron model

We present the design and implementation of an electronic device that, using off the shelf discrete analog components, implements the mathematical model of a cold receptor neuron called Huber-Braun. This model describes the electrical behavior of certain kinds of receptors when interacting with their environment, and it consists of a set of differential equations that has only been solved by numeric simulations. By these means a chaotic behavior has been found. An analog computer can be relevant for further analysis and validation of the model. The results obtained by means of numeric simulations and through our analog circuit simulator are consistent. In particular, temperature and external current bifurcation diagrams were successfully built. Finally, the electronic device allows the observation of all relevant variables and most of the expected behavior (tonic firing, chaotic, burst discharge, subthreshold oscillation and steady state).