41 research outputs found
A Driving Right Leg Circuit (DgRL) for Improved Common Mode Rejection in Bio-Potential Acquisition Systems
The paper presents a novel Driving Right Leg (DgRL) circuit designed to mitigate the effect of common mode signals deriving, say, from power line interferences. The DgRL drives the isolated ground of the instrumentation towards a voltage which is fixed with respect to the common mode potential on the subject, therefore minimizing common mode voltage at the input of the front-end. The paper provides an analytical derivation of the common mode rejection performances of DgRL as compared to the usual grounding circuit or Driven Right Leg (DRL) loop. DgRL is integrated in a bio-potential acquisition system to show how it can reduce the common mode signal of more than 70 dB with respect to standard patient grounding. This value is at least 30 dB higher than the reduction achievable with DRL, making DgRL suitable for single-ended front-ends, like those based on active electrodes. EEG signal acquisition is performed to show how the system can successfully cancel power line interference without any need for differential acquisition, signal post-processing or filtering
An accurate low-cost Crackmeter with LoRaWAN communication and energy harvesting capability
Structural health monitoring (SHM) systems are becoming increasingly widespread and are in some cases mandated by law. A major factor limiting the diffusion of such systems is the lack of low-cost low-power sensor nodes, which can be deployed in large numbers in hard-to-reach areas, while providing high-quality precise measurements over their entire lifespan with minimum maintenance and withstanding climatic stress. In this paper, we present a cost-effective wireless component for Structural Health Monitoring (SHM) that measure and track cracks in concrete and other construction materials. The sensor combines a microprocessor with LoRaWAN wireless communication, an analog transducer, and a solar energy harvester, allowing long-term remote monitoring with easy plug and play installation. Experimental results demonstrate that we achieved about 1\mu\mathrmm accuracy and an expected lifetime of more than 10 years, with stable measurements across a-IS-65°C temperature range
Parametric Detection and Classification of Compact Conductivity Contrasts With Electrical Impedance Tomography
Electrical impedance tomography is a noninvasive and cost-effective imaging method that is increasingly attractive in the field of medical diagnostics. Several health conditions, such as stroke and solid tumors, are characterized by compact conductivity anomalies surrounded by a fairly regular background. Commonly employed voxel-by-voxel reconstruction methods for impedance imaging share the disadvantages of high computational cost and substantial sensitivity to measurement noise and imperfections in the electrical model describing the domain of interest. We present a special purpose algorithm for automatic detection and identification of compact conductivity variations. The technique exploits a priori structural information and, by reconstructing only the limited number of parameters required to describe a compact conductivity contrast, does not depend on a critical regularization parameter. The most demanding kernels are implemented to run on graphics processing units to accelerate computation. The parametric reconstruction is quicker and more robust than widely employed approaches with respect to measurement noise and imperfections in the electrical model, as shown by computational analysis performed on a segmented head domain and experimental measurements acquired on a cylindrical phantom. When the goal is quick detection of compact conductivity contrasts in complex 3-D domains, the inclusion of specific constraints relating to the problem considered leads to enhanced quality of reconstruction, making the presented technique a promising alternative to common voxel-by-voxel reconstruction methods
EIT Forward Problem Parallel Simulation Environment with Anisotropic Tissue and Realistic Electrode Models
Electrical impedance tomography (EIT) is an imaging technology based on impedance measurements. To retrieve
meaningful insights from these measurements, EIT relies on detailed knowledge of the underlying electrical properties of the body.
This is obtained from numerical models of current flows therein.
The nonhomogeneous and anisotropic electric properties of human
tissues make accurate modeling and simulation very challenging,
leading to a tradeoff between physical accuracy and technical feasibility, which at present severely limits the capabilities of EIT. This work presents a complete algorithmic flow for an accurate EIT
modeling environment featuring high anatomical fidelity with a
spatial resolution equal to that provided by an MRI and a novel realistic complete electrode model implementation. At the same time, we demonstrate that current graphics processing unit (GPU)-based platforms provide enough computational power that a domain discretized with five million voxels can be numerically modeled in about 30 s
EEG acquisition system based on active electrodes with common-mode interference suppression by Driving Right Leg circuit
We present a system for the acquisition of EEG signals based on active electrodes and implementing a Driving Right Leg circuit (DgRL). DgRL allows for single-ended amplification and analog-to-digital conversion, still guaranteeing a common mode rejection in excess of 110 dB. This allows the system to acquire high-quality EEG signals essentially removing network interference for both wet and dry-contact electrodes. The front-end amplification stage is integrated on the electrode, minimizing the system's sensitivity to electrode contact quality, cable movement and common mode interference. The A/D conversion stage can be either integrated in the remote back-end or placed on the head as well, allowing for an all-digital communication to the back-end. Noise integrated in the band from 0.5 to 100 Hz is comprised between 0.62 and 1.3 μV, depending on the configuration. Current consumption for the amplification and A/D conversion of one channel is 390 μA. Thanks to its low noise, the high level of interference suppression and its quick setup capabilities, the system is particularly suitable for use outside clinical environments, such as in home care, brain-computer interfaces or consumer-oriented applications
Active Electrode IC for EEG and Electrical Impedance Tomography with Continuous monitoring of contact impedance
The IC presented integrates the front-end for EEG and Electrical Impedance Tomography (EIT) acquisition on the electrode, together with electrode-skin contact impedance monitoring and EIT current generation, so as to improve signal quality and integration of the two techniques for brain imaging applications. The electrode size is less than 2 cm(2) and only 4 wires connect the electrode to the back-end. The readout circuit is based on a Differential Difference Amplifier and performs single-ended amplification and frequency division multiplexing of the three signals that are sent to the back-end on a single wire which also provides power supply. Since the system's CMRR is a function of each electrode's gain accuracy, an analysis is performed on how this is influenced by mismatches in passive and active components. The circuit is fabricated in 0.35 μm CMOS process and occupies 4 mm(2), the readout circuit consumes 360 μW, the input referred noise for bipolar EEG signal acquisition is 0.56 μVRMS between 0.5 and 100 Hz and almost halves if only EEG signal is acquired
On the simulation of fast settling charge pump PLLs up to fourth order
In this paper, we discuss three different models for the simulation of integer-N charge-pump phase-locked loops (PLLs), namely the continuous-time s-domain and discrete time z-domain approximations and the exact semi-analytical time-domain model. The limitations of the two approximated models are analyzed in terms of error in the computed settling time as a function of loop parameters, deriving practical conditions under which the different models are reliable for fast settling PLLs up to fourth order. Besides, output spectral purity analysis methods based upon the time-domain model are introduced and the results are compared with those obtained by means of the s-domain model in terms of phase noise and reference spur estimation. As a case study, we use the three models to analyze a fast switching PLL to be integrated in a frequency synthesizer for WiMedia MB-OFDM UWB systems
A CMOS 90 nm 55 mW 3.4-to-9.2 GHz 12 Band frequency synthesizer for MB-OFDM UWB
A frequency synthesizer for UWB MB-OFDM applications is designed in TSMC 90 nm CMOS technology. It is based on two wideband PLLs capable of settling in less than 300 ns with a 66 MHz external reference. The PLL tuning range (6.6–9.2 GHz) is extended down to 3.4 GHz by a dedicated circuit able to divide the output frequency by 1, 1.5 and 2 with a power consumption of less than 3 mW. Measured data fit the UWB MB-OFDM specifications with an integrated phase noise of 2.8° RMS at maximum output frequency and an aggregate spurious tone power of less than 27 dBc. The joint power consumption is 55 mW and the synthesizer core area occupies less than 0.5 mm2
A Wearable Device for Minimally-Invasive Behind-the-Ear EEG and Evoked Potentials
We present an unobtrusive and minimally invasive system for acquiring 8-channels of EEG behind the ear, to support brain activity monitoring in a socially acceptable fashion and outside clinical environments. Electrical performance are in line with those of clinical EEG systems (0.48 μVRMS integrated noise in the [0-100] Hz band, 106 dB CMRR) and setup is extremely fast, requiring only a mild cleaning of the skin before applying the device. The system can acquire typical brain activity rhythms and potentials evoked by sensory stimuli, which are at the basis of BCI systems. Current consumption is 6.2 rnA, plus 16 mA for Bluetooth® data transmission (4.5 hours life on a 100 mAh battery). The overall cost of components is below 50 USD
A Four-Shell Diffusion Phantom of the Head for Electrical Impedance Tomography
A four-shell head phantom has been built and characterized. Its structure is similar to that of nonhomogeneous concentric shell domains used by numerical solvers that better approximate current distribution than phantoms currently used to validateelectrical impedance tomography systems. Each shell represents a
head tissue, namely, skin, skull, cerebrospinal fluid, and brain. A
novel technique, which employs a volume conductive impermeable
film, has been implemented to prevent ion diffusion between different agar regions without affecting current distribution inside the phantom. Comparisons between simulations and phantom measurements performed over four days are given to prove both the adherence to the model in the frequency range between 10 kHz and 1 MHz and its long-term stability
