Low-Power Tracking Image Sensor Based on Biological Models of Attention

This paper presents implementation of a low-power tracking CMOS image sensor based on biological models of attention. The presented imager allows tracking of up to N salient targets in the field of view. Employing "smart" image sensor architecture, where all image processing is implemented on the sensor focal plane, the proposed imager allows reduction of the amount of data transmitted from the sensor array to external processing units and thus provides real time operation. The imager operation and architecture are based on the models taken from biological systems, where data sensed by many millions of receptors should be transmitted and processed in real time. The imager architecture is optimized to achieve low-power dissipation both in acquisition and tracking modes of operation. The tracking concept is presented, the system architecture is shown and the circuits description is discussed.

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.

Image Sensors in Security and Medical Applications

This paper briefly reviews CMOS image sensor technology and its utilization in security and medical applications. The role and future trends of image sensors in each of the applications are discussed. To provide the reader deeper understanding of the technology aspects the paper concentrates on the selected applications such as surveillance, biometrics, capsule endoscopy and artificial retina. The reasons for concentrating on these applications are due to their importance in our daily life and because they present leading-edge applications for imaging systems research and development. In addition, review of image sensors implementation in these applications allows the reader to investigate image sensor technology from the technical and from other views as well.

Improving the efficiency of PV low-power processing circuits by selecting an optimal inductor current of the DC/DC converter

In the context of autonomous sensors powered by small-size photovoltaic (PV) panels, this work analyses how the efficiency of DC/DC-converter-based power processing circuits can be improved by an appropriate selection of the inductor current that transfers the energy from the PV panel to a storage unit. Each component of power losses (fixed, conduction and switching losses) involved in the DC/DC converter specifically depends on the average inductor current so that there is an optimal value of this current that causes minimal losses and, hence, maximum efficiency. Such an idea has been tested experimentally using two commercial DC/DC converters whose average inductor current is adjustable. Experimental results show that the efficiency can be improved up to 12% by selecting an optimal value of that current, which is around 300-350 mA for such DC/DC converters.

Comparison of low-power wireless communication technologies for wearable health-monitoring applications

Health monitoring technologies such as Body Area Network (BAN) systems has gathered a lot of attention during the past few years. Largely encouraged by the rapid increase in the cost of healthcare services and driven by the latest technological advances in Micro-Electro-Mechanical Systems (MEMS) and wireless communications. BAN technology comprises of a network of body worn or implanted sensors that continuously capture and measure the vital parameters such as heart rate, blood pressure, glucose levels and movement. The collected data must be transferred to a local base station in order to be further processed. Thus, wireless connectivity plays a vital role in such systems. However, wireless connectivity comes at a cost of increased power usage, mainly due to the high energy consumption during data transmission. Unfortunately, battery-operated devices are unable to operate for ultra-long duration of time and are expected to be recharged or replaced once they run out of energy. This is not a simple task especially in the case of implanted devices such as pacemakers. Therefore, prolonging the network lifetime in BAN systems is one of the greatest challenges. In order to achieve this goal, BAN systems take advantage of low-power in-body and on-body/off-body wireless communication technologies. This paper compares some of the existing and emerging low-power communication protocols that can potentially be employed to support the rapid development and deployment of BAN systems.

A low-power silicon-on-insulator PWM discriminator for biomedical applications

A CMOS/SOI circuit to decode PWM signals is presented as part of a body-implanted neurostimulator for visual prosthesis. Since encoded data is the sole input to the circuit, the decoding technique is based on a double-integration concept and does not require dc filtering. Nonoverlapping control phases are internally derived from the incoming pulses and a fast-settling comparator ensures good discrimination accuracy in the megahertz range. The circuit was integrated on a 2 mu m single-metal SOI fabrication process and has an effective area of 2mm(2) Typically, the measured resolution of encoding parameter a was better than 10% at 6MHz and V-DD=3.3V. Stand-by consumption is around 340 mu W. Pulses with frequencies up to 15MHz and alpha = 10% can be discriminated for V-DD spanning from 2.3V to 3.3V. Such an excellent immunity to V-DD deviations meets a design specification with respect to inherent coupling losses on transmitting data and power by means of a transcutaneous link.

Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.

A novel high-sensitivity, low-power, liquid crystal temperature sensor

A novel temperature sensor based on nematic liquid crystal permittivity as a sensing magnitude, is presented. This sensor consists of a specific micrometric structure that gives considerable advantages from other previous related liquid crystal (LC) sensors. The analytical study reveals that permittivity change with temperature is introduced in a hyperbolic cosine function, increasing the sensitivity term considerably. The experimental data has been obtained for ranges from −6 °C to 100 °C. Despite this, following the LC datasheet, theoretical ranges from −40 °C to 109 °C could be achieved. These results have revealed maximum sensitivities of 33 mVrms/°C for certain temperature ranges; three times more than of most silicon temperature sensors. As it was predicted by the analytical study, the micrometric size of the proposed structure produces a high output voltage. Moreover the voltage’s sensitivity to temperature response can be controlled by the applied voltage. This response allows temperature measurements to be carried out without any amplification or conditioning circuitry, with very low power consumption.

Design of a low power - high temperature heated ceramic sensor to detect halogen gases

The design, construction and optimization of a low power-high temperature heated ceramic sensor to detect leaking of halogen gases in refrigeration systems are presented. The manufacturing process was done with microelectronic assembly and the Low Temperature Cofire Ceramic (LTCC) technique. Four basic sensor materials were fabricated and tested: Li2SiO3, Na2SiO3, K2SiO3, and CaSiO 3. The evaluation of the sensor material, sensor size, operating temperature, bias voltage, electrodes size, firing temperature, gas flow, and sensor life was done. All sensors responded to the gas showing stability and reproducibility. Before exposing the sensor to the gas, the sensor was modeled like a resistor in series and the calculations obtained were in agreement with the experimental values. The sensor response to the gas was divided in surface diffusion and bulk diffusion; both were analyzed showing agreement between the calculations and the experimental values. The sensor with 51.5%CaSiO3 + 48.5%Li 2SiO3 shows the best results, including a stable current and response to the gas. ^

Design of a Low Power – High Temperature Heated Ceramic Sensor to Detect Halogen Gases

The design, construction and optimization of a low power-high temperature heated ceramic sensor to detect leaking of halogen gases in refrigeration systems are presented. The manufacturing process was done with microelectronic assembly and the Low Temperature Cofire Ceramic (LTCC) technique. Four basic sensor materials were fabricated and tested: Li2SiO3, Na2SiO3, K2SiO3, and CaSiO3. The evaluation of the sensor material, sensor size, operating temperature, bias voltage, electrodes size, firing temperature, gas flow, and sensor life was done. All sensors responded to the gas showing stability and reproducibility. Before exposing the sensor to the gas, the sensor was modeled like a resistor in series and the calculations obtained were in agreement with the experimental values. The sensor response to the gas was divided in surface diffusion and bulk diffusion; both were analyzed showing agreement between the calculations and the experimental values. The sensor with 51.5%CaSiO3 + 48.5%Li2SiO3 shows the best results, including a stable current and response to the gas.

Design of a wearable platform for PPG analysis with multicore low-power processor

Photoplethysmography (PPG) sensors allow for noninvasive and comfortable heart-rate (HR) monitoring, suitable for compact wearable devices. However, PPG signals collected from such devices often suffer from corruption caused by motion artifacts. This is typically addressed by combining the PPG signal with acceleration measurements from an inertial sensor. Recently, different energy-efficient deep learning approaches for heart rate estimation have been proposed. To test these new solutions, in this work, we developed a highly wearable platform (42mm x 48 mm x 1.2mm) for PPG signal acquisition and processing, based on GAP9, a parallel ultra low power system-on-chip featuring nine cores RISC-V compute cluster with neural network accelerator and 1 core RISC-V controller. The hardware platform also integrates a commercial complete Optical Biosensing Module and an ARM-Cortex M4 microcontroller unit (MCU) with Bluetooth low-energy connectivity. To demonstrate the capabilities of the system, a deep learning-based approach for PPG-based HR estimation has been deployed. Thanks to the reduced power consumption of the digital computational platform, the total power budget is just 2.67 mW providing up to 5 days of operation (105 mAh battery).

Comparative effects of wavelengths of low-power laser in regeneration of sciatic nerve in rats following crushing lesion

Peripheral nerves are structures that, when damaged, can result in significant motor and sensory disabilities. Several studies have used therapeutic resources with the aim of promoting early nerve regeneration, such as the use of low-power laser. However, this laser therapy does not represent a consensus regarding the methodology, thus yielding controversial conclusions. The objective of our study was to investigate, by functional evaluation, the comparative effects of low-power laser (660 nm and 830 nm) on sciatic nerve regeneration following crushing injuries. Twenty-seven Wistar rats subjected to sciatic nerve injury were divided into three groups: group sham, consisting of rats undergoing simulated irradiation; a group consisting of rats subjected to gallium-aluminum-arsenide (GaAlAs) laser at 660 nm (10 J/cm(2), 30 mW and 0.06 cm(2) beam), and another one consisting of rats subjected to GaAlAs laser at 830 nm (10 J/cm(2), 30 mW and 0.116 cm(2)). Laser was applied to the lesion for 21 days. A sciatic functional index (SFI) was used for functional evaluation prior to surgery and on days 7, 14, and 21 after surgery. Differences in SFI were found between group 660 nm and the other ones at the 14th day. One can observe that laser application at 660 nm with the parameters and methods utilised was effective in promoting early functional recovery, as indicated by the SFI, over the period evaluated.

LOCAL LOW POWER LASER IRRADIATION ACCELERATES THE REGENERATION OF THE FIBULAR NERVE IN RATS

Objective: To study the influence of low power GaAsAl laser irradiation on the regeneration of a peripheral nerve, following a controlled crush injury. Material and methods: The right common fibular nerve of 30 Wistar rats was submitted to a crush injury with an adjustable load forceps (5 000 g, 10 minutes of application). The animals were divided into three groups (n=10), according to the postoperative procedure (no irradiation; sham irradiation; effective irradiation). Laser irradiation (830 nm wave-length; 100 mW emission power; continuous mode; 140 J/cm(2)) was started on the first postoperative day and continued over 21 consecutive days. Body mass, time spent on the walking track and functional peroneal index (PFI) were analyzed based on the hind footprints, both preoperatively and on the 21st postoperative day. Results: Walking time and PFI significantly improved in the group that received effective laser irradiation, despite the significant gain in body mass between the pre- and post-operative periods. Conclusion: Low Power GaAsAl laser irradiation, with the parameters used in our study, accelerated and improved fibular nerve regeneration in rats.

Laser Phototherapy as Topical Prophylaxis Against Head and Neck Cancer Radiotherapy-Induced Oral Mucositis: Comparison Between Low and High/Low Power Lasers

Background and Objective: Oral mucositis is a dose-limiting and painful side effect of radiotherapy (RT) and/or chemotherapy in cancer patients. The purpose of the present study was to analyze the effect of different protocols of laser phototherapy (LPT) on the grade of mucositis and degree of pain in patients under RT. Patients and Methods: Thirty-nine patients were divided into three groups: G1, where the irradiations were done three times a week using low power laser; G2, where combined high and low power lasers were used three time a week; and G3, where patients received low power laser irradiation once a week. The low power LPT was done using an InGaAlP laser (660 nm/40 mW/6 J cm(-2)/0.24 J per point). In the combined protocol, the high power LPT was done using a GaAlAs laser (808 nm, 1 W/cm(2)). Oral mucositis was assessed at each LPT session in accordance to the oral-mucositis scale of the National Institute of the Cancer-Common Toxicity criteria (NIC-CTC). The patient self-assessed pain was measured by means of the visual analogue scale. Results: All protocols of LPT led to the maintenance of oral mucositis scores in the same levels until the last RT session. Moreover, LPT three times a week also maintained the pain levels. However, the patients submitted to the once a week LPT had significant pain increase; and the association of low/high LPT led to increased healing time. Conclusions: These findings are desired when dealing with oncologic patients under RT avoiding unplanned radiation treatment breaks and additional hospital costs. Lasers Surg.Med. 41:264-270,2009. (C) 2009Wiley-Liss, Inc.

Relations between high and low power groups: The importance of legitimacy

Using a social identity perspective, two experiments examined the effects of power and the legitimacy of power differentials on intergroup bias. In Experiment 1, 125 math-science students were led to believe that they had high or low representation in a university decision-making body relative to social-science students and that this power position was either legitimate or illegitimate. Power did not have an independent effect on bias; rather, members of both high and low power groups showed more bias when the power hierarchy was illegitimate than when it was legitimate. This effect was replicated in Experiment 2 (N =105). In addition, Experiment 2 showed that groups located within an unfair power hierarchy expected the superordinate power body to be more discriminatory than did those who had legitimately high or low power. The results are discussed in terms of their implications for group relations.