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J. Low Power Electron. Appl., Volume 4, Issue 4 (December 2014) , Pages 268-316

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Open AccessArticle Untrimmed Low-Power Thermal Sensor for SoC in 22 nm Digital Fabrication Technology
J. Low Power Electron. Appl. 2014, 4(4), 304-316; https://doi.org/10.3390/jlpea4040304
Received: 30 September 2014 / Revised: 21 November 2014 / Accepted: 24 November 2014 / Published: 9 December 2014
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Abstract
Thermal sensors (TS) are essential for achieving optimized performance and reliability in the era of nanoscale microprocessor and system on chip (SoC). Compiling with the low-power and small die area of the mobile computing, the presented TS supports a wide range of sampling [...] Read more.
Thermal sensors (TS) are essential for achieving optimized performance and reliability in the era of nanoscale microprocessor and system on chip (SoC). Compiling with the low-power and small die area of the mobile computing, the presented TS supports a wide range of sampling frequencies with an optimized power envelope. The TS supports up to 45 K samples/s, low average power consumption, as low as 20 μW, and small core Si area of 0.013 mm2. Advanced circuit techniques are used in order to overcome process variability, ensuring inaccuracy lower than ±2 °C without any calibration. All this makes the presented thermal sensor a cost-effective, low-power solution for 22 nm nanoscale digital process technology. Full article
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Open AccessArticle Ultra-Low Voltage Sixth-Order Low Pass Filter for Sensing the T-Wave Signal in ECGs
J. Low Power Electron. Appl. 2014, 4(4), 292-303; https://doi.org/10.3390/jlpea4040292
Received: 29 September 2014 / Revised: 18 November 2014 / Accepted: 19 November 2014 / Published: 26 November 2014
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Abstract
An ultra-low voltage sixth-order low pass filter topology, suitable for sensing the T-wave signal in an electrocardiogram (ECG), is presented in this paper. This is realized using a cascade connection of second-order building blocks constructed from a sinh-domain two-integrator loop. The performance of [...] Read more.
An ultra-low voltage sixth-order low pass filter topology, suitable for sensing the T-wave signal in an electrocardiogram (ECG), is presented in this paper. This is realized using a cascade connection of second-order building blocks constructed from a sinh-domain two-integrator loop. The performance of the filter has been evaluated using the Cadence Analog Design Environment and the design kit provided by the Austria Mikro Systeme (AMS) 0.35-µm CMOS process. The power consumption of filters was 7.21 nW, while a total harmonic distortion (THD) level of 4% was observed for an input signal of 220 pA. The RMS value of the input referred noise was 0.43 pA, and the simulated value of the dynamic range (DR) was 51.1 dB. A comparison with already published counterparts shows that the proposed topology offers the benefits of 0.5-V supply voltage operation and significantly improved power efficiency. Full article
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Open AccessReview A Survey of Neural Front End Amplifiers and Their Requirements toward Practical Neural Interfaces
J. Low Power Electron. Appl. 2014, 4(4), 268-291; https://doi.org/10.3390/jlpea4040268
Received: 25 August 2014 / Revised: 27 October 2014 / Accepted: 4 November 2014 / Published: 14 November 2014
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Abstract
When designing an analog front-end for neural interfacing, it is hard to evaluate the interplay of priority features that one must upkeep. Given the competing nature of design requirements for such systems a good understanding of these trade-offs is necessary. Low power, chip [...] Read more.
When designing an analog front-end for neural interfacing, it is hard to evaluate the interplay of priority features that one must upkeep. Given the competing nature of design requirements for such systems a good understanding of these trade-offs is necessary. Low power, chip size, noise control, gain, temporal resolution and safety are the salient ones. There is a need to expose theses critical features for high performance neural amplifiers as the density and performance needs of these systems increases. This review revisits the basic science behind the engineering problem of extracting neural signal from living tissue. A summary of architectures and topologies is then presented and illustrated through a rich set of examples based on the literature. A survey of existing systems is presented for comparison based on prevailing performance metrics. Full article
(This article belongs to the Special Issue Low-Power Biomedical Applications)
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J. Low Power Electron. Appl. EISSN 2079-9268 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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