A Compact Self-Capacitance Sensing Analog Front-End for a Touch Detection in Low-Power Mode

Park, Jiheon; Hwang, Young‐Ha; Oh, Jonghyun; Song, Yoonho; Park, Jun-Eun; Jeong, Deog‐Kyoon

doi:10.1109/islped.2019.8824937

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…These are several reasons why analog circuits are used in sensor interfaces like the capacitive sensing front end demonstrated in [19] and the delay line for ultrasonic imaging demonstrated in [20]. ASPs are also widely used in biopotential acquisition and analysis systems, finding recent applications in the current-mode front-end proposed in [21] and the electrocardiogram feature detector proposed in [22].…”

Section: Proposal Novelty and Overviewmentioning

confidence: 99%

An Acoustic Vehicle Detector and Classifier Using a Reconfigurable Analog/Mixed-Signal Platform

Bhattacharyya

Andryzcik

Graham

2020

JLPEA

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The wireless sensor nodes used in a growing number of remote sensing applications are deployed in inaccessible locations or are subjected to severe energy constraints. Audio-based sensing offers flexibility in node placement and is popular in low-power schemes. Thus, in this paper, a node architecture with low power consumption and in-the-field reconfigurability is evaluated in the context of an acoustic vehicle detection and classification (hereafter “AVDC”) scenario. The proposed architecture utilizes an always-on field-programmable analog array (FPAA) as a low-power event detector to selectively wake a microcontroller unit (MCU) when a significant event is detected. When awoken, the MCU verifies the vehicle class asserted by the FPAA and transmits the relevant information. The AVDC system is trained by solving a classification problem using a lexicographic, nonlinear programming algorithm. On a testing dataset comprising of data from ten cars, ten trucks, and 40 s of wind noise, the AVDC system has a detection accuracy of 100%, a classification accuracy of 95%, and no false alarms. The mean power draw of the FPAA is 43 μ W and the mean power consumption of the MCU and radio during its validation and wireless transmission process is 40.9 mW. Overall, this paper demonstrates that the utilization of an FPAA-based signal preprocessor can greatly improve the flexibility and power consumption of wireless sensor nodes.

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Section: Proposal Novelty and Overviewmentioning

confidence: 99%

An Acoustic Vehicle Detector and Classifier Using a Reconfigurable Analog/Mixed-Signal Platform

Bhattacharyya

Andryzcik

Graham

2020

JLPEA

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“…Therefore, it requires offset compensation circuits to remove the effect of the base self-capacitance and maximize the gain for sensing the self-capacitance variation by touch [ 5 ]. Compared to the single-ended SCS system, the fully-differential SCS system [ 6 ], or the charge-sharing-based SCS system [ 7 , 8 ] naturally removes the offset signal because they sense the self-capacitance difference between two adjacent TSP electrodes. However, because of the self-capacitance mismatch between electrode channels, both the fully-differential- and charge-sharing-based SCS systems still suffer from dynamic range degradation.…”

Section: Introductionmentioning

confidence: 99%

Self Capacitance Mismatch Calibration Technique for Fully-Differential Touch Screen Panel Self Capacitance Sensing System

Seong

Lee

Bae

et al. 2023

Sensors

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This paper presents a fully-differential touch screen panel (TSP) self-capacitance sensing (SCS) system with a self-capacitance mismatch calibration technique. Due to the self-capacitance mismatch of TSP, the analog front-end (AFE) of the receiver (RX) circuit suffers from dynamic range degradation and gain limitations, which lead to the signal-to-noise ratio (SNR) loss for the TSP SCS system. The proposed calibration introduces the difference in input resistance and the driving amplifier’s strength between the fully-differential input. Thus, the mismatch effect is efficiently relieved in terms of area and power consumption. The proposed calibration restores the SNR by 19.54 dB even under the worst self-capacitance mismatch case.

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Novel Capacitance Sensing Measurement Technique for Human-Robot Co-existence

Hande

Scherr

Moradian

et al. 2022

2022 Austrochip Workshop on Microelectronics (Austrochip)

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A Compact Self-Capacitance Sensing Analog Front-End for a Touch Detection in Low-Power Mode

Cited by 4 publications

References 13 publications

An Acoustic Vehicle Detector and Classifier Using a Reconfigurable Analog/Mixed-Signal Platform

An Acoustic Vehicle Detector and Classifier Using a Reconfigurable Analog/Mixed-Signal Platform

Self Capacitance Mismatch Calibration Technique for Fully-Differential Touch Screen Panel Self Capacitance Sensing System

Novel Capacitance Sensing Measurement Technique for Human-Robot Co-existence

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