A 213.7-$\mu$ W Gesture Sensing System-On-Chip With Self-Adaptive Motion Detection and Noise-Tolerant Outermost-Edge-Based Feature Extraction in 65 nm

Le, Van Loi; Yoo, Taegeun; Kim, Ju Eon; Baek, Kwang‐Hyun; Kim, Tony Tae-Hyoung

doi:10.1109/lssc.2019.2935560

Cited by 9 publications

(18 citation statements)

References 5 publications

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“…CMOS image sensors are widely used in so-called digital still cameras such as smartphones, compact cameras, and single-lens reflex cameras, as well as in surveillance cameras, industrial applications [1][2][3], object recognition [4][5][6][7][8], ToF sensors for distance measurement [9][10][11], and medical applications [12][13][14]. The performance requirements in these fields are low noise, high speed, wide dynamic range, and high resolution, and various technologies have been reported to improve these performances.…”

Section: Introductionmentioning

confidence: 99%

Circuit Techniques to Improve Low-Light Characteristics and High-Accuracy Evaluation System for CMOS Image Sensor

Kato

Morishita

Okubo

et al. 2022

Sensors

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The surveillance cameras we focus on target the volume zone, and area reduction is a top priority. However, by simplifying the ADC comparator, we face a new RUSH current issue, for which we propose a circuit solution. This paper proposes two novel techniques of column-ADC for surveillance cameras to improve low-light characteristics. RUSH current compensation reduces transient current consumption fluctuations during AD conversion and utilizing timing shift ADCs decreases the number of simultaneously operating ADCs. These proposed techniques improve low-light characteristics because they reduce the operating noise of the circuit. In order to support small signal measurement, this paper also proposes a high-accuracy evaluation system that can measure both small optical/electrical signals in low-light circumstances. To demonstrate these proposals, test chips were fabricated using a 55 nm CIS process and their optical/electrical characteristics were measured. As a result, low-light linearity as optical characteristics were reduced by 63% and column interference (RUSH current) as an electrical characteristic was also reduced by 50%. As for the high-accuracy evaluation system, we confirmed that the inter-sample variation of column interference was 0.05 LSB. This ADC achieved a figure-of-merit (FoM) of 0.32 e-·pJ/step, demonstrating its usefulness for other ADC architectures while using a single-slope-based simple configuration.

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Section: Introductionmentioning

confidence: 99%

Circuit Techniques to Improve Low-Light Characteristics and High-Accuracy Evaluation System for CMOS Image Sensor

Kato

Morishita

Okubo

et al. 2022

Sensors

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show abstract

“…Benefiting from the rapid development of the sensor technologies and the miniaturization of the electronics, the wearable and implantable electronic devices have been widely used in biomedical research Yang et al (2019); Juteau and Gosselin (2020), motion detection Le et al (2019); Dabbaghian et al (2019) and health monitoring Ding et al (2021); Lee et al, 2020b. In such scenarios, the wireless sensor nodes (WSNs) are in charge of monitoring the physical parameters and transmitting the digitized data. It is highly demanded to prolong the usage time of the WSNs while subjecting to small-volume batteries.…”

Section: Introductionmentioning

confidence: 99%

Review of the Multi-Input Single-Inductor Multi-Output Energy Harvesting Interface Applied in Wearable Electronics

Gao

Wang

et al. 2021

Front.Electron.

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Along with the industrialization and popularization of the wearable electronics, an increasing number of the wireless sensor nodes (WSNs) are deployed. Nevertheless, the conventional battery-based power supply system has no longer satisfied the requirement of large-scale WSNs in terms of battery life, which emerges the energy harvesting (EH) technique. In order to combine various of energy sources and drive multi-loads, the multi-input single-inductor multi-output (MISIMO) EH interface applied to wearable electronics is spotlighted. In this mini-review article, the solutions for improving power conversion efficiency (PCE) and output quality in MISIMO EH interface are summarized. Furthermore, the future trends of MISIMO EH interface are also presented.

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“…The RGB camera is widely used in computer vision tasks due to its high resolution, low cost, and abundant color information. Many endeavors [16]- [20] have been made…”

Section: B Rgb Camera-based Hgr Systemsmentioning

confidence: 99%

“…In addition to the aforementioned HGR systems [16]- [18] based on computing- intensive algorithms, some compact HGR systems [19], [20] adopt customized algorithms to achieve a balance between accuracy and power. However, the energyefficient features used in these systems limit the number of gesture types that can be recognized, therefore, constraining the applicable scenarios of the HGR systems.…”

Section: B Rgb Camera-based Hgr Systemsmentioning

confidence: 99%

“…However, the computation-intensive tasks, such as image processing and fingertip localization, were implemented on FPGA whose power was not included in the power analysis. Apart from the aforementioned HGR systems for complex HCI scenarios as in [33], the ultralow-power HGR systems [19], [20] utilizing lite signal processing algorithms have also been proposed. The system on chip (SoC) in [19] can recognize 8 dynamic gestures using the features of the projected histogram with an average accuracy of 90.6%.…”

Section: Pre-processingmentioning

confidence: 99%

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Design of low-power gesture recognition system and self-organizing map processors

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A 213.7-$\mu$ W Gesture Sensing System-On-Chip With Self-Adaptive Motion Detection and Noise-Tolerant Outermost-Edge-Based Feature Extraction in 65 nm

Cited by 9 publications

References 5 publications

Circuit Techniques to Improve Low-Light Characteristics and High-Accuracy Evaluation System for CMOS Image Sensor

Circuit Techniques to Improve Low-Light Characteristics and High-Accuracy Evaluation System for CMOS Image Sensor

Review of the Multi-Input Single-Inductor Multi-Output Energy Harvesting Interface Applied in Wearable Electronics

Design of low-power gesture recognition system and self-organizing map processors

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