A 96&amp;#x00D7;96 1V ultra-low power CMOS image sensor for biomedical application

Wang, Tongxi; Huang, Xiwei; Yan, Mei; Yu, Hao; Yeo, Kiat Seng; Cevik, Ismail; Ay, Suat U.

doi:10.1109/apccas.2012.6418959

Cited by 7 publications

(7 citation statements)

References 12 publications

(12 reference statements)

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“…Tong xi Wang et al [ 33 ] designed an ultra-low power CIS particularly used for endomicroscopy applications. This image sensor has a dual operation mode, which leads to self-powering internally.…”

Section: Role Of Cis In Human Body-related Disease Diagnosis Systementioning

confidence: 99%

Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review

Sukhavasi

Elleithy

Abuzneid

et al. 2021

Sensors

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According to the Center for Disease Control and Prevention (CDC), the average human life expectancy is 78.8 years. Specifically, 3.2 million deaths are reported yearly due to heart disease, cancer, Alzheimer’s disease, diabetes, and COVID-19. Diagnosing the disease is mandatory in the current way of living to avoid unfortunate deaths and maintain average life expectancy. CMOS image sensor (CIS) became a prominent technology in assisting the monitoring and clinical diagnosis devices to treat diseases in the medical domain. To address the significance of CMOS image ‘sensors’ usage in disease diagnosis systems, this paper focuses on the CIS incorporated disease diagnosis systems related to vital organs of the human body like the heart, lungs, brain, eyes, intestines, bones, skin, blood, and bacteria cells causing diseases. This literature survey’s main objective is to evaluate the ‘systems’ capabilities and highlight the most potent ones with advantages, disadvantages, and accuracy, that are used in disease diagnosis. This systematic review used PRISMA workflow for study selection methodology, and the parameter-based evaluation is performed on disease diagnosis systems related to the human body’s organs. The corresponding CIS models used in systems are mapped organ-wise, and the data collected over the last decade are tabulated.

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Section: Role Of Cis In Human Body-related Disease Diagnosis Systementioning

confidence: 99%

Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review

Sukhavasi

Elleithy

Abuzneid

et al. 2021

Sensors

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“…The most common CMOS pixel sensor is the active pixel sensor (APS) [6,[13][14][15][16][17][18][19][20][21][22][23][24][25] which has 2 conventional types, namely 3T APS [6,14,18,[21][22][23][24] and 4T APS [13][14][15][16][17][18][19][20]25], as shown in Fig. 3.…”

Section: Active Pixel Sensor (Aps)mentioning

confidence: 99%

“…In particular, 2 types of pixel structure are reviewed. They are active pixel sensor (APS) [6,[13][14][15][16][17][18][19][20][21][22][23][24][25] in Section 2 and pseudo-active pixel sensor (PAPS) [26,27] in Section 3. Then a new sensor called zero bias pixel sensor (ZBPS), that can eliminate dark current, is proposed in Section 4.…”

Section: Introductionmentioning

confidence: 99%

A Zero Bias Pixel Sensor and its Zero-Bias Column Buffer-Direct-Injection Circuit

Suriyavejwongs¹,

Leelarasmee²,

Pora³

2017

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Abstract. Two pixel sensors, namely active pixel sensor (APS) and pseudo-active pixel sensor (PAPS), are reviewed to show that APS suffers from dark current while PAPS suffers from leakage current. Then a new pixel sensor called zero bias pixel sensor (ZBPS) in which only two MOS switches in addition to the photodiode are used, one for connecting the pixel's photodiode to a column bus and the other for bypassing it. A zero-bias column buffer-direct-injection (ZCBDI) circuit, which is similar to a regulated cascode amplifier, is used to control the voltage at column bus at zero. All ZBPS pixels are guaranteed to work at zero voltage at all times to eliminate the dark current as well as leakage current. A case of a 10µm x 10µm ZBPS pixel designed with standard 0.18µm CMOS process is studied through simulation. This pixel generates a photocurrent within a range from 1pA to 100nA. To handle a large variation of photocurrent while maintaining zero column voltage, the ZCBDI is designed using differential cascode, common source, and buffer stages and then compensated for 50 degree phase margin. Transient simulation shows that the pixel steady state response time is around 1.406ms, leading to at most 5.5 frames per second for an image of 128x128 ZBPS pixels. The fill factor of ZBPS for this case is around 59%.

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“…A CMOS image sensor is one device that comprises a two-dimensional pixel array to convert the incident light at its surface into an array of electrical signals [72][73][74].…”

Section: Cmos Image Sensormentioning

confidence: 99%

“…The recent advance of microfluidics-based LOC technology has introduced the possibility for the miniaturized microflow cytometer for potable flow cytometry [131-133, 136, 137]. With the integration of CMOS image sensor chip underneath the microfluidic channel, microfluidics-based lensless imaging systems [44,55,57,61,63,64,73,138] can be developed for portable contact-imaging [43] based microflow cytometer. Illuminated by incoherent light source, the direct projected shadow or contact images of cells can be captured by the image sensor underneath without lenses [44,55,57,61,63,64,138].…”

Section: Microfluidic Contact Imagingmentioning

confidence: 99%

CMOS multimodal sensor based lab-on-a-chip system for personalized bio-imaging diagnosis

Huang¹

Self Cite

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The world population is rapidly ageing with proportion of people aged 60-year-old and over, growing faster than any other age groups. Considering the current aging society, there is an emerging need to develop the future diagnosis with portable biomedical devices by bio-instrument miniaturization. The recent development of labon-a-chip (LOC) technology has provided a promising integration platform of microfluidic channels, microelectromechanical systems (MEMS), and sensors, which allow non-invasive and near-field sensing functions. The standard complimentary metal-oxide semiconductor (CMOS) process allows a low-cost system-on-chip xiii 5.2.3

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A 96×96 1V ultra-low power CMOS image sensor for biomedical application

Cited by 7 publications

References 12 publications

Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review

Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review

A Zero Bias Pixel Sensor and its Zero-Bias Column Buffer-Direct-Injection Circuit

CMOS multimodal sensor based lab-on-a-chip system for personalized bio-imaging diagnosis

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