Octagonal CMOs image sensor with strobed RGB LED illumination for wireless capsule endoscopy

Yoshizaki, Satoshi; Serb, Alexantrou; Liu, Yan; Constandinou, Timothy G.

doi:10.1109/iscas.2014.6865520

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…5a , for capturing the activity of neural networks in real-time. We envisage an overall system architecture very similar to standard active pixel sensor CMOS imagers 39 . In this hybrid system, data from each of the N pixels in the array arrives as an analogue current from the MEA and is multiplexed onto one of the M on-chip trans-impedance amplifier (TIA) blocks, which are followed by on-chip offset stages.…”

Section: Resultsmentioning

confidence: 99%

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

et al. 2016

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Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology's potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces.

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Section: Resultsmentioning

confidence: 99%

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

et al. 2016

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“…In the future, it is imperative to go beyond this to advanced image processing for diagnosis of visually undetectable disease [159], to map the 3D environment of the given organ using visual simultaneous localization and mapping (SLAM) [160] or optical flow based advanced motion detection algorithms to predict the capsule motion precisely [161], and to propose new active focusing and 3D illumination methods to improve the imaging quality and diagnosis precision [162]. …”

Section: Challenges and Emerging Concepts In Miniaturized Biomedmentioning

confidence: 99%

Biomedical Applications of Untethered Mobile Milli/Microrobots

et al. 2015

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Untethered robots miniaturized to the length scale of millimeter and below attract growing attention for the prospect of transforming many aspects of health care and bioengineering. As the robot size goes down to the order of a single cell, previously inaccessible body sites would become available for high-resolution in situ and in vivo manipulations. This unprecedented direct access would enable an extensive range of minimally invasive medical operations. Here, we provide a comprehensive review of the current advances in biome dical untethered mobile milli/microrobots. We put a special emphasis on the potential impacts of biomedical microrobots in the near future. Finally, we discuss the existing challenges and emerging concepts associated with designing such a miniaturized robot for operation inside a biological environment for biomedical applications.

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“…Once triggered the FSM cannot be re-triggered until the SH bank is full. Finally, the SH circuit is implementable using the switch capacitor circuit topology carrying out correlated double sampling in CMOS imagers [14] (Fig. 3(b)).…”

Section: B Block Descriptionmentioning

confidence: 99%

A memristor-CMOS hybrid architecture concept for on-line template matching

Serb

Papavassiliou

Prodromakis

2017

2017 IEEE International Symposium on Circuits and Systems (ISCAS)

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The ability to identify (detect) and categorise (sort) neural spikes in real-time and under highly restrictive power/area budgets is a major enabling technology towards the development of intelligent implantable systems. In this work we propose a memristor-CMOS hybrid architecture concept that relies on a 'template pixel' (texel) circuit combining CMOS and memristive devices to perform on-line spike sorting through template matching. We show through simulation how the texel is capable of comparing an input voltage against a stored (in the memristors) value and converting the degree of matching between input and stored pattern into a current. We further illustrate the fundamental texel design space that includes tuning it to a different preferred input voltage and controlling the sharpness of the tuning. Finally, we estimate that even in an unoptimised technology and design a texel array capable of recognising three different 10-point patterns will consume a very promising maximum of 3.15 µW for a footprint of approx. 500 µm 2 .

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Octagonal CMOs image sensor with strobed RGB LED illumination for wireless capsule endoscopy

Cited by 4 publications

References 7 publications

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

Biomedical Applications of Untethered Mobile Milli/Microrobots

A memristor-CMOS hybrid architecture concept for on-line template matching

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