The biomimetic CMOS dynamic vision and image sensor described in this paper is based on a QVGA (304×240) array of fully autonomous pixels containing event-based change detection and pulse-width-modulation (PWM) imaging circuitry. Exposure measurements are initiated and carried out locally by the individual pixel that has detected a change of brightness in its field-of-view. Pixels do not rely on external timing signals and independently and asynchronously request access to an (asynchronous arbitrated) output channel when they have new grayscale values to communicate. Pixels that are not stimulated visually do not produce output. The visual information acquired from the scene, temporal contrast and grayscale data, are communicated in the form of asynchronous address-events (AER), with the grayscale values being encoded in inter-event intervals. The pixel-autonomous and massively parallel operation ideally results in lossless video compression through complete temporal redundancy suppression at the pixel level. Compression factors depend on scene activity and peak at ~1000 for static scenes. Due to the time-based encoding of the illumination information, very high dynamic range - intra-scene DR of 143 dB static and 125 dB at 30 fps equivalent temporal resolution - is achieved. A novel time-domain correlated double sampling (TCDS) method yields array FPN of 56 dB (9.3 bit) for >10 Lx illuminance.

A QVGA 143 dB Dynamic Range Frame-Free PWM Image Sensor With Lossless Pixel-Level Video Compression and Time-Domain CDS

The rapid increase in healthcare demand has seen novel developments in health monitoring technologies, such as the body area networks (BAN) paradigm. BAN technology envisions a network of continuously operating sensors, which measure critical physical and physiological parameters e.g., mobility, heart rate, and glucose levels. Wireless connectivity in BAN technology is key to its success as it grants portability and flexibility to the user. While radio frequency (RF) wireless technology has been successfully deployed in most BAN implementations, they consume a lot of battery power, are susceptible to electromagnetic interference and have security issues. Intrabody communication (IBC) is an alternative wireless communication technology which uses the human body as the signal propagation medium. IBC has characteristics that could naturally address the issues with RF for BAN technology. This survey examines the on-going research in this area and highlights IBC core fundamentals, current mathematical models of the human body, IBC transceiver designs, and the remaining research challenges to be addressed. IBC has exciting prospects for making BAN technologies more practical in the future.

A Survey on Intrabody Communications for Body Area Network Applications

State-of-the-art image sensors suffer from significant limitations imposed by their very principle of operation. These sensors acquire the visual information as a series of “snapshot” images, recorded at discrete points in time. Visual information gets time quantized at a predetermined frame rate which has no relation to the dynamics present in the scene. Furthermore, each recorded frame conveys the information from all pixels, regardless of whether this information, or a part of it, has changed since the last frame had been acquired. This acquisition method limits the temporal resolution, potentially missing important information, and leads to redundancy in the recorded image data, unnecessarily inflating data rate and volume. Biology is leading the way to a more efficient style of image acquisition. Biological vision systems are driven by events happening within the scene in view, and not, like image sensors, by artificially created timing and control signals. Translating the frameless paradigm of biological vision to artificial imaging systems implies that control over the acquisition of visual information is no longer being imposed externally to an array of pixels but the decision making is transferred to the single pixel that handles its own information individually. In this paper, recent developments in bioinspired, neuromorphic optical sensing and artificial vision are presented and discussed. It is suggested that bioinspired vision systems have the potential to outperform conventional, frame-based vision systems in many application fields and to establish new benchmarks in terms of redundancy suppression and data compression, dynamic range, temporal resolution, and power efficiency. Demanding vision tasks such as real-time 3-D mapping, complex multiobject tracking, or fast visual feedback loops for sensory-motor action, tasks that often pose severe, sometimes insurmountable, challenges to conventional artificial vision systems, are in reach using bioinspired vision sensing and processing techniques.

Retinomorphic event-based vision sensors: Bioinspired cameras with spiking output

The signal transmission mechanism on the surface of the human body is studied for the application to body channel communication (BCC). From Maxwell's equations, the complete equation of electrical field on the human body is developed to obtain a general BCC model. The mechanism of BCC consists of three parts according to the operating frequencies and channel distances: the quasi-static near-field coupling part, the reactive induction-field radiation part, and the surface wave far-field propagation part. The general BCC model by means of the near-field and far-field approximation is developed to be valid in the frequency range from 100 kHz to 100 MHz and distance up to 1.3 m based on the measurements of the body channel characteristics. Finally, path loss characteristics of BCC are formulated for the design of BCC systems and many potential applications.

The Signal Transmission Mechanism on the Surface of Human Body for Body Channel Communication

http://lightweightcryptography.com/wp-content/papercite-data/pdf/j37camarapt2015.pdf

Security and privacy issues in implantable medical devices

Electric-field intrabody communication (EF-IBC) is a promising new scheme for the data exchange among wearable biomedical sensors. It uses the body as the signal transmission media. Compared with existing body area network (BAN) schemes, EF-IBC can achieve higher data rate with less transmission power. Until now, the detailed EF-IBC channel mechanism is not well understood. In this work, finite-element method (FEM) is utilized for the first time to investigate the EF-IBC channel. A circuit-coupled FEM model is established for the EF-IBC channel. The FEM model is extensively verified by experimental measurements. The new physical model enables the revelation of characteristics and effects of different components in the EF-IBC channel. The FEM investigation finds that the capacitive return path is critical to the characteristics of the EF-IBC channel. Parameters of the capacitive return path are quantitatively measured. The investigation also finds that the body plays an important role to the return path capacitance. The forward body path can be well modeled by a cascade of π-shaped circuits. Based on the FEM model of the EF-IBC channel, a simplified circuit model is derived to provide an efficient tool for the transceiver design.

Electric-Field Intrabody Communication Channel Modeling With Finite-Element Method

Array sensors require a high-performance analog-to-digital converter (ADC) array with small area and low power. Successive-approximation register (SAR) ADC has good potential for ADC array due to its simple analog circuits. However, SAR ADCs with 10-b resolution and higher normally need a large capacitor array due to the stringent matching requirement. The large capacitor array also limits the ADC dynamic performance. The capacitor mismatch has been compensated by analog calibration techniques. In this work, a novel digital calibration method is developed for SAR ADC based on dithering. With dithering, weights of most significant bit (MSB) capacitors can be measured accurately so that very small capacitors can be used in the SAR ADC due to the relaxed matching requirement. A modified bit-cycling procedure is developed to avoid the code gaps caused by capacitor dithering. This calibration technique requires no analog calibration overhead and simple digital decoders. The technique is implemented in an ADC array design including 256 SAR ADCs for a high-speed CMOS imaging sensor in a 0.18-μm CMOS process. The 10-b SAR ADC is designed with the minimum capacitor array size in the process. A single SAR ADC only occupies 15 μm × 710 μm. Sampling at 768 kS/s, peak DNL and peak INL of the original ADCs averaged across the array are 0.82 least significant bit (LSB) and 3.85 LSB, respectively. For a signal close to the Nyquist frequency, original ADCs have 7.96-b average ENOB. After calibration with dithering, ADCs have 0.55-LSB peak DNL and 0.77-LSB peak INL averaged across the array. The average ENOB improves to 9.83 b. Compared with the benchmark 10-b SAR ADCs, this design is the most area-efficient design. In this work, the calibration decoders are implemented off-chip. With a sample-and-hold amplifier, the calibration method can run in the background.

Digitally Calibrated 768-kS/s 10-b Minimum-Size SAR ADC Array With Dithering

Wearableand implantable medical sensors have been investigated continuously in recent years to provide better diagnostics and monitoring for personal health care. Much attention has been drawn to the establishment of the ubiquitous body area network (BAN) to reliably connect the body sensors and collect the sensor data in real time. Electric-held intrabody communication (EF-IBC) is a promising physical link technology for the body area network. Compared to existing wireless technologies, EF-IBC hts the body characteristics better and is able to achieve higher data rate with less transmission power. EF-IBC relies on the parasitic capacitive coupling between the transmitter and the receiver to close the signal circuit loop. With this parasitic coupling, EF-IBC links can be influenced by the environment. However until now, there is lack of systematic research on various environment coupling effects to the EF-IBC channel. In this paper, environment effects on the EF-IBC channel are comprehensively studied. The interference from the nearby EF-IBC channel is investigated for the first time to gain useful insights into the establishment of the BAN with EF-IBC. The FEM model is also established to explain the mechanism of the capacitive return path.

Equation Environment Coupling and Interference on the Electric-Field Intrabody Communication Channel

Described herein is a circuit and related method for improving the dynamic range and the linearity characteristic of a CMOS image sensor. In various embodiments of the CMOS image sensor, a current sampler, a comparator, and a 1-bit memory are incorporated in each pixel circuit. In the image sensor, pixels are arranged in columns and a column slice is used to read the digital and analog singles from each column. In addition, a calibration circuit is incorporated in the sensor circuit for providing calibration current, which is used to generate calibration parameter. The image sensor operates in three non-overlapping modes: the difference mode, the WDR mode, and the calibration mode. The image sensor is switched among the three modes by control signals, which are provided to the image sensor by various control circuits. The image sensor normally operates in the difference mode and switches to the WDR mode when the difference between consecutive frames is over a threshold. The calibration mode allows the image sensor generate calibration parameters which are used to improve the linearity of the sensor through a interpolation method.

Apparatus and method for improving dynamic range and linearity of CMOS image sensor

High-speed CMOS imaging sensors (CIS) normally have low sensitivity because of the large integration capacitance. They also have high noise because pixel circuits cannot implement correlated double sampling (CDS) to remove the pixel reset noise. For applications, such as micro-computed tomography (micro-CT), this is a major limitation. In this work, we developed a technique to achieve high sensitivity and low noise for high-speed CIS. To maximize the sensitivity, we designed a new capacitive transimpedance amplifier (CTIA) pixel with a tiny metal-oxide-metal capacitor. The pixel circuit also implements CDS. As a result, the temporal noise is greatly reduced, and the sensitivity improves dramatically. To compensate the mismatch of small integration capacitors across the pixel array, an on-chip calibration scheme with in-pixel circuits is developed. Fully differential column circuits are designed to suppress the power supply injection in the large array of high-speed column circuits. A successive-approximation analog-to-digital (SAR ADC) is designed to achieve 10-bit resolution and to fit in the 15-μm column pitch. For testing modes, column circuits are configured into a two-step ADC to provide 13-bit dynamic range. The 256 × 256 CIS design is fabricated in a 0.18-μm CMOS process. The imager samples up to 1500 fps. The pixel integration capacitor is 0.7 fF, which enables 68.5 V/lux · s sensitivity under the white illumination. The CIS temporal noise is 13.6e-. This sensitivity and noise performances are much better than previous high-speed CIS benchmark designs. Running at 1500 fps, the CIS can capture recognizable images with illumination down to 1 lux. The on-chip calibration suppresses the fixed-pattern noise lower than 0.52%. The prototype chip consumes 390 mW of power.

Jie Yuan

Papers

Electric-Field Intrabody Communication Channel Modeling With Finite-Element Method

Digitally Calibrated 768-kS/s 10-b Minimum-Size SAR ADC Array With Dithering

Equation Environment Coupling and Interference on the Electric-Field Intrabody Communication Channel

Apparatus and method for improving dynamic range and linearity of CMOS image sensor

A 1500 fps Highly Sensitive 256 $\,\times\,$ 256 CMOS Imaging Sensor With In-Pixel Calibration