Contextual Haptics for Wearable Devices

Haptic feedback is an important feature for wearable devices such as watches, fitness bands, etc. Current techniques to provide hardware feedback either cannot generate specially customized haptic feedback, or are limited to predefined haptic effects, and are limited by the battery and peak power draw available on a wearable device. This document describes context-aware haptics that take into account the user state while using the wearable device. With permission from the user, the user state or activity, e.g., sitting, walking, running, etc. is detected by analyzing sensor readings from inertial measurement unit (IMU) sensor(s) that are included in the wearable device. Based on the user state, dynamic haptics are provided that adapt to the determined user state/ context

Fully Quantized Always-on Face Detector Considering Mobile Image Sensors

Despite significant research on lightweight deep neural networks (DNNs) designed for edge devices, the current face detectors do not fully meet the requirements for "intelligent" CMOS image sensors (iCISs) integrated with embedded DNNs. These sensors are essential in various practical applications, such as energy-efficient mobile phones and surveillance systems with always-on capabilities. One noteworthy limitation is the absence of suitable face detectors for the always-on scenario, a crucial aspect of image sensor-level applications. These detectors must operate directly with sensor RAW data before the image signal processor (ISP) takes over. This gap poses a significant challenge in achieving optimal performance in such scenarios. Further research and development are necessary to bridge this gap and fully leverage the potential of iCIS applications. In this study, we aim to bridge the gap by exploring extremely low-bit lightweight face detectors, focusing on the always-on face detection scenario for mobile image sensor applications. To achieve this, our proposed model utilizes sensor-aware synthetic RAW inputs, simulating always-on face detection processed "before" the ISP chain. Our approach employs ternary (-1, 0, 1) weights for potential implementations in image sensors, resulting in a relatively simple network architecture with shallow layers and extremely low-bitwidth. Our method demonstrates reasonable face detection performance and excellent efficiency in simulation studies, offering promising possibilities for practical always-on face detectors in real-world applications.Comment: Accepted to ICCV 2023 Workshop on Low-Bit Quantized Neural Networks (LBQNN), Ora

Efficient Unified Demosaicing for Bayer and Non-Bayer Patterned Image Sensors

As the physical size of recent CMOS image sensors (CIS) gets smaller, the latest mobile cameras are adopting unique non-Bayer color filter array (CFA) patterns (e.g., Quad, Nona, QxQ), which consist of homogeneous color units with adjacent pixels. These non-Bayer sensors are superior to conventional Bayer CFA thanks to their changeable pixel-bin sizes for different light conditions but may introduce visual artifacts during demosaicing due to their inherent pixel pattern structures and sensor hardware characteristics. Previous demosaicing methods have primarily focused on Bayer CFA, necessitating distinct reconstruction methods for non-Bayer patterned CIS with various CFA modes under different lighting conditions. In this work, we propose an efficient unified demosaicing method that can be applied to both conventional Bayer RAW and various non-Bayer CFAs' RAW data in different operation modes. Our Knowledge Learning-based demosaicing model for Adaptive Patterns, namely KLAP, utilizes CFA-adaptive filters for only 1% key filters in the network for each CFA, but still manages to effectively demosaic all the CFAs, yielding comparable performance to the large-scale models. Furthermore, by employing meta-learning during inference (KLAP-M), our model is able to eliminate unknown sensor-generic artifacts in real RAW data, effectively bridging the gap between synthetic images and real sensor RAW. Our KLAP and KLAP-M methods achieved state-of-the-art demosaicing performance in both synthetic and real RAW data of Bayer and non-Bayer CFAs

18.4 Improving CDR Performance via Estimation

An implementation of the semi-digital dual-loop first-order CDR of [1] is shown in Fig. 18.4.1. The CDR (peripheral) loop consists of a bang-bang phase detector, gain (pre_filt), binary accumulator (P_acc), and phase DAC. Pre_filt is an accumulator that generates a positive or negative carry when the accumulated error reaches a certain programmable threshold (±1, 2, 4, or 8) and acts as a linear attenuator (1, 1/2, 1/4, or 1/8). The truncation occurring in pre_filt also helps to suppress limit cycles caused by loop delay [2]. The core loop is both a frequency synthesizer and multiphase generator. The high-frequency jitter tolerance (i.e. timing margin) of this CDR improves as its bandwidth (loop gain) is reduced since more ISI jitter is removed (Fig. 18.4.5(a)). However, this increases lock time and decreases frequency operation range. Building an estimator that adjusts its loop gain according to operating conditions can remove this tradeoff. Since the first-orde

Selective Surface Treatment Using Atmospheric Ar Plasma Jet for Aluminum‐doped Zinc Oxide Based Transparent and Flexible Electronics

Abstract Transparent and flexible electronics are emerging technologies with the potential to enable new applications. However, to ensure high‐performance transparent electronics, post‐processing such as thermal annealing and vacuum plasma treatment is necessary, which are difficult to apply to polymer‐based flexible substrates. This study analyzed the feasibility of applying selective Ar plasma jet treatment at atmospheric pressure to transparent flexible electronics. When atmospheric Ar plasma treatment is applied to transparent flexible aluminum‐doped zinc oxide (AZO), it showed a maximum 83.1% improvement in sheet resistance while maintaining a high transmittance performance, of over 70%. To verify the mechanism behind the surface treatment effect using atmospheric Ar plasma, comprehensive analyses are performed using atomic force microscopy, X‐ray diffraction, and X‐ray photoelectron spectroscopy, which confirmed that the effect is due to oxygen vacancy formation caused by ion bombardment and thermal diffusion. The application of atmospheric plasma treatment to a patterned transparent flexible AZO device resulted in a reduction in contact resistance, and it is confirmed that the performance improvement effects can be retained for >500 h by applying additional passivation

Gradual electrical‐double‐layer modulation in ion‐polymer networks for flexible pressure sensors with wide dynamic range

To realize flexible pressure sensors with high sensitivity, surface-textured soft films have often been adopted and the contact area can vary significantly depending on the applied pressure. However, the contact area modulation realized in such a way is subject to a limited dynamic range, and its infinitesimal zero-pressure contact area raises concerns regarding durability. Herein, a flexible pressure sensor made of a texturing-free piezocapacitive layer based on ion-polymer networks is proposed. In this scheme, ion infiltration leads to electrical-double-layer modulation that gradually varies over a wide range of applied pressures. The proposed flexible pressure sensors with the optimal ion concentration are shown to exhibit both excellent mechanical durability and linear responses with high sensitivity over a wide pressure range up to 1 MPa. With the simple fabrication route, high performance, and reliability, the proposed approach may open up a new avenue for skin-like pressure sensors ideal for many emerging applications

A CMOS Image Sensor Based Refractometer without Spectrometry

The refractive index (RI), an important optical property of a material, is measured by commercial refractometers in the food, agricultural, chemical, and manufacturing industries. Most of these refractometers must be equipped with a prism for light dispersion, which drastically limits the design and size of the refractometer. Recently, there have been several reports on the development of a surface plasmon resonance (SPR)-based RI detector, which is characterized by its high sensitivity and simplicity. However, regardless of the prism, an expensive spectrometer is required to analyze the resonance wavelength or angle of incidence. This paper proposes a method that eliminates the need for the prism and other conventional spectrometer components. For this purpose, total internal reflection SPR technology was used on an Ag thin film, and RI analysis was combined with a lens-free CMOS image sensor or a smartphone camera. A finite-difference time-domain (FDTD) numerical simulation was performed to evaluate the relationship between the output power intensity and Ag film thickness for different RIs at three wavelengths of commercial light-emitting diodes (LEDs). The maximum sensitivity of −824.54 RIU−1 was achieved with AG20 at an incident wavelength of 559 nm. Due to its simple design and cost effectiveness, this prism-less, SPR-based refractometer combined with a lens-free CMOS image sensor or a smartphone could be a superior candidate for a point-of-care device that can determine the RIs of various analytes in the field of biological or chemical sensing

PyNET-QxQ: A Distilled PyNET for QxQ Bayer Pattern Demosaicing in CMOS Image Sensor

The deep learning-based ISP models for mobile cameras produce high-quality images comparable to the professional DSLR camera. However, many of them are computationally expensive, which may not be appropriate for mobile environments. Also, the recent mobile cameras adopt non-Bayer CFAs (e.g., Quad Bayer, Nona Bayer, and QxQ Bayer) to improve image quality; however, most deep learning-based ISP models mainly focus on standard Bayer CFA. In this work, we propose PyNET-QxQ based on PyNET, a light-weighted ISP explicitly designed for the QxQ CFA pattern. The number of parameters of PyNET-QxQ is less than 2.5% of PyNET. We also introduce a novel knowledge distillation technique, progressive distillation, to train the compressed network effectively. Finally, experiments with QxQ images (obtained by an actual QxQ camera sensor, under development) demonstrate the outstanding performance of PyNET-QxQ despite significant parameter reductions.Comment: in revie

Spontaneous Generation of Molecular Thin Hydrophobic Skin Layer on Sub-20 nm, High-k Polymer Dielectric for Extremely Stable Organic Thin-Film Transistor (OTFT) Operation

Polymer dielectric materials with hydroxyl functionalities such as poly(4-vinylphenol) and poly(vinyl alcohol) been utilized widely in organic thin-film transistors (OTFTs) because of their excellent insulating performance gained by hydroxyl-mediated cross-linking. However, the polar hydroxyl functionality also deleteriously affects the performance of OTFTs and significantly impairs the device stability. In this study, a sub-20 nm, high-k copolymer dielectric with hydroxyl functionality, poly(2-hydroxyethyl acrylate-co-di(ethylene glycol) divinyl ether), was synthesized in the vapor phase via initiated chemical vapor deposition. The inherently dry environment offered by the vapor phase polymer synthesis prompted the snuggling of polar hydroxyl functionalities into the bulk polymer film to form a molecular thin hydrophobic skin layer at its surface, verified by near-edge X-ray absorption fine structure analysis. The chemical composition of the copolymer dielectric was optimized systematically to achieve high dielectric constant (k approximate to 6.2) as well as extremely low leakage current densities (less than 3 X 10(-8) A/cm(2) in the range of +/- 2 MV/cm) even with sub-20 nm thickness, leading to one of the highest capacitance (higher than 300 nF/cm(2)) achieved by a single polymer dielectric to date. Exploiting the structural advantage of the cross-linked high-k polymer dielectric, high-performance OTFTs were obtained. Notably, the spontaneously formed molecular thin, hydrophobic skin layer in the copolymer film substantially suppressed the hysteresis in the transistor operation. The trap analysis also suggested the formation of bulk trap with a high energy barrier and sufficiently low trap densities at the semiconductor/dielectric interface, owing to the surface skin layer. Furthermore, the OTFTs with the OH-containing copolymer dielectric showed an unprecedentedly excellent operational stability. No apparent OTFT degradation was observed up to 50 000 s of high constant voltage stress (corresponding to the applied electric field of 1.4 MV/cm) because of the markedly suppressed interfacial trap density by the hydrophobic skin layer, together with the current compensation by the bulk hydroxyl functionalities. We believe that the surface modification-free, one-step polymer dielectric synthetic strategy will provide a new insight into the design of polymer dielectric materials for high-performance, low-power soft electronic devices with high operational stability.11Nsciescopu