Consumer electronics have started to support 8K/4K/UHD/SUHD videos in order to improve the perceived QoE. It is beneficial to assess the consumer’s perceived quality degradation at the output prior to transmitting the video in an error prone channel, to include concealment support and error resilient features to minimize these artifacts. While existing error resilient schemes have attempted to include

Image distortion during multiple-exposure capture is a common scenario, and most of the existing legacy image content is in the low dynamic range (LDR). For both of these problems, pseudo multiple exposure image generation from a single image is a possible solution. Hence, in this article, we propose a novel method for high dynamic range (HDR)-like image generation by fusing pseudo-multi-exposure images

Real-time computer vision tasks are emerging in consumer electronics with lightweight computing performance, which are an exquisite design art to balance the computational efficiency and accuracy. In this paper, we present the embedded background subtraction (EBGS) – an optimization algorithm for the entire process to increase computational efficiency and detection accuracy simultaneously. EBGS exploits

More and more consumer electronics, such as personal computers and smart phones, adopt NAND flash memory as their data storage devices. However, garbage collection (GC) operations in flash memory may degrade both the performance and lifetime for consumer electronics due to the extra page reads and page writes caused by GC. Greedy algorithm, which selects the block with the least valid pages for GC

NAND flash memory is being widely used as data storage in consumer electronics devices such as tablet computers and smartphones. However, due to the inherent nature of NAND flash memory where in-place update is not supported, NAND flash-based SSDs (Solid-State Drives) suffer from severe performance degradation as they need to move valid data during garbage collection (GC). Recently, multi-streamed

We investigate a new approach for designing spectral shaping block codes with a target spectrum, $H_{t}(f)$ , that has been specified at a plurality of frequencies. We analyze the probability density function of the spectral power density function of uncoded $n$ -symbol bipolar codewords. We present estimates of the redundancy and the spectrum of spectral shaping codes with specified target spectral

Epileptic seizures present a serious danger to the lives of their victims, rendering them unconscious, lacking control, and may even result in death only a few seconds after onset. This gives rise to a crucial need for an effective seizure detection method that is fast, accurate, and has the potential for mass market adoption. Kriging methods have a good reputation for high accuracy in spatial prediction

Haptic interactions in consumer devices have become more critical with immersive streaming content by including high-resolution video and sound as well as tactile information. Mobile devices such as tablets and smartphones are significantly limited for creating effective haptic illusions as they are too small in size to accommodate complex actuators and are without mechanical support. Recent studies

Mean squared error (MSE) is adopted as the distortion metric for the rate-distortion optimization (RDO) and rate control (RC) in most of the existing video coding standards, e.g., H.265/High-Efficiency Video Coding (HEVC) and H.264/Advanced Video Coding (AVC), because the pixel-wise MSE can represent the image fidelity efficiently. As videos are usually used for visual enjoyment, recently, researchers

Nowadays, eHealth is one of the most important topics in the next generation of consumer electronics (CE) and consumer technology (CT). Some disruptive technologies are allowing the development of these new devices helping their deployment to the mass market. The expansion of new applications in the field of eHealth has created the new concept of eHealth-IoT where several low cost devices are interconnected

In this work, our objective is to design, develop, and evaluate the effectiveness of a stress detection model for older adults using a system of wrist-worn sensors. Our system uses four signals, EDA, BVP, IBI, and ST from EDA, PPG, and ST sensors, embedded in a smart wristband, to classify between stressed and not-stressed state. The stress reference is obtained from salivary cortisol measurement,

NAND flash-based solid-state drives (SSDs) have been widely used in consumer electronic products such as smartphones, digital video recorders, and laptops. The flash translation layer (FTL) is crucial to the performance of SSDs. In this article, an on-demand FTL, briefly as HDFTL, is proposed for hybrid SSDs built with SLC+MLC flash memory. HDFTL divides the SLC into data blocks and translation blocks

Rapid advancement in sensor technology through miniaturization of electronic components has enabled the consumer electronic (CE) research community including the manufacturers to embed various utility sensors into handheld devices. In addition to traditional sensors such as Inertial Measurement Unit (IMU), camera, fingerprint or proximity, futuristic sensors such as Electroencephalogram (EEG) or Electromyography

Artificial Intelligence (AI) based Speech Emotion Recognition (SER) has been widely used in the consumer field for control of smart home personal assistants, with many such devices on the market. However, with the increase in computational power, connectivity, and the need to enable people to live in the home for longer though the use of technology, then smart home assistants that could detect human

Recent advances of energy management system in a smart home can lead to load monitoring of electrical appliances for energy saving and reduction of electricity bill. Thus, smart metering technology is getting widely implemented in several electricity distribution networks. Most of the existing research are concentrated towards individual power consumption of different household loads using some machine

We present a conceptually simple framework for 6DoF object pose estimation, especially for autonomous driving scenarios. Our approach can efficiently detect the traffic participants from a monocular RGB image while simultaneously regressing their 3D translation and rotation vectors. The proposed method 6D-VNet, extends the Mask R-CNN by adding customised heads for predicting vehicle’s finer class,

Detecting stress in computer users, while technically challenging, is of the utmost importance in the workplace, especially now that remote working scenarios are becoming ubiquitous. In this context, cost-effective, subject-independent systems are needed that can be embedded in consumer devices and classify users’ stress in a reliable and unobtrusive fashion. Leveraging keyboard and mouse dynamics

Considering today’s lifestyle, people just sleep forgetting the benefits sleep provides to the human body. Smart-Yoga Pillow (SaYoPillow) is proposed to help in understanding the relationship between stress and sleep and to fully materialize the idea of “Smart-Sleeping” by proposing an edge device. An edge processor with a model analyzing the physiological changes that occur during sleep along with

Because of the excellent performance and decreasing price of NAND flash, NAND flash-based solid-state drive (SSD) has been widely used as a storage system in consumer electronics. Moreover, modern consumer SSDs usually adopt a multichannel parallel structure. Thus, how to fully utilize the internal parallelism through IO scheduling is a key problem. The existing IO schedulers fail to solve the following:

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

This article proposes a wearable assistive system based on artificial intelligence (AI) edge computing techniques to help visually impaired consumers safely use marked crosswalks, or zebra crossings. The proposed wearable assistive system consists of a pair of smart sunglasses, a waist-mounted intelligent device, and an intelligent walking cane (stick). A deep learning technique is adopted for zebra

Context-aware computing, which gathers information about the environment at a given time and adapts its behavior accordingly, can be effectively applied to a monitoring system that automatically detects and copes with emergency situations. In this paper, we propose an indoor emergency awareness alarm system using a deep neural network on a mobile device for at-risk people, such as the elderly and children

Most modern operating systems have adopted the one-to-one thread model to support fast execution of threads in both multi-core and single-core systems. This thread model, which maps the kernel-space and user-space threads in a one-to-one manner, supports quick thread creation and termination in high-performance server environments. However, the performance of time-critical threads is degraded when

Wearable consumer electronics such as smartwatch and smartglasses generally use peer-to-peer (P2P) communications to connect to their companion devices such as smartphones. The recent wearable consumer electronics are equipped with multiple heterogeneous network interfaces, which have different power consumption and transfer bandwidths. To optimize energy efficiency, a network interface must be selected

Falls among the elderly living on their own have been regarded as a major public health worry that can even lead to death. Fall detection system (FDS) that alerts caregivers or family members can potentially save lives of the elderly. However, conventional FDS involves wearable sensors and specialized hardware installations. This article presents a passive device-free FDS based on commodity WiFi framework

Commercially available wearable systems are increasingly helping people to continuously monitor their health status. To enable continuous monitoring for the battery operated lightweight wearable systems, power consumption is the most critical factor. The battery life of such systems has to be decent to make any acceptable product. In these systems, the power consumption is dominated by the transmitter

People around the globe rely on their blood samples for their glucose level measurement. There is a demand for non-invasive, precise and cost-effective solutions to monitor blood glucose level and control of diabetes. Serum glucose is an accurate blood glucose measurement method in comparison to capillary glucose measurement. Presently, the serum glucose is measured through laboratory setup with an

Infant monitoring is very important in daily life, since infants lack the ability to verbalize and communicate with their caregivers. However, a full-time monitoring provided by caregivers or practitioners is very expensive and labor intensive. To solve the practical difficulties for particular nighttime monitoring and further reduce the labor cost, in this article, we propose a novel 24-hour infant

The motion activities performed by a mobile or wearable device user are characteristic of the user and the accuracy of detection of motion activity context can be improved by incorporating personalized samples of motion activity. But obtaining personalized samples of motion activity from device user is not practically feasible. In this article, a semi-supervised method is presented for improving the

With the advantages of low power consumption, flexibility, and high readability against bright ambiance, electrophoretic displays (EPDs) have wide application prospects in the fields of education, smart supermarkets, Internet of Things, smart homes, wearable devices, etc. EPDs suffer from a severe history dependence during grayscale switching, which results in annoying ghost images. However, currently

We present a straightforward, non-intrusive adaptive bit rate streaming segment quality selection policy which aims at extending battery lifetime during playback while limiting the impact on the user’s quality of experience, thus benefiting consumers of video streaming services. This policy relies on the relationship between the available channel bandwidth and the bit rate of the representations in

With the wide use of personal consumer electronics devices such as smartphones, people store sensitive and confidential information more on their devices. Active authentication (AA) systems continuously authenticate users to reduce possible attacks after a successful login on the device. In this article, we propose match-on-card (MOC) approach for a secure active authentication scheme using touchscreen

Hardware accelerators are widely used as computationally-intensive cores in consumer electronics (CE) applications. However security and speed of such hardware accelerators, that are responsible for computing data-intensive tasks, play an important role in improving consumer experience in terms of safety and performance. This article presents novel low power multi-modal hardware accelerator architectures

Universal Serial Bus (USB) is widely used, for example to facilitate hot-swapping and plug-and-play. However, USB ports can be exploited by an adversary to extract private or personal data from the connected devices. Hence, a number of organizations and workplaces have prohibited their employees from using USB devices, and there have been efforts to design secure USB storage device schemes to more

Consumer devices continue to expand their capabilities by connecting to digital services and other devices to form information-sharing ecosystems. This is complex and requires meeting connection requirements and minimal processing capabilities to ensure communication. The emergence of new services, and the evolution of current technologies, constantly redefine the rules of the game by opening up new

Low power hardware acceleration cores for integration into real-time High Efficiency Video Coding (HEVC) codec for smartphones, tablets, camcorders, and televisions are in great demand. This need motivates one for an efficient realization of Discrete Cosine Transform (DCT) and Inverse-DCT (IDCT) for HEVC. This paper presents an algorithm to calculate the required minimum number of low-frequency DCT-output/IDCT-input

Consumer Electronics (CE) devices have started to support 360° videos in order to improve the perceived video quality by consumers. Higher compression in 360° videos not only lead to improved consumer perception, but also efficient energy and storage usage in CE devices. Consequently, efficient compression of such video content is becoming a critical design consideration of CE devices. To this end

Recently, the Internet of Things (IoT) topology has used to collect physical, physiological, vital signs of patients in consumer-centric e-health or consumer’ wellness care services. In such healthcare systems, varieties of medical sensors are attached to the patients to collect vital signs from those who are under observation. The data gathering process in IoT-enabled Wireless Sensor Network (WSN)

Home energy management requires accurate information about the appliances’ consumption pattern. This information can help consumers save energy, control their usage by shifting their usage to off-peak hours and reduce their electricity costs. Non-intrusive load monitoring (NILM) in which the power consumption profile of appliances are extracted from the aggregated signal of a household, provides this

NAND flash memory has been widely used as data storage devices in consumer electronics, such as tablet computers and smart phones. Logical-to-physical address translation is important for improving the performance of NAND flash-based SSDs. Even though keeping the mapping table in a DRAM can boost the address translation, it is already infeasible to do this as the capacity of SSDs keeps increasing and

Intellectual property (IP) core of digital signal processing (DSP) kernels act as hardware accelerators in consumer electronics (CE) systems. However due to rising threats of cloning and counterfeiting to an IP core, security remains an important subject of research for these hardware accelerators. This paper presents a novel key-driven hash-chaining based hardware steganography for securing such IP

As one of the main threats to people’s health, especially for the elderly, falls have caused a large number of accidents. Detecting falls in time can minimize the severity of the injury and save lives. Therefore, designing fall detection algorithms to assist people’s daily life has been a hot research topic. In the last decade, different fall detection approaches based on wearable sensors have been

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Presents a listing of the CES society Board of Governors.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

In this article, a novel and an efficient methodology is presented for real-time monitoring of ECG signals. The method involves fast Fourier transform (FFT) based discrete wavelet transform (DWT) for extracting the features from the heartbeats which involves less computational complexity in terms of additions and multiplications operations for higher order filter lengths. These features extracted are

Not knowing when to stop eating or how much food is too much can lead to many health issues. In iLog, we propose a system which can not only monitor but also create awareness for the user of how much food is too much. iLog provides information on the emotional state of a person along with the classification of eating behaviors to Normal-Eating or Stress-Eating. Chronic stress, uncontrolled or unmonitored

Consumer electronics equipped with a microphone array, such as car navigation devices and headsets commonly implement speech enhancement techniques based on the gradient method to cope with additive noise. However, while these techniques had been originally developed for voice communication and can maximize the signal-to-distortion ratio (SDR), they cannot always maximize automatic speech recognition

As the popularity of Smart Televisions (TVs) and interactive Smart TV applications (apps) has recently grown, the usability of these apps has become an important quality characteristic. Previous studies examined Smart TV apps from a usability perspective. However, these methods are mainly manual, and the potential of automated model-based testing methods for usability testing purposes has not yet been

Video Surveillance is an active area of research and provides promising security measures for consumer applications. To ease consumer surveillance investigations, Video Synopsis (VS) serves as a powerful tool to assess hours of video in a shorter retro of time by projecting multiple objects concurrently. The optimization module in VS framework is considered to be a key module, yet to date, only traditional

Tone mapping operators (TMOs) reproduce the high dynamic range (HDR) images on low dynamic range (LDR) consumer electronics devices such as monitors or printers. To accurately measure and compare the performance of different TMOs, this article proposes a tone-mapped images (TMIs) luminance partition model and corresponding quality measure. First, each tone-mapped (TM) image is segmented into highlight

Security of Digital Signal Processing (DSP) based Intellectual Property (IP) core is very important for the overall security and reliability of Consumer Electronics (CE) systems. These DSP based IP cores are highly vulnerable to threats such as reverse engineering (RE) leading to Trojan insertion, counterfeiting and cloning. Thus developing robust defense mechanisms is highly significant for these

Nowadays, the advancement of non-intrusive load monitoring (NILM) is hastened by the everincreasing requirements for smart power utilization and demand side management. Thus, an intelligent event-driven non-intrusive load monitoring method based on convolutional neural network (CNN) is proposed in this article to profile residential consumer behavior, which focused on limited applicability and low

As several home appliances, such as air conditioners, heaters, and refrigerators, were connecting to the Internet, they became targets of cyberattacks, which cause serious problems such as compromising safety and even harming users. We have proposed a method to detect such attacks based on user behavior. This method models user behavior as sequences of user events including operation of home IoT (Internet

Recently, consumer electronics devices have started adopting NAND flash memories as their storage units. NAND flash memories are suitable as portable consumer device storages, as they have several advantages such as non-volatility, high density and low power consumption. However, flash memories are difficult to be used directly as storages in consumer devices because of a limited lifespan, which is

Presents the table of contents for this issue of the publication.