A brain–computer interface (BCI) is a device that allows user to communicate with external devices through thought processes alone. novel signal acquisition tool for BCIs near-infrared spectroscopy (NIRS), an optical technique measure localized cortical brain activity. The benefits of using this non-invasive modality are safety, portability and accessibility. number commercial multi-channel NIRS system available; however we have developed straightforward custom-built investigate the...

A brain-computer interface (BCI) gives those suffering from neuromuscular impairments a means to interact and communicate with their surrounding environment. BCI translates physiological signals, typically electrical, detected the brain control an output device. significant problem current BCIs is lengthy training periods involved for proficient usage, which can often lead frustration anxiety on part of user. Ultimately this abandonment The primary reason that relatively indirect measures...

The combination of reducing birth rate and increasing life expectancy continues to drive the demographic shift toward an aging population. This, in turn, places ever-increasing burden on healthcare due prevalence patients with chronic illnesses income-generating population base needed sustain them. need urgently address this "time bomb" has accelerated growth ubiquitous, pervasive, distributed technologies. current move from hospital-centric in-home health assessment is aimed at alleviating...

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features interest reduce quality information available signal. If multichannel recordings are for a given signal source, then there currently considerable range methods suppress or some cases remove distorting effect such artifacts. There are, however, considerably...

Generative adversarial networks (GANs) have been extensively studied in the past few years. Arguably their most significant impact has area of computer vision where great advances made challenges such as plausible image generation, image-to-image translation, facial attribute manipulation and similar domains. Despite successes achieved to date, applying GANs real-world problems still poses challenges, three which we focus on here. These are: (1) generation high quality images, (2) diversity...

The market for wearable electronic devices is experiencing significant growth and increasing potential the future. Researchers worldwide are actively working to improve these devices, particularly in developing electronics with balanced functionality wearability commercialization. Electrospinning, a technology that creates nano/microfiber-based membranes high surface area, porosity, favorable mechanical properties human vitro vivo applications using broad range of materials, proving be...

We present a camera-based device capable of capturing two photoplethysmographic (PPG) signals at different wavelengths simultaneously, in remote noncontact manner. The system comprises complementary metal-oxide semiconductor camera and dual wavelength array light emitting diodes (760 880nm). By alternately illuminating region tissue with each light, detecting the backscattered photons rate 16frames∕wavelengths, multiplexed PPG wave forms are simultaneously captured. This process is basis...

This article brings together the various elements that constitute signal processing challenges presented by a hemodynamics-driven functional near-infrared spectroscopy (fNIRS) based brain-computer interface (BCI). We discuss use of optically derived measures cortical hemodynamics as control signals for next generation BCIs. To this end we present suitable introduction to underlying measurement principle, describe appropriate instrumentation and highlight how where performance improvements...

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods this process has become particularly acute as healthcare technology deployment undergoes transition current hospital-centric setting toward a wearable ubiquitous monitoring environment. Currently, determining relative efficacy performance multiple artifact techniques available on real world data can be problematic, due to incomplete information...

With the growing use of digital health technologies (DHT) in clinical trials, opportunity to technology promote greater patient centricity and inclusivity has emerged. Current provides various mechanisms for communication, eg, through voice or text, however, participant familiarity preference them is poorly understood. The purpose this study was understand participants' communication preferences, their comfort with messaging methods attitudes towards different technology-driven symptom...

The algorithm enhances Savitzky–Golay smoothing with maximum likelihood estimation, which outperforms traditional in terms of peak fidelity and SNR.

A Brain-computer Interface (BCI) can be used as a neurofeedback training tool to improve cognitive performance. BCIs aim the effectiveness and efficiency of conventional methods by focusing on self-regulation individualized neuromarkers rather than generic ones in graphically appealing environment. In this work, for first time, we have modified widely P300-based speller BCI it an engaging neurofeedack game enhance P300. According user's performance becomes more difficult adaptive manner,...

Although cloud computing is one of the promising technologies for online business services, how to schedule real-time jobs with high quality service (QoS) still challenging current techniques. With advancing machine learning, deep reinforcement learning (DRL) has demonstrated its outstanding capability in dispatching time-sensitive tasks. However, reinforced rewards DRL are typically unavailable until completion scheduling all jobs. Considering fact that trajectory always long, DRL-based...

Abstract Clinical studies from WHO have demonstrated that only 50–70% of patients adhere properly to prescribed drug therapy. Such adherence failure can impact therapeutic efficacy for the in question and compromises data quality around population-level indications targeted. In this study, we applied various ensemble learning deep models predict medication among patients. Our contribution endeavour involves targeting problem prediction a particularly challenging class who self-administer...

Generative adversarial networks (GANs) studies have grown exponentially in the past few years. Their impact has been seen mainly computer vision field with realistic image and video manipulation, especially generation, making significant advancements. While these advances garnered much attention, GAN applications diversified across disciplines such as time series sequence generation. As a relatively new niche for GANs, fieldwork is ongoing to develop high quality, diverse private data. In...

This paper is the first part of a two-part that documents detailed survey research carried out on consistency and latency in distributed interactive applications (DIAs) recent decades. Part I reviews terminology associated with DIAs offers definitions for latency. Related issues such as jitter fidelity are also discussed. Furthermore, various maintenance mechanisms researchers have used to improve reduce effects considered. These grouped into one three categories, namely time management,...

Brain-Computer Interfaces (BCI) can potentially be used to aid in the recovery of lost motor control a limb following stroke. BCIs are typically by subjects with no damage brain therefore relatively little is known about technical requirements for design rehabilitative BCI 32-channel electroencephalogram (EEG) was recorded during finger-tapping task from 10 healthy one session and 5 stroke patients two sessions approximately 6 months apart. An off-line based on Filter Bank Common Spatial...