Portable Technology Research Articles

Building Daily Living Skills Through Portable Video Modeling.

This study used video modeling via portable technology to improve daily living skills for a student with an intellectual disability in a university campus-based transition program. Results showed increased independence across four daily living skills. Implications for future practice are discussed.

Enabling Gait Analysis in the Telemedicine Practice through Portable and Accurate 3D Human Pose Estimation

Human pose estimation (HPE) through deep learning-based software applications is a trend topic for markerless motion analysis. Thanks to the accuracy of the state-of-the-art technology, HPE could enable gait analysis in the telemedicine practice. On the other hand, delivering such a service at a distance requires the system to satisfy multiple and different constraints like accuracy, portability, real-time, and privacy compliance at the same time. Existing solutions either guarantee accuracy and real-time (e.g., the widespread OpenPose software on well-equipped computing platforms) or portability and data privacy (e.g., light convolutional neural networks on mobile phones). We propose a portable and low-cost platform that implements real-time and accurate 3D HPE through an embedded software on a low-power off-the-shelf computing device that guarantees privacy by default and by design. We present an extended evaluation of both accuracy and performance of the proposed solution conducted with a marker-based motion capture system (i.e., Vicon) as ground truth. The results show that the platform achieves real-time performance and high-accuracy with a deviation below the error tolerance when compared to the marker-based motion capture system (e.g., less than an error of 5∘ on the estimated knee flexion difference on the entire gait cycle and correlation 0.91<ρ<0.99). We provide a proof-of-concept study, showing that such portable technology, considering the limited discrepancies with respect to the marker-based motion capture system and its working tolerance, could be used for gait analysis at a distance without leading to different clinical interpretation.

Robust Assessment of EEG Connectivity Patterns in Mild Cognitive Impairment and Alzheimer's Disease.

The prevalence of dementia, including Alzheimer's disease (AD), is on the rise globally with screening and intervention of particular importance and benefit to those with limited access to healthcare. Electroencephalogram (EEG) is an inexpensive, scalable, and portable brain imaging technology that could deliver AD screening to those without local tertiary healthcare infrastructure. We study EEG recordings of subjects with sporadic mild cognitive impairment (MCI) and prodromal familial, early-onset, AD for the same working memory tasks using high- and low-density EEG, respectively. A challenge in detecting electrophysiological changes from EEG recordings is that noise and volume conduction effects are common and disruptive. It is known that the imaginary part of coherency (iCOH) can generate functional connectivity networks that mitigate against volume conduction, while also erasing true instantaneous activity (zero or π-phase). We aim to expose topological differences in these iCOH connectivity networks using a global network measure, eigenvector alignment (EA), shown to be robust to network alterations that emulate the erasure of connectivities by iCOH. Alignments assessed by EA capture the relationship between a pair of EEG channels from the similarity of their connectivity patterns. Significant alignments-from comparison with random null models-are seen to be consistent across frequency ranges (delta, theta, alpha, and beta) for the working memory tasks, where consistency of iCOH connectivities is also noted. For high-density EEG recordings, stark differences in the control and sporadic MCI results are observed with the control group demonstrating far more consistent alignments. Differences between the control and pre-dementia groupings are detected for significant correlation and iCOH connectivities, but only EA suggests a notable difference in network topology when comparing between subjects with sporadic MCI and prodromal familial AD. The consistency of alignments, across frequency ranges, provides a measure of confidence in EA's detection of topological structure, an important aspect that marks this approach as a promising direction for developing a reliable test for early onset AD.

Zero-Dimensional Zn-Based Halides with Ultra-Long Room-Temperature Phosphorescence for Time-Resolved Anti-Counterfeiting.

Though fluorescence-tag-based anti-counterfeiting technology has distinguished itself with cost-effective features and huge information loading capacity, the clonable decryption process of spatial-resolved anti-counterfeiting cannot meet the requirements for high-security-level anti-counterfeiting. Herein, we demonstrate a spatial-time-dual-resolved anti-counterfeiting system based on new organic-inorganic hybrid halides BAPPZn2 (Cly Br1-y )8 (BAPP=1,4-bis(3-ammoniopropyl)piperazinium, y=0-1) with ultra-long room-temperature phosphorescence (RTP). Remarkably, the afterglow lifetime can be facilely tuned by regulating the halide-induced heavy-atom effect and can be identified by the naked eyes or with the help of a simple machine vision system. Therefore, the short-lived unicolor fluorescence and lasting-time-tunable RTP provide the prerequisites for unicolor-time-resolved anti-counterfeiting, which lowers the decryption-device requirements and further provides the design strategy of advanced portable anti-counterfeiting technology.

(Invited) Nanomaterial-Based Electrochemical Sensors for the Detection of Pharmaceutical Compounds

The surging growth of the pharmaceutical industry is a result of the rapidly increasing human population, which has inevitably led to new biomedical and environmental issues. Aside from the quality control of pharmaceutical production and drug delivery, there is an urgent need for precise, sensitive, portable, and cost-effective technologies to track patient overdosing and to monitor ambient water sources and wastewater for pharmaceutical pollutants. The development of advanced nanomaterial-based electrochemical sensors for the detection of pharmaceutical compounds has garnered immense attention due to their advantages, such as high sensitivity and selectivity, real-time monitoring, and ease of use. Recently, my research team has designed and fabricated a variety of functional nanomaterials and nanocomposites. In this talk, the synthesis of nanoporous gold and the development of graphene-based nanomaterials as well as their promising applications in electrochemical sensing of different pharmaceutical compounds (e.g., acetaminophen, naproxen and isoniazid) are presented. The design rationale and the performance of the proposed electrochemical sensors are highlighted.

(Invited) Flock -Flare Clock: Passive Sweat-Based Eczematous Flare Detection System

Point-of-need platforms that work with sweat offer the advantage of self-monitoring for chronic diseases. Sweat based platform offer benefits in areas like comfort, functionality, and provide real time analysis of biomarker fluctuations in the body. For chronic conditions like Atopic Dermatitis, evaluating the severity of the disease on a case-by-case basis can help with providing an effective treatment plan. Sweat contains biomarkers like interleukin-31 and cortisol, which are biomarkers for atopic dermatitis (AD) and circadian disruption that is associated with the itching symptom of the disease. This portable detection technology is aimed at bridging the gap between assessing the severity of the disease and providing a patient-centric treatment plan. The research is envisioned to work as a wearable that can predict flares based on the biomarker levels and help with management of severe cases of AD, especially in pediatric populations.FLOCK (flare clock) system is a novel platform that comprises of a nanoporous membrane based multilayer stack that works with passively secreted sweat. It is designed to capture eczema severity and circadian disruption caused due to its symptoms. This is aimed to be a wearable designed for efficient management of the flaring associated with Atopic Dermatitis (AD). The work presents the development of an eczematous flare tracker that detects IL-31 and cortisol levels to create an AD management platform. The platform uses electrochemical detection for tracking these biomarkers in sweat. It is sensitive to IL-31 levels in various flare-based formulations tested through simulated sweating with a detection limit of 50 pg/mL and range 50-1000 pg/mL. On-body study highlights the ability of the wearable platform to track the rise and fall in the biomarkers’ levels. These levels are well correlated to salivary levels and commercial gold standard techniques (r>0.8, R2 >0.95).

Sowing kernels for food safety: Importance of rapid on‐site detction of pesticide residues in agricultural foods

AbstractSustainable cultivation and safe agricultural production are needed to ensure the safety of all living organisms and ecosystems. Most agricultural foods currently contain unacceptable levels of pesticide residues. In an attempt to ensure pest control and high crop yields, farmers spray a large number of pesticides in quantities that exceed the safety limits for agricultural crops. Pesticide residues are highly toxic to humans, causing severe and even deadly diseases. Traditional analytical strategies for laboratory pesticide detection are often limited because they are time‐consuming and require trained personnel, which makes them very costly. Hence, accurate, rapid, and on‐site analysis of pesticides is drawing increasing attention for food safety reasons. Therefore, on‐site or point‐of‐care (POC) detection of pesticide residues has become an approach of paramount importance. Recently, various portable detection technologies, such as colorimetric, fluorescence, electrochemical, surface plasmon resonance, chemiluminescence, phosphorescence, microfluidic, and surface‐enhanced Raman scattering techniques, have been designed for on‐site monitoring of pesticide residues in vegetables and fruits. These devices have demonstrated great power of detection in preclinical agricultural settings. This review highlights the emerging insights and novel advances in portable devices, POC technologies, and on‐site sensing approaches for the detection of pesticide residues in agricultural foods. However, greater rigor in the design of portable pesticide‐detection devices is essential. The increasing demand for rapid detection of hazardous pesticide components has prompted a timely opportunity to summarize recent developments and progress in portable devices and on‐site sensing strategies to evaluate food safety.

High-performance, additively-manufactured atomic spectroscopy apparatus for portable quantum technologies.

We demonstrate a miniaturised and highly robust system for performing Doppler-free spectroscopy on thermal atomic vapour for three frequencies as required for cold atom-based quantum technologies. The application of additive manufacturing techniques, together with efficient use of optical components, produce a compact, stable optical system, with a volume of 0.089 L and a weight of 120 g. The device occupies less than a tenth of the volume of, and is considerably lower cost than, conventional spectroscopic systems, but also offers excellent stability against environmental disturbances. We characterise the response of the system to changes in environmental temperature between 7 and 35 ∘C and exposure to vibrations between 0 - 2000 Hz, finding that the system can reliably perform spectroscopic measurements despite substantial vibrational noise and temperature changes. Our results show that 3D-printed optical systems are an excellent solution for portable quantum technologies.

Microteaching: Theoretical Origins and Practice

Through a selective review of the literature, this article examines the theoretical origins and early use of microteaching and charts its development over the last nearly six decades in the field of teacher education. From its beginning in the 1960’s as a method for pre-service teacher behavioural modification with new portable video technology, to today’s mini-lessons recorded on students’ phones, microteaching has evolved with the trends in educational theory and technology. Today’s microteaching research and practice should be informed by those that have come before it, but also reflect the field’s current trends in practice and theory.

Electrotactile Perception Properties and Its Applications: A Review.

With the increased demands of human-machine interaction, haptic feedback is becoming increasingly critical. However, the high cost, large size and low efficiency of current haptic systems severely hinder further development. As a portable and efficient technology, cutaneous electrotactile stimulation has shown promising potential for these issues. This paper presents a review on and insight into cutaneous electrotactile perception and its applications. Research results on perceptual properties and evaluation methods have been summarized and discussed to understand the effects of electrotactile stimulation on humans. Electrotactile applications are presented in categories to understand the methods and progress in various fields such as prostheses control, sensory substitution, sensory restoration and sensorimotor restoration. State of the art has demonstrated the superiority of electrotactile feedback, its efficiency and its flexibility. However, the complex factors and the limitations of evaluation methods made it challenging for precise electrotactile control. Groundbreaking innovation in electrotactile theory is expected to overcome challenges such as precise perception control, information capacity increasing, comprehension burden reducing and implementation costs.

Chinese Online Language Dissemination from the Perspective of Mobile Information System

The emergence of new media technology will inevitably bring new changes to people's daily communication. The development and change of society supports the development and change of language. Language networks are created and developed along with Internet applications. It is a new variant of the traditional language adapted to the new media environment of the Internet Age. With the increasing popularity and importance of network media, network language has received extensive attention and research on local languages. This paper analyzes and investigates the dissemination of Chinese Internet language from the perspective of mobile information system. On the basis of researching and proposing the mobile information system model, the structure of the system is deeply analyzed, and the key characteristics and technologies of various fields are discussed. Wireless mobile terminal wireless Internet access technology, portable intelligent terminal mobile application development technology, and local database technology are very suitable for Chinese network analysis and research to reduce wireless connections, and the effective range is from 50 feet to 1000 feet. The article uses the communication theories and methods of linguistics, cultural studies, network neologism generation, and communication characteristics analysis. It uses students as examples to explore their online neologism use and dyslexia and their problem-solving strategies for obstacles. The results show that 50% of the students can accept the new words on the Internet very well, and 30% of the students do not understand it.

Highlighting the Aspects to Support the Complexity of Primary Selection in Children's Alpine Skiing as a Sustainability of their Harmonious Development and Training

The extremely rapid evolution of portable technologies and children's receptiveness to constantly accessing the latest information creates the conditions for a number of new developments in most areas of activity. Moreover, their attraction to real-time visualisation of various events and competitions projects a certain level of perception and imitation of certain behaviours. Therefore, special attention should be paid to them from the earliest stages, i.e., from the time they are selected to play various sports. Also, the complementarity of some sports must be taken into account when it is desired to obtain positive results. Age group adaptation and the investigation of some of the parameters relevant to different age groups have generated values that can support positive outcomes in the long term and thus increase motivation to participate in sport at a competitive level.

Portable stroke detection devices: a systematic scoping review of prehospital applications

BackgroundThe worldwide burden of stroke remains high, with increasing time-to-treatment correlated with worse outcomes. Yet stroke subtype determination, most importantly between stroke/non-stroke and ischemic/hemorrhagic stroke, is not confirmed until hospital CT diagnosis, resulting in suboptimal prehospital triage and delayed treatment. In this study, we survey portable, non-invasive diagnostic technologies that could streamline triage by making this initial determination of stroke type, thereby reducing time-to-treatment.MethodsFollowing PRISMA guidelines, we performed a scoping review of portable stroke diagnostic devices. The search was executed in PubMed and Scopus, and all studies testing technology for the detection of stroke or intracranial hemorrhage were eligible for inclusion. Extracted data included type of technology, location, feasibility, time to results, and diagnostic accuracy.ResultsAfter a screening of 296 studies, 16 papers were selected for inclusion. Studied devices utilized various types of diagnostic technology, including near-infrared spectroscopy (6), ultrasound (4), electroencephalography (4), microwave technology (1), and volumetric impedance spectroscopy (1). Three devices were tested prior to hospital arrival, 6 were tested in the emergency department, and 7 were tested in unspecified hospital settings. Median measurement time was 3 minutes (IQR: 3 minutes to 5.6 minutes). Several technologies showed high diagnostic accuracy in severe stroke and intracranial hematoma detection.ConclusionNumerous emerging portable technologies have been reported to detect and stratify stroke to potentially improve prehospital triage. However, the majority of these current technologies are still in development and utilize a variety of accuracy metrics, making inter-technology comparisons difficult. Standardizing evaluation of diagnostic accuracy may be helpful in further optimizing portable stroke detection technology for clinical use.

Eye Movements in Mild Traumatic Brain Injury: Ocular Biomarkers.

Mild traumatic brain injury (mTBI, or concussion), results from direct and indirect trauma to the head (i.e. a closed injury of transmitted forces), with or without loss of consciousness. The current method of diagnosis is largely based on symptom assessment and clinical history. There is an urgent need to identify an objective biomarker which can not only detect injury, but inform prognosis and recovery. Ocular motor impairment is argued to be ubiquitous across mTBI subtypes and may serve as a valuable clinical biomarker with the recent advent of more affordable and portable eye tracking technology. Many groups have positively correlated the degree of ocular motor impairment to symptom severity with a minority attempting to validate these findings with diffusion tract imaging and functional MRI. However, numerous methodological issues limit the interpretation of results, preventing any singular ocular biomarker from prevailing. This review will comprehensively describe the anatomical susceptibility, clinical measurement, and current eye tracking literature surrounding saccades, smooth pursuit, vestibulo-ocular reflex, vergence, pupillary light reflex, and accommodation in mTBI.

Technology usage for teaching and learning in nursing education: An integrative review.

BackgroundThe increasing availability of technology devices or portable digital assistant devices continues to change the teaching-learning landscape, including technology-supported learning. Portable digital assistants and technology usage have become an integral part of teaching and learning nowadays. Cloud computing, which includes YouTube, Google Apps, Dropbox and Twitter, has become the reality of today’s teaching and learning and has noticeably improved higher education, including nursing education.ObjectivesThe aim of this integrative literature review was to explore and describe technology usage for teaching and learning in nursing education.MethodA five-step integrative review framework by Whittemore and Knafl was used to attain the objective of this study. The authors searched for both empirical and non-empirical articles from EBSCOhost (health information source and health science), ScienceDirect and African Journals Online Library databases to establish what is already known about the keywords. Key terms included in literature search were coronavirus disease 2019 (COVID-19), digital learning, online learning, nursing, teaching and learning, and technology use.ResultsNineteen articles were selected for analysis. The themes that emerged from this review were (1) technology use in nursing education, (2) the manner in which technology is used in nursing education, (3) antecedents for technology use in nursing education, (4) advantages of technology use in nursing education, (5) disadvantages of technology use in nursing education and (6) technology use in nursing education amidst COVID-19.ConclusionTechnology in nursing education is used in both clinical and classroom teaching to complement learning. However, there is still a gap in its acceptance despite its upward trend.ContributionThe findings of this study contribute to the body of knowledge on the phenomenon of technology use for teaching and learning in nursing education.

TEACHING ENGLISH DURING THE COVID-19 PANDEMIC

On account of the worldwide Covid-19 pandemic, the move online learning amid the quarantine has different negative impacts on teachers and learners. On the point of the failure to adjust bodily instruction strategies to remove instruction, and the incapacity to plan modern teaching forms has led to pressure and tension being exerted on learning experience; this rings true for students. The present research focuses on exploring the challenges and opportunities of online education while learning English as a Foreign Language (EFL). In consequence, historical process of online education and importance of online education while learning EFL are briefly summarized, and challenges and opportunities of online education, possible security problems faced by online learners and purposes of learners' use of social media are discussed in this research. A questionnaire adapted from Becker (2019), titled ‘E-learning Questionnaire’ was used in the study. 87 students studying at Foreign Languages Teaching department at Khoja Akhmet Yassawi International Kazakh-Turkish University in Kazakhstan participated in the study. The results of this study show that all participants have been using the Internet for years. Most of the participants improve their English language skills through the Internet, and they mostly prefer portable digital technologies to access the Internet. Easy access to updated English resources, learning at one’s personal space, flexibility, and eliminating travel and accommodation costs are among the opportunities of e-learning mostly agreed by the participants. The main challenges of online education are social isolation, not getting instant feedback, negative attitudes towards online education, planning difficulties as a result of lack of self-study habits, and fear of using digital technologies resulting from lack of technical training and support.

Roboethics in Remote Human Interactions and Rehabilitative Therapeutics

Global aging, the need for continuous high-quality services, and the recent COVID-19 pandemic have caused many sectors to reduce in-person contact between individuals where possible, and to instead use remote communication technology. With increased robot use replacing in-person interventions, ethical considerations arise. The benefits of robotic technology must be weighed against the possibility of harm to humans. The first rules of roboethics were written by Isaac Asimov in 1942, but these pre-date the range of robotic applications used today. There is no central agency for oversight in Canada, although universities and funding organizations have developed guidelines. Roboethical considerations include data use and privacy, the common good, and safety. Humans may potentially form emotional bonds with robots. Loss of jobs to automation is also a concern, particularly when many workers have suffered job losses due to the pandemic. Some health care services have switched to a remote care model, to reduce the spread of COVID-19. Remote hand rehabilitation of patients with brain injury is possible with iManus. Using a portable smart-glove technology, patients practice rehabilitative hand movements that are analyzed remotely through a sensor that offers instantaneous feedback. A therapist monitors their patient’s progress remotely and designs individualized programs. This technology benefits humanity by improving access to care for patients globally. The importance of data security and privacy is emphasized. As patient progress will be monitored by a human (a therapist), the safety of iManus is not a concern. The principles discussed in this paper can help researchers and engineers design ethical robotics in remote health care settings.

Smart connected worker edge platform for smart manufacturing: Part 2—Implementation and on‐site deployment case study

AbstractIn this paper, we describe specific deployments of the Smart Connected Worker (SCW) Edge Platform for Smart Manufacturing through implementation of four instructive real‐world use cases that illustrate the role of people in a Smart Manufacturing paradigm through which affordable, scalable, accessible, and portable (ASAP) information technology (IT) acquires and contextualizes data into information for transmission to operation technologies (OT). For case one, the platform captures the relationships between energy consumption and human workflows for improved energy productivity while workers interact with machines during semiconductor manufacturing. The platform utilizes human cognition to identify anomalous machine behavior for root cause analysis of system faults via neural network (NN) that recognize alarm postures of workers with cameras. For case two, a smart assembly line is demonstrated for state monitoring and fault detection. Machine learning (ML) models are used to recognize system states and identify fault scenarios with human intervention. For case three, the platform monitors human–machine interactions to classify manufacturing machine states for proper operations and energy productivity. Internal energy states of individual or collections of manufacturing equipment are determined via NN based algorithms that disaggregate signals associated with smart metering typically deployed at manufacturing facilities. These methods predict the real time energy profile of each machine from the total energy profile of a manufacturing site. For case four, a software defined sensor system built with scientific workflow engines is demonstrated for contextualizing data from laser surface refraction for characterization, and diagnostics in the processing of additively manufactured titanium alloy.

Monitoring rapid metabolic changes in health and type-1 diabetes with breath acetone sensors

Routine detection of health parameters is desirable to recognize the early onset of metabolic diseases (e.g., diabetes mellitus) and to personalize their treatment. Promising are non-invasive, affordable and portable technologies, such as breath sensors. Yet, the selective monitoring of breath markers (e.g., acetone for lipolysis) with sensors to track metabolic changes that can reveal disease-related abnormalities remains challenging. Here, subtle breath acetone changes during fasting, exercise and glucose ingestion are tracked in two model situations: Patients suffering from type-1 diabetes mellitus (T1DM) and healthy subjects (total: 19 volunteers) were monitored using chemoresistive sensors based on Si/WO3 nanoparticles. Specifically, each subject cycled after overnight fasting to stimulate fatty acid oxidation followed by an oral glucose tolerance test (OGTT), as monitored by capillary blood glucose and β-hydroxybutyrate (BOHB) concentrations. The sensor recognized accurately the individual breath acetone patterns before and after OGTT (both R2 = 0.9) at negligible interference, for instance, from glucose ingestion-associated volatiles (e.g., ethanol) or isoprene, as confirmed by high-resolution mass spectrometry. Furthermore, distinct differences in the breath acetone patterns of T1DM over healthy subjects were revealed including higher (t-test, p = 0.006) breath acetone ratio 2 h after starting the OGTT. Worth noting is that after glucose intake, breath isoprene steadily increased for T1DM subjects while it remained rather constant for healthy ones, an intriguing observation that requires more research to clarify its biochemical origin and medical relevance.

Use and Trends of Diabetes Self-Management Technologies: A Correlation-Based Study.

Applications and systems for diabetes self-management are growing and involve a vast majority of factors to consider. This study was aimed at examining the integration of portable technologies for diabetes self-management, as well as benefits and issues arising of its use. From a web-based study on several groups of people with diabetes, most of them accustomed to the daily use of devices and applications for self-control, a deeper analysis based on correlations and inference was conducted considering information about the disease, technology knowledge and devices handling, use of technologies for diabetes control and management, and training with devices from a clinical and educational viewpoint. In this study, more than 70% of participants use Continuous Glucose Systems and additional devices (41.85% also use insulin pumps) which impacts positively on the knowledge of incoming technologies. The “easy to use” factor of current apps for diabetes self-management is the most valuable feature. Also, 88.98% of participants did not use gamification-based methods during the initial training sessions, although gamification is a useful technique in learning stages. An inference analysis shows how specific characteristics of diabetes devices and apps should improve. On the basis of the results, we discuss about benefits, shortcomings, and the state of these technologies and patient needs for the future.