Personal Devices Research Articles

The Real-World Usability, Feasibility, and Performance Distributions of Deploying a Digital Toolbox of Computerized Assessments to Remotely Evaluate Brain Health: Development and Usability Study.

An ongoing global challenge is managing brain health and understanding how performance changes across the lifespan. We developed and deployed a set of self-administrable, computerized assessments designed to measure key indexes of brain health across the visual and auditory sensory modalities. In this pilot study, we evaluated the usability, feasibility, and performance distributions of the assessments in a home-based, real-world setting without supervision. Potential participants were untrained users who self-registered on an existing brain training app called BrainHQ. Participants were contacted via a recruitment email and registered remotely to complete a demographics questionnaire and 29 unique assessments on their personal devices. We examined participant engagement, descriptive and psychometric properties of the assessments, associations between performance and self-reported demographic variables, cognitive profiles, and factor loadings. Of the 365,782 potential participants contacted via a recruitment email, 414 (0.11%) registered, of whom 367 (88.6%) completed at least one assessment and 104 (25.1%) completed all 29 assessments. Registered participants were, on average, aged 63.6 (SD 14.8; range 13-107) years, mostly female (265/414, 64%), educated (329/414, 79.5% with a degree), and White (349/414, 84.3% White and 48/414, 11.6% people of color). A total of 72% (21/29) of the assessments showed no ceiling or floor effects or had easily modifiable score bounds to eliminate these effects. When correlating performance with self-reported demographic variables, 72% (21/29) of the assessments were sensitive to age, 72% (21/29) of the assessments were insensitive to gender, 93% (27/29) of the assessments were insensitive to race and ethnicity, and 93% (27/29) of the assessments were insensitive to education-based differences. Assessments were brief, with a mean duration of 3 (SD 1.0) minutes per task. The pattern of performance across the assessments revealed distinctive cognitive profiles and loaded onto 4 independent factors. The assessments were both usable and feasible and warrant a full normative study. A digital toolbox of scalable and self-administrable assessments that can evaluate brain health at a glance (and longitudinally) may lead to novel future applications across clinical trials, diagnostics, and performance optimization.

VibHead: An Authentication Scheme for Smart Headsets through Vibration

Recent years have witnessed the fast penetration of Virtual Reality (VR) and Augmented Reality (AR) systems into our daily life, the security and privacy issues of the VR/AR applications have been attracting considerable attention. Most VR/AR systems adopt head-mounted devices (i.e., smart headsets) to interact with users and the devices usually store the users’ private data. Hence, authentication schemes are desired for the head-mounted devices. Traditional knowledge-based authentication schemes for general personal devices have been proved vulnerable to shoulder-surfing attacks, especially considering the headsets may block the sight of the users. Although the robustness of the knowledge-based authentication can be improved by designing complicated secret codes in virtual space, this approach induces a compromise of usability. Another choice is to leverage the users’ biometrics; however, it either relies on highly advanced equipments which may not always be available in commercial headsets or introduce heavy cognitive load to users. In this paper, we propose a vibration-based authentication scheme, VibHead, for smart headsets. Since the propagation of vibration signals through human heads presents unique patterns for different individuals, VibHead employs a CNN-based model to classify registered legitimate users based the features extracted from the vibration signals. We also design a two-step authentication scheme where the above user classifiers are utilized to distinguish the legitimate user from illegitimate ones. We implement VibHead on a Microsoft HoloLens equipped with a linear motor and an IMU sensor which are commonly used in off-the-shelf personal smart devices. According to the results of our extensive experiments, with short vibration signals (≤ 1s ), VibHead has an outstanding authentication accuracy; both FAR and FRR are around 5%.

Effects of postural control by personal mobility on human joint movements-prototype of a new alert system for personal mobility devices

Purpose: This study aimed to develop a prototype Personal Mobility (PM) system with human-robot synchronous motion measurement and sensory feedback as an attention reminder to ensure the safe performance of sustained, step-by-step rehabilitation tailored to the daily living conditions of elderly individuals. Methods: Five healthy adults were fitted with a simulation tool to experience the elderly, and inertial measurement unit sensors were placed on the subjects and the PM device to measure joint movements during two postural movements (sitting to supine and supine to standing). In addition, vibration stimulation and voice guidance were implemented as alerts at a certain set threshold of the joint motion angle. We analyzed the deviation of each joint motion between the subject and the PM device regarding the angle measurements of the trunk, hip, knee, and ankle joints. Results: Trunk angle misalignment was high in the sitting-to-supine position. Hip angle misalignment was greater in the supine to standing position. As an alert system, vibration and voice guidance could be presented to the subject with a 0.3-second delay after the set threshold was reached. Conclusion: The misalignment between a human and a motorized wheelchair in contact with the human is more than several tens of degrees when expressed as the angle change value of the joint motion. We believe that a system that can constantly sense and alert the user regarding whether the user and the PM device are in sync is necessary for PM devices being used in rehabilitation or as daily life support.

Understanding of non-immersive virtual reality technology in the context of museums via the lens of stimulus–organism–response (S–O–R) and aesthetics frameworks

ABSTRACT Guided by the Stimulus–Organism–Response (S–O–R) and aesthetics frameworks, this research investigated the impacts of non-immersive virtual reality (VR) aesthetics on visitors’ perceived utilitarian and hedonic values, attitudes toward VR, and visit intention. Three hundred and thirty-five respondents who had completed a virtual guided tour provided by the Hong Kong Railway Museum by using personal devices such as computers and smartphones without having the aid of more advanced technologies were surveyed. The results revealed that design aesthetics, interactivity aesthetics, and presence aesthetics of VR could strongly predict users’ cognitive and emotional reactions regarding their perceptions of utilitarian and hedonistic values, their attitude toward using VR, and their intention to visit the museums, with the exception that interactivity aesthetics was found to have no effects on the perceived utilitarian values. This study contributed by providing a newly formulated and tested theoretical framework that aids understanding of the role of aesthetics in VR technology in the specific context of museums. It also sheds light for museum operators on how VR innovation can evoke positive responses and attract more visitors.

Thermal performance of a novel traditional Chinese personal heating device (Huotong) combined with PCMs

Chinese traditional individual heating equipment with a history of hundreds of years “Huotong” was widely used in rural areas. The Huotong consisted of a closed wooden barrel-shaped outer wall and an iron basin with combustion layer. However, the traditional Huotong had problems of low energy utilization efficiency and poor thermal comfort. Thus, a novel Huotong combined with phase change materials (PCMs) was proposed. The basic model of novel Huotong was designed and manufactured. The thermal performances of the novel Huotong under two kinds of heat sources of charcoal heating and electric heating were investigated. The results showed that: (1) Under the method of charcoal heating, the heat storage and thermal comfort performance of the novel Huotong were higher than that of the traditional Huotong. Under the three-charcoal mass of 0.15, 0.25 and 0.5 kg, the heat storage performance of the novel Huotong was 1.36, 1.43 and 1.52 times of the traditional Huotong, respectively. The average PMV values of the novel Huotong was 0.92, 1.17 and 1.31, while for the traditional Huotong was 0.87, 1.32 and 1.58, respectively. (2) Under the four electric heating methods, the thermal efficiency of the novel Huotong was 1.63, 1.61, 1.47 and 1.39 times of the traditional Huotong, respectively. The heat storage performance was 1.72, 1.67, 1.47 and 1.28 times than that of the traditional Huotong. The average PMV values of the novel Huotong was 1.25, 1.22, 0.69 and 1.68, while for the traditional Huotong was 1.64, 1.53, 0.87 and 2.03, respectively.

IMPACT OF REMOTE MONITORING ON PATIENTS’ QUALITY OF LIFE. A SINGLE CENTRE STUDY

Objective: PROSIT (Patient Reported Outcomes and Smart Imaging in Telecardiology) is an innovative research initiative designed to explore the efficacy of remote patient monitoring in cardiovascular care. This project leverages wearable technology and patient-reported data to enhance the management of cardiac conditions, aiming to improve both patient outcomes and quality of life. Design and method: We evaluated 100 Caucasian patients, affected by hypertension, who access to Unit of Internal Medicine “G. Baccelli” and Unit of Hypertension “A.M. Pirrelli” from April to October 2023. Patients were divided in three groups: group A, with a wearable device (Hi) for continuous monitoring and an app with manual vital signs reporting, group B with only manual vital signs reporting through app on personal devices, and group C as the control group. The app for A and B group was able to suggest patient-physician interaction evaluating data inputted. All patients were assigned in different groups with a randomized approach based on factors such as age, gender, ejection fraction, presence of atrial fibrillation, and pulmonary embolism. Results: Telemonitoring usage has led patients to experience safe feelingsin their daily lives. In fact, patients in group B (app only) and A (app and Hi device) presented an improvement, notably significant for those in group A (p<0,05), compared to group C. In contrast, group C did not change their responses after one month of follow-up. Despite encountering minor issues during the trial, all enrolled patients believe that the telemonitoring program and telemedicine visits are commendable. Although the patients themselves have pointed out areas for improvement in the software, this does not diminish the substantial foundation that this technology signifies. No change was found in treatment adherence or blood pressure control. Conclusions: This study leads up to a future where digital support to medical practice will play a crucial role in accessing patient care and therapies, both for patients and clinicians alike. Patients are ready to embrace a new method for accessing care and being monitored by clinicians, one that integrates the old and the new, keeping pace with the times.

Consumer wearables and personal devices for tracking the fertile window

The market for technology that tracks ovulation to promote conception is rapidly expanding in the United States, targeting the growing audience of technologically proficient, reproductive-age female consumers. In this narrative review, twenty-three different, non-prescription wearables and devices designed to help women track their fertile window were identified as currently, commercially available in the United States. The majority of these utilize measurements of basal body temperature or combinations of various urinary hormones. This clinical opinion characterizes the scant available research validating the accuracy of these technologies. It further examines research oversight, discusses the utility of these wearables and devices to consumers, and considers these technologies through an equity lens. The discussion concludes with a call for innovation, describing promising new technologies that not only harness unique physiologic parameters to predict ovulation, but also focus on cost-effectiveness with the hope of increasing access to these currently costly devices and wearables.

Examination of Dominant Factors Affecting The Decision To Purchase Personal Medical Devices

This study aims to analyze the effect of product quality, price perception, advertising and distribution channels on purchasing decisions for personal health devices. In addition, this study also aims to determine the dominant factors that influence purchasing decisions for medical devices. This research was conducted in Denpasar City by taking a research sample of 100 (one hundred) people using purposive sampling technique. This study uses multiple linear regression analysis techniques, t test and F test and test of determination. The result of the research is product quality, price perception has a positive and significant effect on purchasing decisions, while distribution channels have no significant effect on purchasing decisions. The implication of this research is that manufacturers who provide medical devices must be able to carry out price strategies in improving purchasing decisions and controlling market share in the health industry.

Using personal tracking software data to aid the impact of illegal trails in national parks

ABSTRACT The use of personal tracking devices for recreational use and for safety when in the outdoors has grown exponentially in recent years. The large-scale data collected through these platforms has enabled our team to gain a greater understanding of the way in which people encroach onto National Parks causing environmental damage. The project used freely accessible data on the access of illegal trails primarily from motor bike and mountain bike use in the East Otway Range of Victoria. This region was an excellent case study as it is a mosaic of state and national parks and the signage and restrictive fences place by national parks have been aligned with the illegal trail formation. The data mapping has been coupled with measurement of the impact on the environment including the number and scale of the trails and the type of environment they are impacting including fauna and flora of national significance. The data has shown some useful information around the manner in which illegal trails are identified and concealed by users. Further, the research has uncovered ways in which trails have been concealed from authorities.

Стратегическое значение инновационных кластеров Москвы в развитии прогрессивной транспортной инфраструктуры мегаполиса

The pace of metropolitan life is growing higher and higher. To keep up with it, Moscow residents have to abandon cars and public transport in favor of personal mobility devices, e.g., electric scooters. As a result, the state authorities are developing a unified strategy for urban public transport that would include personal mobility devices and their rent. An effective strategy should integrate all innovative public transport vehicles into a single urban transport system. Technopolis is a special economic zone of innovation clusters in Moscow that offers conditions for design and production of innovative electric individual mobility devices. New-generation vehicles that meet the needs of metropolitan residents will become a key strategic vector in the development of Moscow’s transport system. The key strategic goals are to improve the quality of urban life and to ensure the national technological sovereignty. Modernization and consistent implementation of production facilities can stimulate innovative technologies in the transport sector and its progressive transformation nationwide. Moscow’s innovation clusters produce innovative technologies, test them, and spread the most effective innovations onto all regions.

Study of the Demand for Ecological Means of Transport in Micromobility: A Case of Bikesharing in Szczecin, Poland

The need for urban societies to move continues to grow with the intensity of their various activities. One of the challenges in micromobility in cities based on bike, scooter, or public scooter systems is determining the potential yet realistic demand for such services. This article aims to present the level of demand for eco-friendly non-motorized transport systems and identify the motivations driving users of public transport to choose these eco-friendly Personal Mobility Devices (PMD). The authors propose a methodology based on the integration of four components: a case study, an analysis of participatory budget projects, a metadata analysis of bikesharing (BSS) in Szczecin, and a meta plan. They utilized a case study method and conducted a survey based on a custom questionnaire. An analysis of participatory budget projects and data from the operation of bikesharing in Szczecin was performed using statistical methods. Applying the heuristic tool meta plan, they outlined the directions for the development and support of bikesharing as an example of micromobility in Szczecin. The research identified connections between the socio-demographic structure of respondents and attributes of bike communication. This study highlighted periods of intensive system use and locations with the highest exploitation. It showed that the demand for BSS depends on weather conditions, traveler convenience, the density and coherence of bike infrastructure with important locations for residents, transfer connections, and safety. The presented research results can assist planners and authorities in Szczecin and other cities in expanding bikesharing.

Lightweight Crypto-Ransomware Detection in Android Based on Reactive Honeyfile Monitoring.

Given the high relevance and impact of ransomware in companies, organizations, and individuals around the world, coupled with the widespread adoption of mobile and IoT-related devices for both personal and professional use, the development of effective and efficient ransomware mitigation schemes is a necessity nowadays. Although a number of proposals are available in the literature in this line, most of them rely on machine-learning schemes that usually involve high computational cost and resource consumption. Since current personal devices are small and limited in capacities and resources, the mentioned schemes are generally not feasible and usable in practical environments. Based on a honeyfile detection solution previously introduced by the authors for Linux and Window OSs, this paper presents a ransomware detection tool for Android platforms where the use of trap files is combined with a reactive monitoring scheme, with three main characteristics: (i) the trap files are properly deployed around the target file system, (ii) the FileObserver service is used to early alert events that access the traps following certain suspicious sequences, and (iii) the experimental results show high performance of the solution in terms of detection accuracy and efficiency.

Caffeic-Acid-Functionalized MWCNTs and PEDOT:PSS Formed Composite Flexible Films with "Reinforced Concrete" Structure for Electrical Heating and EMI Shielding.

Nowadays, flexible multifunctional composites are attracting much attention and are practically being used in various emerging electronic devices. However, most composites suffer from the disadvantages of high loadings of conductive fillers, complicated preparation processes, and low energy conversion efficiency. In this article, Caffeic acid-modified multiwalled carbon nanotubes (C-MWCNTs)/poly(3,4-ethylene dioxythiophene):polystyrene sulfonic acid (PEDOT:PSS)/polyimide (PI) composite films (CPFs) were prepared using a simple layer-by-layer deposition method. The "reinforced concrete" structure of the C-MWCNTs/PEDOT:PSS layer ensures high electrical conductivity of the film, while the PI layer provides excellent mechanical properties (72.69 MPa). The composite film exhibits excellent electrothermal response and thermal stability up to approximately 125 °C at 5 V. In addition, the good conductivity of the film provides its electromagnetic shielding effectiveness (32.69 dB). With these advantages, we expect that flexible CPFs will be widely utilized in wearable devices, electromagnetic interference (EMI) shielding applications, and thermal management of personal or electronic devices.

Development and validation of an episodic memory measure in the Mobile Toolbox (MTB): Arranging Pictures

ABSTRACT Introduction Arranging Pictures is a new episodic memory test based on the NIH Toolbox (NIHTB) Picture Sequence Memory measure and optimized for self-administration on a personal smartphone within the Mobile Toolbox (MTB). We describe evidence from three distinct validation studies. Method In Study 1, 92 participants self-administered Arranging Pictures on study-provided smartphones in the lab and were administered external measures of similar and dissimilar constructs by trained examiners to assess validity under controlled circumstances. In Study 2, 1,021 participants completed the external measures in the lab and self-administered Arranging Pictures remotely on their personal smartphones to assess validity in real-world contexts. In Study 3, 141 participants self-administered Arranging Pictures remotely twice with a two-week delay on personal iOS smartphones to assess test-retest reliability and practice effects. Results Internal consistency was good across samples (ρxx = .80 to .85, p < .001). Test-retest reliability was marginal (ICC = .49, p < .001) and there were significant practice effects after a two-week delay (ΔM = 3.21 (95% CI [2.56, 3.88]). As expected, correlations with convergent measures were significant and moderate to large in magnitude (ρ = .44 to .76, p < .001), while correlations with discriminant measures were small (ρ = .23 to .27, p < .05) or nonsignificant. Scores demonstrated significant negative correlations with age (ρ = -.32 to −.21, p < .001). Mean performance was slightly higher in the iOS compared to the Android group (MiOS = 18.80, NiOS = 635; MAndroid = 17.11, NAndroid = 386; t(757.73) = 4.17, p < .001), but device type did not significantly influence the psychometric properties of the measure. Indicators of potential cheating were mixed; average scores were significantly higher in the remote samples (F(2, 850) = 11.415, p < .001), but there were not significantly more perfect scores. Conclusion The MTB Arranging Pictures measure demonstrated evidence of reliability and validity when self-administered on personal device. Future research should examine the potential for cheating in remote settings and the properties of the measure in clinical samples.

Design Novel CNN Architecture to Protect Personal Devices from Unauthorized Access Using Face Recognition

Design Novel CNN Architecture to Protect Personal Devices from Unauthorized Access Using Face Recognition

Personal Air-Quality Monitoring with Sensor-Based Wireless Internet-of-Things Electronics Embedded in Protective Face Masks

Personal Air-Quality Monitoring with Sensor-Based Wireless Internet-of-Things Electronics Embedded in Protective Face Masks

Driving in Cars with Noise

Driving in Cars with Noise

Evaluating the Acceptability and Feasibility of Collecting Passive Smartphone Data to Estimate Psychological Functioning in U.S. Service Members and Veterans: A Pilot Study.

This study investigated the acceptability and feasibility of digital phenotyping in a military sample with a history of traumatic brain injury and co-occurring psychological and cognitive symptoms. The first aim was to evaluate the acceptability of digital phenotyping by (1a) quantifying the proportion of participants willing to download the app and rates of dropout and app discontinuation and (1b) reviewing the stated reasons for both refusing and discontinuing use of the app. The second aim was to investigate technical feasibility by (2a) characterizing the amount and frequency of transferred data and (2b) documenting technical challenges. Exploratory aim 3 sought to leverage data on phone and keyboard interactions to predict if a participant (a) is depressed and (b) has depression that improves over the course of the study. A passive digital phenotyping app (Mindstrong Discovery) functioned in the background of the participants' smartphones and passively collected phone usage and typing kinematics data. Fifteen out of 16 participants (93.8%) consented to install the app on their personal smartphone devices. Four participants (26.7%) discontinued the use of the app partway through the study, primarily because of keyboard usability and technical issues. Fourteen out of 15 participants (93.3%) had at least one data transfer, and the median number of days with data was 40 out of a possible 57 days. The exploratory machine learning models predicting depression status and improvement in depression performed better than chance. The findings of this pilot study suggest that digital phenotyping is acceptable and feasible in a military sample and provides support for future larger investigations of this technology.

Immaterial intimacy: The neoliberal entanglement of digital technologies in social movement volunteer work

Outside of visible moments of mass mobilization, ongoing latent work, such as direct service and mutual aid, is a long-standing tradition in social movements. Yet, like all labor, personal digital devices have changed the norms and practices of direct service social movement work. In this article, as situated in the technology–media–movement complex (TMMC), I analyze qualitative interview data ( N = 26) with volunteers from a yearlong ethnographic project at an abortion fund hotline in the reproductive justice movement in the US South. To name hotline volunteers’ digital care labor, I offer the term immaterial intimacy to describe its ubiquitous, ephemeral, and intimate nature. I argue immaterial intimate labor enabled the organization to provide a responsive service, but relied on individualized digital volunteer work, existing within gendered and neoliberal norms. I discuss and question the use of personal digital technologies for direct service volunteer work in contemporary social movements.

Enhancing Facial Recognition Accuracy in Low-Light Conditions Using Convolutional Neural Networks

Facial recognition technology has become increasingly everywhere in various domains, from security and surveillance to personal device authentication. However, its effectiveness can be significantly hindered in low-light conditions, where images often lack sufficient illumination for accurate recognition. This study proposes a novel approach to enhance facial recognition accuracy in low-light conditions using Convolutional Neural Networks (CNNs), Deep Retinex Decomposition Network (DRDN), and CenterFace algorithm. The methodology leverages CNNs for robust feature extraction, while DRDN corrects illumination by decomposing images. CenterFace integrates feature fusion and denoising layers for discriminative facial features and noise mitigation. Experimental results demonstrate a remarkable improvement in recognition performance, exceeding 80% accuracy. This approach showcases the potential of CNN-based methods with advanced techniques to enhance reliability in real-world facial recognition applications, particularly in low-light environments.