Mobile Handheld Devices Research Articles

Teleophthalmology through handheld mobile devices: a pilot study in rural Nepal.

To compare screening referral recommendations made by remotely located ophthalmic technicians with those of an ophthalmologist examining digital photos obtained by a portable ophthalmic camera system powered by an iOS handheld mobile device (iPod Touch). Dilated screening eye exams were performed by ophthalmic technicians in four remote districts of Nepal. Anterior and posterior segment photographs captured with a Paxos Scope ophthalmic camera system attached to an iPod Touch 6th generation device were uploaded to a secure cloud database for review by an ophthalmologist in Kathmandu. The ophthalmic technicians' referral decisions based on slit-lamp exam were compared to the ophthalmologist's recommendation based on the transmitted images. Using the transmitted images, the ophthalmologist recommended referral for an additional 20% of the 346 total subjects screened who would not have been referred by the ophthalmic technician. Of those subjects, 34% were referred to the retina clinic. Conversely, among the 101 patients referred by the technician, the ophthalmologist concurred with the appropriateness of referral in more than 97% of cases but thought eight (2.8%) of those patients had variants of normal eye pathology. An ophthalmologist who reviewed data and photos gathered with the mobile device teleophthalmology system identified a significant number of patients whose need for referral was not identified by the screening technician. Posterior segment pathology was most frequently found by the remote reader and not by the technician performing dilated slit lamp examinations. These results are promising for further clinical implementation of handheld mobile devices as tools for teleophthalmic screening in resource-limited settings.

"Get Ready and Empowered About Treatment" (GREAT) Study: a Pragmatic Randomized Controlled Trial of Activation in Persons Living with HIV.

Little is known about strategies to improve patient activation, particularly among persons living with HIV (PLWH). To assess the impact of a group intervention and individual coaching on patient activation for PLWH. Pragmatic randomized controlled trial. Eight practices in New York and two in New Jersey serving PLWH. Three hundred sixty PLWH who received care at participating practices and had at least limited English proficiency and basic literacy. Six 90-min group training sessions covering use of an ePersonal Health Record loaded onto a handheld mobile device and a single 20-30min individual pre-visit coaching session. The primary outcome was change in Patient Activation Measure (PAM). Secondary outcomes were changes in eHealth literacy (eHEALS), Decision Self-efficacy (DSES), Perceived Involvement in Care Scale (PICS), health (SF-12), receipt of HIV-related care, and change in HIV viral load (VL). The intervention group showed significantly greater improvement than the control group in the primary outcome, the PAM (difference 2.82: 95% confidence interval [CI] 0.32-5.32). Effects were largest among participants with lowest quartile PAM at baseline (p < 0.05). The intervention doubled the odds of improving one level on the PAM (odds ratio 1.96; 95% CI 1.16-3.31). The intervention group also had significantly greater improvement in eHEALS (difference 2.67: 95% CI 1.38-3.9) and PICS (1.27: 95% CI 0.41-2.13) than the control group. Intervention effects were similar by race/ethnicity and low education with the exception of eHealth literacy where effects were stronger for minority participants. No statistically significant effects were observed for decision self-efficacy, health status, adherence, receipt of HIV relevant care, or HIV viral load. The patient activation intervention modestly improved several domains related to patient empowerment; effects on patient activation were largest among those with the lowest levels of baseline patient activation. This study is registered at Clinical Trials.Gov (NCT02165735).

Understanding Users’ Intention to Use Mobile Financial Services: A Study in Khulna City

Purpose: Mobile Financial Services are such applications of mobile computing which provide customers the support that is needed to access their bank accounts and bank anywhere and anytime using a mobile handheld device such as a mobile phone. Mobile Financial Services remove space and time limitations from banking activities such as checking account balances or transferring money from one account to another. The study tries to understand users’ level of intention to use mobile financial services in Khulna city. Methodology: Data have been collected from 110 respondents out of which 35 respondents are agents and rest is from different professions. All mobile financial service users in Khulna city have been assumed as population for the study. There has been no demographic barrier for the mobile financial services users to be taken or to be given priority. A structured questionnaire has been administered among the respondents to collect the data. There are 7 variables that have been interviewed among the respondents. These variables are taken from ‘Technology acceptance model’ and ‘Theory of reasoned action’. Correlation and multiple regression analysis are applied to understand the intention of the users. Findings: The study finds that there are strong relationships among the variables. It also shows that trust has strong relation with intention to use mobile financial services. Value: Different stakeholders like mobile financial service providers, mobile operators, regulatory authorities, government and others will get benefit from the study.

Chronic wound assessment and infection detection method

BackgroundNumerous patients suffer from chronic wounds and wound infections nowadays. Until now, the care for wounds after surgery still remain a tedious and challenging work for the medical personnel and patients. As a result, with the help of the hand-held mobile devices, there is high demand for the development of a series of algorithms and related methods for wound infection early detection and wound self monitoring.MethodsThis research proposed an automated way to perform (1) wound image segmentation and (2) wound infection assessment after surgical operations. The first part describes an edge-based self-adaptive threshold detection image segmentation method to exclude nonwounded areas from the original images. The second part describes a wound infection assessment method based on machine learning approach. In this method, the extraction of feature points from the suture area and an optimal clustering method based on unimodal Rosin threshold algorithm that divides feature points into clusters are introduced. These clusters are then merged into several regions of interest (ROIs), each of which is regarded as a suture site. Notably, a support vector machine (SVM) can automatically interpret infections on these detected suture site.ResultsFor (1) wound image segmentation, boundary-based evaluation were applied on 100 images with gold standard set up by three physicians. Overall, it achieves 76.44% true positive rate and 89.04% accuracy value. For (2) wound infection assessment, the results from a retrospective study using confirmed wound pictures from three physicians for the following four symptoms are presented: (1) Swelling, (2) Granulation, (3) Infection, and (4) Tissue Necrosis. Through cross-validation of 134 wound images, for anomaly detection, our classifiers achieved 87.31% accuracy value; for symptom assessment, our classifiers achieved 83.58% accuracy value.ConclusionsThis augmentation mechanism has been demonstrated reliable enough to reduce the need for face-to-face diagnoses. To facilitate the use of this method and analytical framework, an automatic wound interpretation app and an accompanying website were developed.Trial registration201505164RIND, 201803108RSB.

Feasibility and performance of a device for automatic self-detection of symptomatic acute coronary artery occlusion in outpatients with coronary artery disease: a multicentre observational study

Time delay between onset of symptoms and seeking medical attention is a major determinant of mortality and morbidity in patients with acute coronary artery occlusion. Response time might be reduced by reliable self-detection. We aimed to formally assess the proof-of-concept and accuracy of self-detection of acute coronary artery occlusion by patients during daily life situations and during the very early stages of acute coronary artery occlusion. In this multicentre, observational study, we tested the operational feasibility, specificity, and sensitivity of our RELF method, a three-lead detection system with an automatic algorithm built into a mobile handheld device, for detection of acute coronary artery occlusion. Patients were recruited continuously by physician referrals from three Belgian hospitals until the desired sample size was achieved, had been discharged with planned elective percutaneous coronary intervention, and were able to use a smartphone; they were asked to perform random ambulatory self-recordings for at least 1 week. A similar self-recording was made before percutaneous coronary intervention and at 60 s of balloon occlusion. Patients were clinically followed up until 1 month after discharge. We quantitatively assessed the operational feasibility with an automated dichotomous quality check of self-recordings. Performance was assessed by analysing the receiver operator characteristics of the ST difference vector magnitude. This trial is registered with ClinicalTrials.gov, number NCT02983396. From Nov 18, 2016, to April 25, 2018, we enrolled 64 patients into the study, of whom 59 (92%) were eligible for self-applications. 58 (91%) of 64 (95% CI 81·0-95·6) patients were able to perform ambulatory self-recordings. Of all 5011 self-recordings, 4567 (91%) were automatically classified as successful within 1 min. In 65 balloon occlusions, 63 index tests at 60 s of occlusion in 55 patients were available. The mean specificity of daily life recordings was 0·96 (0·95-0·97). The mean false positive rate during daily life conditions was 4·19% (95% CI 3·29-5·10). The sensitivity for the target conditions was 0·87 (55 of 63; 95% CI 0·77-0·93) for acute coronary artery occlusion, 0·95 (54 of 57; 0·86-0·98) for acute coronary artery occlusion with electrocardiogram (ECG) changes, and 1·00 (35 of 35) for acute coronary artery occlusion with ECG changes and ST-segment elevation myocardial infarction criteria (STEMI). The index test was more sensitive to detect a 60 s balloon occlusion than the STEMI criteria on 12-lead ECG (87% vs 56%; p<0·0001). The proportion of total variation in study estimates due to heterogeneity between patients (I2) was low (12·6%). The area under the receiver operator characteristics curve was 0·973 (95% CI 0·956-0·990) for acute coronary artery occlusion at different cutoff values of the magnitude of the ST difference vector. No patients died during the study. Self-recording with our RELF device is feasible for most patients with coronary artery disease. The sensitivity and specificity for automatic detection of the earliest phase of acute coronary artery occlusion support the concept of our RELF device for patient empowerment to reduce delay and increase Survival without overloading emergency services. Ghent University, Industrial Research Fund.

3484 Examining the Use of Mobile Technology Among Low-Income African Americans and Hispanics with Hypertension

OBJECTIVES/SPECIFIC AIMS: The primary objective of this study was to assess the interest in using mobile technology to manage hypertension and assessing medication adherence among African Americans and Hispanics living in a low-income urban community in Central PA. METHODS/STUDY POPULATION: This qualitative research study was designed using structured interviews with 30 African American participants with hypertension. The study survey consisted of 43 questions which included demographics, use of technology, technology literacy, health literacy, and medication adherence. Participants self-reported their responses about use of technology, literacy, and adherence. The data was examined using summary statistics. RESULTS/ANTICIPATED RESULTS: Out of 30 participants, 61% identified as African American and 30% identified as Hispanic. Overall, participants reported high use of technology; with 63.3% using the internet occasionally, 73.3% having a cell phone, and 66.7% accessing the internet using a mobile handheld device. Participants expressed an interest in measuring blood pressure, accessing health information, and managing medication on their cellphone or tablet. Twenty-five percent of participants self-reported not being confident at all in managing their medication without help and remembering to take their medication as prescribed. Fewer participants (54.2%) were very confident with using technology to help manage medication and treatment. DISCUSSION/SIGNIFICANCE OF IMPACT: This study provides important insights on the use of technology for managing hypertension in an urban low-income community. Results suggest that medication adherence, the use of technology, and the willingness to use mobile applications for hypertension management is high within this low-income community. This study gives future researchers a framework on how to assess these specific areas in their own population.

An Upgraded Version of the Binary Search Space-Structured VQ Search Algorithm for AMR-WB Codec

Adaptive multi-rate wideband (AMR-WB) speech codecs have been widely used for high speech quality in modern mobile communication systems, e.g., handheld mobile devices. Nevertheless, a major handicap is that a remarkable computational load is required in the vector quantization (VQ) of immittance spectral frequency (ISF) coefficients of an AMR-WB coding. In view of this, a two-stage search algorithm is presented in this paper as an efficient way to reduce the computational complexity of ISF quantization in AMR-WB coding. At stage 1, an input vector is assigned to a search subspace in an efficient manner using the binary search space-structured VQ (BSS-VQ) algorithm, and a codebook search is performed over the subspace at stage 2 using the iterative triangular inequality elimination (ITIE) approach. Through the use of the codeword rejection mechanisms equipped in both stages, the computational load can be remarkably reduced. As compared with the original version of the BSS-VQ algorithm, the upgraded version provides a computational load reduction of up to 51%. Furthermore, this work is expected to satisfy the energy saving requirement when implemented on an AMR-WB codec of mobile devices.

An Efficient and Provably Secure Anonymous User Authentication and Key Agreement for Mobile Cloud Computing

Nowadays, due to the rapid development and wide deployment of handheld mobile devices, the mobile users begin to save their resources, access services, and run applications that are stored, deployed, and implemented in cloud computing which has huge storage space and massive computing capability with their mobile devices. However, the wireless channel is insecure and vulnerable to various attacks that pose a great threat to the transmission of sensitive data. Thus, the security mechanism of how the mobile devices and remote cloud server authenticate each other to create a secure session in mobile cloud computing environment has aroused the interest of researchers. In this paper, we propose an efficient and provably secure anonymous two-factor user authentication protocol for the mobile cloud computing environment. The proposed scheme not only provides mutual authentication between mobile devices and cloud computing but also fulfills the known security evaluation criteria. Moreover, utilization of ECC in our scheme reduces the computing cost for mobile devices that are computation capability limited and battery energy limited. In addition, the formal security proof is given to show that the proposed scheme is secure under random oracle model. Security analysis and performance comparisons indicate that the proposed scheme has reasonable computation cost and communication overhead at the mobile client side as well as the server side and is more efficient and more secure than the related competitive works.

An efficient method of computation offloading in an edge cloud platform

In a data-rich digital world, our hand-held resource-constrained mobile devices are restricted to performing small-to-medium-level computation processes and are incapable of performing high-computation processes. Computation offloading is a suitable solution for overcoming this shortcoming. Until recently, we have perceived cloud computing as an appropriate computation-offloading platform for mobile devices. However, cloud data centers, being far-end networks for mobile devices, increase the latency or network delay, which in turn affects the performance of real-time mobile Internet-of-Things applications. Hence, for critical real-time applications, a near-end network approach of computation offloading is required. Furthermore, the major hurdles for geographically distributed mobile devices are mobility and heterogeneity in the process of computation offloading. To overcome these challenges, the use of a deep-learning-based response-time-prediction framework is proposed in this paper to determine whether to offload in the nearby fog/edge node or neighbor fog/edge node, or cloud node. Furthermore, a restricted Boltzmann machines learning is applied to tackle the randomness in the availability of resources. We simulate the proposed model in MATLAB while considering the mobility and fluctuating resource demands of the end users. Implementing our deep-learning-based response-time-prediction framework improves the performance of the computation offloading because it facilitates a prompt selection of the offloading location.

A Review for Mobile Commerce Research and Service

There is no doubt that the use of wireless andmobile networks and devices is growing. From the1990s onwards, we have been witnessing a great shift in methods of doing business with the emergence of the electronic commerce (e-commerce). Academics, businesses, and even individuals have been focusing on this new way of conducting business online. Advanced and mature wireless and mobile technologies facilitate e-commerce conducted from a wired network to a wireless network. Mobile commerce (m-commerce) can be viewed as a subset of e-commerce and refers to bany transaction with monetary value that is conducted via a mobile network .When users conduct e-commerce such as e-banking or purchase products, they do not need to use a personal computer system. Indeed, they can simply use some mobile handheld devices such as Personal Digital Assistants (PDA) and mobile phones to conduct various e-commerce activities. In the past, these mobile devices or technologies were regarded as a kind of luxury for individuals. However, this situation has changed. The market for mobile technologies has seen significant growth in the past few years. This is creating a new opportunity for the growth of m-commerce. According to a study conducted by Datamonitor, global m-commerc revenues will amount to $131.7 billion by 2017.

Design of Dual Band 5G Antenna Array with SAR Analysis for Future Mobile Handsets

This paper presents the design and specific absorption rate (SAR) analysis of the dual band antenna array for the future fifth generation (5G) mobile communication. The proposed antenna array operates in the Ka-band, at 28 and 38 GHz frequency bands. Roggers-5880 is used as a substrate having relative permittivity, thickness and loss tangent of 2.2, 0.254 mm and 0.0009 respectively in the proposed antenna array design. The main lobe gain of the single element 5G antenna is 7.71 and 7.73 dB at 28 and 38 GHz resonance frequencies correspondingly. As the gain requirement for 5G mobile communication system is 12 dB, thus 2 × 2 and 1 × 4 antenna arrays are designed to achieve the desired gain. The 2 × 2 antenna array yields a bore side gain of 12.3 and 15 dB, while 1 × 4 antenna array gives a bore side gain of 12.5 and 12.1 dB at 28 at 38 GHz frequency bands correspondingly. The dual band antenna (single element, antenna arrays) matched with a VSWR < 1.16 in the two frequency bands. All the simulations are carried out using computer simulation technology software. The SAR analysis averaged over 10 g of tissue of the proposed dual band 2 × 2 antenna array has been carried out on the head of human body using X-finite difference time domain electromagnetic simulation software, giving a safer limit of 0.37 and 1.34 W/kg < 2 W/kg according to the European IEC Standard at 28 and 38 GHz frequency bands correspondingly. The proposed antenna array is a suitable contender for the future 5G mobile handheld devices.

3D Object Manipulation Techniques in Handheld Mobile Augmented Reality Interface: A Review

Handheld mobile devices referring to mobile phones and tablets become the major output medium for augmented reality (AR), which have seen significant growth in popularity and usage among the public due to the growing release of consumer-oriented communication products nowadays, especially touchscreen smartphones. Unlike traditional desktop or tabletop AR (large display-based) and head-mounted display-based AR systems, small display-based AR (handheld mobile display) requires different interaction techniques that mostly utilize single-hand interaction as well as the limitation of small screen display and limited activity time due to the battery operation hour of handheld mobile devices. However, in handheld mobile AR, research is still lacking, especially research that focuses on 3D interaction in handheld mobile AR for virtual object manipulation. Thus, this paper provides an overview of 3D interaction techniques in handheld mobile AR with critical analysis. First, we describe three main interaction technique categories that applicable in handheld mobile AR, which is touch-based interaction, mid-air gestures-based interaction, and device-based interaction techniques, of their basic concepts on 3D object manipulation. Then, we classify and systematize the highlighted techniques and discuss the advantages and drawbacks of each. Previous studies for widely used techniques have been studied comprehensively. We then draw up a comparison among the different techniques based on the important elements considered in handheld mobile AR. The aim of this paper is to provide researchers with background information on AR and those who are interested in the field of 3D interaction, realizing each technique category.

Precise Target Selection Techniques in Handheld Augmented Reality Interfaces

Augmented reality (AR) capabilities on handheld mobile devices are increasing; therefore, interaction with a virtual scene is a key feature to explore the full potential of mobile AR. One of the primary interaction tasks is 3D target selection. Because touch screens provide a direct means of interaction with AR content by directly touching and manipulating AR elements, touch-based interaction is a natural and appealing style of input for AR applications. However, developing AR selection techniques for handheld devices using touch screens is not a straightforward task. One issue is that while interacting with AR targets, users occlude the targets with their fingers. Furthermore, because the user’s finger covers a large area of the screen, the size of the target users can touch is limited. In addition, in a 3D AR environment, it is difficult to select targets by touch when they are occluded from each other due to differences in spatial depth. In this paper, we present four novels AR selection techniques for handheld mobile devices that can precisely select targets with small sizes even when they are occluded. Then, we present the results of an experimental study in which we evaluated the usability, performance, and error rate of our proposed and existing AR selection techniques.

Energy Efficient Face Recognition in Mobile-Fog Environment

Proliferation in technological advancements has leveraged the evolution of cell-phones as powerful smart-phones with high computing competence. Integration of sensors and high definition camera has empowered the smart-phones as a tool to solve real world problems. Multiple applications of face recognition have been developed to address the security challenges using the computation power of handheld (mobile) devices. However, one important limitations of mobile devices is energy efficiency. This work has proposed an energy efficient fog-based face recognition using mobile platform. The architecture in proposed system initially performs the facial part detection on mobile device and uploads the selected part by discarding the rest. This reduces the network traffic and attempts to reduce energy consumption. Preliminary results have indicated a saving of approximately 93% of energy in mobile devices.

Catching All Pokémon: Virtual Reward Optimization With Tensor Voting Based Trajectory Privacy

The widespread adoption of mobile devices with global positioning system enables location-based games (LBGs) to use real world maps, while locations and objectives in LBGs can make the progression, achievements, and virtual rewards feel more palpable and entertaining. However, allowing location sharing in LBGs gives dishonest parties opportunities to learn users’ trajectories, which compromises the users’ privacy. In this paper, we propose a novel scheme jointly maximizing LBG players’ virtual rewards while preserving their trajectory privacy. Briefly, we first introduce a quantitative machine learning-based approach to model trajectory inference attacks via tensor voting. Then, to thwart this attack, we propose a tensor voting-based $k$ -anonymous obfuscation strategy. Considering the trajectory privacy concerns and power constraint of hand-held mobile devices, we mathematically formulate the LBG players’ virtual reward maximization optimization into the mixed integer problem and develop the feasible solutions. Simulation results and analysis show that the proposed scheme can effectively preserve LBG players’ trajectory privacy against tensor voting based inference attacks while maximizing LBG players’ virtual rewards.

Role of Habit and Value Perceptions on m-Learning Outcomes

ABSTRACT The significance of mobile devices in digital learning is growing fast as they allow users to have easier access to content materials and build engaging interactions with others. On the other hand, there exist concerns without enough systematic investigations that users may be distracted when using mobile devices for learning. Drawing upon the value-based adoption perspective in combination with habit, this study investigates m-learning dynamics using a survey method with 257 participants. The results showed that habit has a direct impact on utilitarian/hedonic values and m-learning continuance intention, but a distal influence on learning outcomes. The analysis of results by the mobile device types indicates differences in m-learning dynamics between users with handheld mobile devices and those with laptops. For handheld mobile device users, hedonic value has a greater impact on learning outcomes than utilitarian value does, while utilitarian value has more influence on learning outcomes for laptop users.

Post-disaster map builder: Crowdsensed digital pedestrian map construction of the disaster affected areas through smartphone based DTN

Constructing digital pedestrian maps of the disaster affected areas is a vital requirement for post-disaster relief operation. Digital maps help disaster management agencies in decision making and mobilizing the manpower and resources in the disaster affected areas. However, due to the intermittent connectivity after large scale natural disasters, the existing web based digital mapping systems remain inaccessible in the disaster affected areas. Moreover, the road networks in such areas change drastically because of disaster (for instance waterlogging due to flood, structural collapse or incidental destructions like a landslide). Hence, existing analog (paper based) route maps of such areas become obsolete. In this work, we propose Post-Disaster Map Builder, a crowdsenced digital pedestrian map construction system over smartphone based DTN. The proposed system generates digital pedestrian maps of the disaster affected areas using battery powered mobile handheld devices. Here, trajectory traces collected by the volunteers are periodically shared among the other volunteers of the disaster affected area through smartphone based DTN. Pedestrian maps of the disaster affected areas are gradually constructed in the mobile handheld devices of the volunteers by combining the collected traces over time. The proposed system is thoroughly evaluated through simulation and testbed implementation. The results reveal that our proposed system can automatically construct digital pedestrian maps of disaster affected areas with high accuracy at the cost of marginal delay.

Multi-Band Hybrid Mobile Phone Antenna Based on Electromagnetic Coupling

This research presents a multi-band hybrid mobile phone antenna based on electromagnetic coupling, which can be applied to mobile handheld devices, occupying a small board space of 39.7mm×15.6mm on the system circuit board. By adding resonant and coupled branch instead of multi-feed on the traditional bent antenna, this design provides four wide operating bands of 0.772—0.998 GHz, 1.540—1.600 GHz, 1.680—2.270 GHz and 2.300—2.690 GHz with the hybrid feature of planar inverted-F antenna (PIFA), L-shape, U-shape and S-shape structures, which cover nine-band, i.e., GSM850, GSM900, GPS1575, DCS1800, PCS1900, IMT200, LTE2300, LTE2600 and Blue Tooth/Wi-Fi. Ansoft software HFSS is used in this research to make the antenna performance better and the operating principle of the proposed antenna is described in detail. Result of simulation reveals that the maximum gains of these four wide bands are 2.20, −0.99, 4.01 and 4.05 dBi, respectively. Moreover, this research also tests the return loss (S11) of the fabricated antenna with the vector network analyzer and the result is in accordance with the simulation result on the whole. There are four wide resonant frequencies which cover nine-band of wireless wide area network (WWAN), wireless local area network (WLAN) and long term evolution (LTE), when the available bandwidth is better than 6 dBi return loss.

Developing hand-worn input and haptic support for real-world target finding

Locating places in cities is typically facilitated by handheld mobile devices, which draw the visual attention of the user on the screen of the device instead of the surroundings. In this research, we aim at strengthening the connection between people and their surroundings through enabling mid-air gestural interaction with real-world landmarks and delivering information through audio to retain users’ visual attention on the scene. Recent research on gesture-based and haptic techniques for such purposes has mainly considered handheld devices that eventually direct users’ attention back to the devices. We contribute a hand-worn, mid-air gestural interaction design with directional vibrotactile guidance for finding points of interest (POIs). Through three design iterations, we address aspects of (1) sensing technologies and the placement of actuators considering users’ instinctive postures, (2) the feasibility of finding and fetching information regarding landmarks without visual feedback, and (3) the benefits of such interaction in a tourist application. In a final evaluation, participants located POIs and fetched information by pointing and following directional guidance, thus realising a vision in which they found and experienced real-world landmarks while keeping their visual attention on the scene. The results show that the interaction technique has comparable performance to a visual baseline, enables high mobility, and facilitates keeping visual attention on the surroundings.

Enhancement of the antenna bandwidth by coupling the planar inverted‐F antenna and multi‐ultra‐thin slots for handheld devices with metal housing

AbstractWe propose an invisible multi‐ultra‐thin slot antenna and a planar inverted‐F antenna (PIFA) coupling design for handheld mobile devices in complete metal housing systems. To enhance the bandwidth of the traditional single λ/4 PIFA used in a 2.45‐GHz Wi‐Fi system and to consider the strong impact on radiation due to the metal‐housing shielding effect and position of the internal antenna, this design etches 0.1‐mm wide slots on the metal housing using PIFA to excite these slot antennas through coupling. The metal housing is a major radiator that enhances the antenna bandwidth and efficiency. It uses electric and magnetic coupling between the two antennas to achieve the specification bandwidth, and we design the number, gap, and position of slots by investigating the mutual coupling effect. The bandwidth of the proposed structure is 147 and 134 MHz in simulations and in measurements involving the etching of three multi‐ultra‐thin slots, respectively (L = 38 mm, W = 0.1 mm), for 2.45‐GHz usage. The results depict that this design enhances the antenna bandwidth when some slots are etched, especially for handheld devices with metal housing.