As the population ages, prediction of falls risk is becoming an increasingly important research area. Due to built-in inertial sensors and ubiquity, smartphones provide an at- tractive data collection and computing platform for falls risk prediction and continuous gait monitoring. One challenge in continuous gait monitoring is that signi cant signal variability exists between individuals with a high falls risk and those with low-risk. This variability increases the di cultly in building a universal system which segments and labels changes in signal state. This paper presents a method which uses unsu- pervised learning techniques to automatically segment a gait signal by computing the dissimilarity between two consecutive windows of data, applying an adaptive threshold algorithm to detect changes in signal state, and using a rule-based gait recognition al- gorithm to label the data. Using inertial data,the segmentation algorithm is compared against manually segmented data and is capable of achieving recognition rates greater than 71.8%.

This diploma thesis deals with comparison of insurance companies and insurance groups and their mobile applications for non-life insurance. Part of diploma thesis is survey between users of smartphones and mobile applications. Another part is interview with experts connected with mobile applications of insurance companies. Based on acquired data and information is developed set of steps useful for effective marketing for any mobile application for non-life insurance, especially for Pojišťovna application. The diploma thesis includes tables, pictures and graphics processing data.

This master's thesis aims to develop a mobile application for the Google Android operating system based on customer requirements. Applications should serve to showcase customer's products, view calendar of courses and to let user book chosen course term. The work begins with research of a few chosen books focused on developing applications for Android and then client requirements are defined. Based on the results of research and defined customer requirements, detailed application specifications are laid down. Then there is presented architecture of whole application. The work ends with a pair of manuals. The first one is intended to the application administrator, whom it will serve during modifying and updating data. The second one is for user, whom it will assist during the process of application installation to the device and to introduce its control methods. The installation file of developed application is in the appendixes of this work.

BACKGROUND: The COVID-19 pandemic has increased the demand for mental health services but has also imposed new barriers for those seeking care, creating a widespread shortage. As a result, providers are increasingly looking to incorporate technology into mental healthcare. Despite the increased focus on mental health technology in recent years, many new technologies are framed as products rather than clinical tools and fail to be effectively implemented. Digital clinics, hybrids of clinical care and technology, such as a smartphone app, offer a model of how technology can be implemented into mental healthcare. In addition to increasing the need for technology in mental healthcare, the COVID-19 pandemic has also lessened many historical barriers to successful implementation of a digital clinic including regularity restrictions, financial challenges, and the motivations of patients and providers in adding technology into healthcare. Objective: In order to better understand how technology can be incorporated into mental healthcare, the Technology Enabled Care Program (TECC), a digital clinic at Beth Israel Deaconess Medical Center, will be evaluated through the study of a case series. The integrated-Promoting Action on Research Implementation in Health Services (i-PARISH) framework, an implementation science model, will be applied to TECC in order to identify factors important to the larger scale implementation of this digital clinic. METHODS: The TECC program combines eight sessions of face-to-face therapy via telehealth with the use of a mindLAMP, a mental health smartphone app. The app is customizable for each use case and is supported by a 3-member care team containing technology specialists and a therapist. Quantitative data from this program will be investigated and discussed along with information on patients’ qualitative experiences in order to get a better understanding of the successes and areas for improvement in this first implementation of TECC. RESULTS: From the six initial patients who have completed TECC, four were selected to be represented in this case series. One patient was highly engaged with the app and used it on a daily basis throughout the program. Two patients use the app consistently at times but experienced periods of low engagement during their care. A fourth patient struggled with technical issues and their app use was intermittent. Most feedback on the program was positive, but exceptions will be detailed. CONCLUSION: Implementation of the TECC program and mindLAMP app into practice was successful in many regards and these early cases shed light on areas of potential improvement in future iterations of the digital clinic. Moving forward, these results will inform a focus on factors that can increase adoption by patients, clinicians, and healthcare systems.

BACKGROUND: As smartphone devices have become a ubiquitous part of our modern lives, parents and clinicians have become increasingly concerned about the effects of digital media use on the mental well-being of adolescents and young adults. Smartphone ownership in youth has increased significantly over the last decade, paralleling the rise in mental health disorders. This study seeks to use the digital phenotyping (DP) methodology to elucidate these relationships. Most studies examining these variables use cross-sectional data in healthy adolescents. To our knowledge, no studies have used DP methodology to characterize the relationship between digital media use, depression and anxiety in a population of clinical adolescents. METHODS: 50 adolescent and young adults between the ages of 12-23 receiving outpatient mental health services from a community hospital network in the greater Boston area were enrolled. Participants installed an application on their personal smartphones that collected daily surveys that captured mood symptoms, digital media use (screen time, social media time, and top apps used [active data]), and that also continuously captured sensor data (GPS and accelerometer [passive data]) over six weeks. RESULTS: Using linear regression and multilevel modeling, no significant associations were found between screen time or social media time, and anxiety and depression symptoms. Productivity apps were used significantly more in those with no depression symptoms than in those with moderate to severe levels of depression. CONCLUSION: Our study results challenge the present intuition that the amount of digital media use negatively impacts mental well-being in youth. Total screen time and social media time measures may be insufficient when attempting to assess the impact of digital media engagement on youth. Additionally, the results of our study suggest that the types of apps used by youth may depend on an individual’s mood severity. Although not without limitations, DP studies may be the ideal methodology for capturing with greater granularity digital use behavior and its association with mood symptoms in adolescents. / 2022-11-22T00:00:00Z

This thesis focuses on developement of mobile app for cross country skiiers. It follows, step by step, the process of developement; starting with analysis, through design, up to premises of future developement. The app is being developed for iOS platform. The thesis also discusses proposed means of monetization.

Smartphone adoption is occurring at an exponential rate with a user base far exceeding that of traditional mobile phones. Previous literature has identified various points of usage across demographics such as age, gender, income and nationality, however little of this is with regards to Smartphone attributes. Furthermore, generational change has provided a gravitational shift in the application of marketing techniques, as Generation-Y is a generation unlike any other, where traditional techniques are more hit and miss than targeted. A deeper understanding as to how antecedent decision-making is performed via the influence of Smartphone attributes upon Generation-Y’s choice of those phones is required. This research assists in the filling of these gaps by presenting findings in a holistic view of Generation-Y’s Smartphone attribute preferences as well as perceptions among South African business users. This paper seeks to add insight by unpacking the needs of the Generation that will soon be the largest consumer group in history - Generation-Y. Self Explicated Conjoint Analysis provides insights into attribute ranking and level of influence of specific attributes. Factor analysis extracts the salient factors of influence by Generation-Y consumers when choosing a Smartphone. Further to this, managerial implications, future work and limitations of this study for theory and practice are presented. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

Smartphone's are extremely popular and in high demand nowadays. They are easy to handle and very intuitive compared with old phones for end users. Approximately two billion people use Smartphones all over the world, so it is clear that these phones are very popular. One of the major issues of these smart phones is theft. What happens if someone steals your phone? Why should we try to secure our phones? The reason is that, even if the phone is stolen, the thief should not be able to open and use it through unlocking easily. People are generally careless while typing their password/pin code or drawing a pattern while others are watching. Maybe someone can see it just by standing next to or behind the person who is typing the pin or drawing the pattern. This scenario of getting the information is called shoulder surfing. Another scenario is to use a hidden camera, so-called Record monitoring. Shoulder surfing can be used by an attacker/observer to get passwords or PINs. Shoulder surfing is very easy to perform by just looking over the shoulder when a user is typing the PIN or drawing the unlock pattern. Record monitoring needs more preparation, but is not much more complicated to perform. Sometimes it also happens that the phone gets stolen and by seeing fingerprints or smudge patterns on the phone, the attacker can unlock it. These above two are general security threats for smart phone users. This thesis introduces some different approaches to overcome the above mentioned security threats in Smartphones. The basic aim is to make it more difficult to perform shoulder surfing or record monitoring, and these will not be easy to perform by the observer after switching to the new techniques introduced in the thesis. In this thesis, the usability of each method developed will be described and also future use of these approaches. There are a number of techniques by which a user can protect the phone from observation attacks. Some of these will be considered, and a user interface evaluation will be performed in the later phase of development. I will also consider some important aspects while developing the methods such as -user friendliness, Good UI concepts etc. I will also evaluate the actual security added by the methods, and the overall user impression. Two separate user studies have been performed, first one with students from the Computer Science department, and then one with students from other departments. The results indicate that students from Computer Science are more attracted to the new security solution than students from other departments.

Uppsatsen grundar sig i nyfikenheten kring hur smarttelefoner och sociala medier påverkar individens sociala interaktion. Uppsatsen fördjupar sig i individens personliga upplevelser av det hybridiserade rummet, samt studerar smarttelefoner och sociala mediers konflikt och samverkan med ansikte-mot-ansikte interaktioner i det fysiska rummet. Arbetet avgränsar sig till studenter vid Uppsala Universitet och använder sig av en kvalitativ metod för att besvara syftet; undersöka hur smarttelefoner och sociala medier påverkar individers sociala interaktion. Uppsatsens resultat och analys visar att smarttelefoner konkurrerar med det fysiska rummet om individens uppmärksamhet som i sin tur påverkar sociala ansikte-mot-ansikte interaktioner. Det är en följd av att individen skapat ett behov av kontroll av smarttelefonen och bär med sig den vart man än går, smarttelefonen blir en del av kroppens rörelsemönster i det fysiska rummet. Smarttelefonanvändning har lett till minskade fysiska möten samtidigt som behovet av fysiska möten inte minskats. Individens inställning till smarttelefonanvändning beror således på om individen är ensam i det fysiska rummet eller i sällskap av vänner. Mindre fördelaktigt med smarttelefonanvändning sägs utifrån resultatet vara i sammanhang med vänner, där smarttelefonen förflyttar individen rent sinnesmässigt till ett annat rum och drabbar den sociala ansikte-mot-ansikte interaktionen.

Work in demanding postures is a known risk factor for work-related musculoskeletal disorders (MSDs), specifically work with elevated arms may cause neck/shoulder disorders. Such a disorder is a tragedy for the individual, and costly for society. Technical measurements are more precise in estimating the work exposure, than observation and self-reports, and there is a need for uncomplicated methods for risk assessments. The aim of this project was to develop and validate an iOS application for measuring arm elevation angle. Such an application was developed, based on the built-in accelerometer and gyroscope of the iPhone/iPod Touch. The application was designed to be self-exploratory. Directly after a measurement, 10th, 50th and 90th percentiles of angular distribution and median angular velocity, and percentage of time above 30°, 60°, and 90° are presented. The focused user group, ergonomists, was consulted during the user interface design phase. Complete angular datasets may be exported via email as text files for further analyses. The application was validated by comparison to the output of an optical motion capture system for four subjects. The two methods correlated above 0.99, with absolute error below 4.8° in arm flexion and abduction positions. During arm swing movements, the average root-mean-square differences (RMSDs) were 3.7°, 4.6° and 6.5° for slow (0.1 Hz), medium (0.4 Hz) and fast (0.8 Hz) arm swings, respectively. For simulated painting, the mean RMSDs was 5.5°. Since the accuracy was similar to other tested field research methods, this convenient and “low-cost” application should be useful for ergonomists, for risk assessments or educational use. The plan is to publish this iOS application on Apple Store (Apple Inc.) for free. New user feedback may further improve the user interface.