1,721,013 research outputs found
Sociability Issues for Designing Usable Mobile iTV Applications
No full textThe adoption of mobile iTV will depend not just fromthe availability of suitable technologies but mainly fromthe limitations related to its use. As for many otherexamples of personal communications technologies,several issues related to the appropriateness of use indifferent social contexts will have an important impactin users’ acceptance of this technology. In this paperwe present three mobile iTV scenarios that highlightsome of the most relevant relationships between tasks,devices, interfaces and the environment that may affectand be affected by sociability. Some findings aboutthese relationships will be described to outline how theymay influence designers to create more usable mobileiTV applications
Detecting dressing failures using temporal–relational visual grammars
Full text linkEvaluation of dressing activities is essential in the assessment of the performance of patients with psycho-motor impairments. However, the current practice of monitoring dressing activity (performed by the patients in front of the therapist) has a number of disadvantages when considering the personal nature of dressing activity as well as inconsistencies between the recorded performance of the activity and performance of the same activity carried out in the patients’ natural environment, such as their home. As such, a system that can evaluate dressing activities automatically and objectively would alleviate some of these issues. However, a number of challenges arise, including difficulties in correctly identifying garments, their position in the body (partially of fully worn) and their position in relation to other garments. To address these challenges, we have developed a novel method based on visual grammars to automatically detect dressing failures and explain the type of failure. Our method is based on the analysis of image sequences of dressing activities and only requires availability of a video recording device. The analysis relies on a novel technique which we call temporal–relational visual grammar; it can reliably recognize temporal dressing failures, while also detecting spatial and relational failures. Our method achieves 91% precision in detecting dressing failures performed by 11 subjects. We explain these results and discuss the challenges encountered during this work
Indoor Positioning Using FM Radio
Full text linkThis paper presents an indoor positioning system based on FM radio. The system is built on commercially available short-range FM transmitters. This is the first experimental study of FM performance for indoor localisation. FM radio possesses a number of features, which make it distinct from other localisation technologies. Despite the low cost and off-the-shelf components, this FM positioning system reaches a high performance, comparable to other positioning technologies such as Wi-Fi. The authors’ experiments have yielded a median accuracy of 1.0 m and in 95% of cases the error is below 5 m.</p
Automatic Sensing of Speech Activity and Correlation with Mood Changes
Full text linkhe association between social relationships and psychological health has been established fairly recently, in the last 30-40 years, relying on survey-based methods to record past activities and the psychological responses in individuals. However, using the self-reporting methods for capturing social behavior exhibits a number of shortcomings including recall bias, memory dependence, and a high end user effort for a continuous long-term monitoring. In contrast, automated sensing techniques for monitoring social activity, and in general, human behavior, has a potential to provide more objective measurements thus to overcome the shortcomings of self-reporting methods. In this paper, we present a privacy preserving approach to detect one component of social interactions - the speech activity, through the use of off-the-shelf accelerometers. Furthermore, we used the accelerometer based speech detection method to investigate the correlation between the amount of speech (which is an aspect that reflects the participation in verbal social interactions) and mood changes. Our pilot study suggested that verbal interactions are an important factor that has an impact on individuals’ mood, while the study also demonstrated the potential of automated capturing social activity comparable to the use of gold standard surveys
Investigation of indoor localization with ambient FM radio stations
Full text linkLocalization plays an essential role in many ubiquitous computing applications. While the outdoor location-aware services based on GPS are becoming increasingly popular, their proliferation to indoor environments is limited due to the lack of widely available indoor localization systems. The de-facto standard for indoor positioning is based on Wi-Fi and while other localization alternatives exist, they either require expensive hardware or provide a low accuracy. This paper presents an investigation into localization system that leverages signals of broadcasting FM radio stations. The FM stations provide a worldwide coverage, while FM tuners are readily available in many mobile devices. The experimental results show that FM radio can be used for indoor localization, while providing longer battery life than Wi-Fi, making FM an alternative to consider for positioning
RFID-Based System for Tracking People: Approaches to Tagging Demented Patients
No full textRFID technology has proven to be an effective solution in many applications for monitoring demented patients. However, its wider acceptance is still limited by prohibitive deployment costs, technological limitations and privacy concerns. In this paper, an RFID-based indoor tracking system was analyzed regarding an additional barrier of RFID’s acceptance which is an issue of choosing an appropriate strategy for tagging patients. This includes making the trade-off between technological constraints, healthcare staff’s routines and the fact that patients with dementia may tend to remove foreign objects
Speech activity detection using accelerometer
Full text linkThe level of social activity is linked to the overall wellbeing and to various disorders, including stress. In this regard, a myriad of automatic solutions for monitoring social interactions have been proposed, usually including audio data analysis. Such approaches often face legal and ethical issues and they may also raise privacy concerns in monitored subjects thus affecting their natural behaviour. In this paper we present an accelerometer-based speech detection which does not require capturing sensitive data while being an easily applicable and a cost-effective solution
Challenges and opportunities in evolving TreC personal health record platform
No full textElectronic Health Records (EHR) have been one of the factors in transforming healthcare and health management by providing electronic access to information recorded on paper charts. However, increasing interest of patients to be actively involved in the management of their condition and their health has necessitated evolution of EHRs so as to accommodate patients' role in the care loop. In response, Personal Health Records (PHR) have been developed that are patient-facing and provide the possibility to enrich EHRs data using data sources that have not been considered in the traditional healthcare, either due to unavailability or difficulty in acquiring data. An example of PHR is TreC platform, designed and validated by our research group. We provide an overview of TreC PHR, describe the challenges and provide an outlook on future opportunities
Virtual uniforms
Full text linkIn this paper, we present the concept of grouping individuals and detecting their proximity by emitting/receiving inaudible tones using their mobile phones. The inspiration stems from uniforms metaphor (of different colors) that groups subjects based on the roles, occupations or teams. The goal is to get an insight into the social context and social interaction patterns
Indoor Localization Using Audio Features of FM Radio Signals
Full text linkTypical localization systems use various features of the signal to estimate the distance, including received signal strength indicator (RSSI), timing information or angle of arrival (AoA). However, there are a number of signal features of FM radio that may also be suitable for localization, namely stereo channel separation (SCS) and signal to noise ratio (SNR). This paper investigates the feasibility of indoor localization using fingerprinting of audio features of FM radio signals emitted by low-power FM transmitters using SNR and SCS values. The experimental results demonstrate the possibility of audio-based localization, when signal strength readings are not available
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