Dr. Rossel-Cid, Pedro

Software Product Lines allow creating a set of applications that share a set of common features. This makes software product lines appropriate for implementing a family of software products when each stakeholder has different needs and requirements evolve constantly. In the case of emergency management, firefighters have begun using their own smartphones to collaborate and access information during emergencies. However, each firefighter role requires different information and the firefighters’ requirements are constantly evolving. We propose a well-defined process to help stakeholders in this domain specify the products they require, showing that it is possible to apply this software engineering process to extract collaborative requirements common to a set of applications. To confirm whether it was useful for real software implementation, we defined and implemented two applications for this domain. This paper presents the process used to systematically define the domain model and determine the domain scope, which may be used for other domains. We found the process to be appropriate for identifying features related to the domain and its collaborative aspects. The results are promising; the process allowed us to create two working applications which were positively received by two types of stakeholders.

Smoking is the biggest avoidable health risk, causing millions of deaths per year worldwide. Persuasive applications are those designed to change a person’s behavior, usually in a specific way. Several mobile phone applications and messaging systems have been used to promote smoking cessation. However, most interventions use participants’ self-reports to track cigarette consumption and avoidance, which may not be accurate or objective. Previous proposals have used sensors to track hand movements and other contextual data to detect smoking or have used devices to detect smoke or breath carbon monoxide. This article proposes a low-cost wearable device that may be worn in a front shirt pocket or clipped to clothing to detect smoke and secondhand smoke. Furthermore, the device is integrated into a persuasive application to promote smoking cessation. The device was evaluated through an experiment to detect whether it may detect direct, passive, and no smoking conditions. The results are promising and may help improve tracking of cigarettes in persuasive applications.

Emotional information is complex to manage by humans and computers alike, so it is difficult for users to express emotional information through technology. Two main approaches are used to gather this type of information: objective (e.g. through sensors or facial recognition) and subjective (reports by users themselves). Subjective methods are less intrusive and may be more accurate, although users may fail to report their emotions or not be entirely truthful about them. The goal of this study is to identify trends in the area of interfaces for the self-report of human emotions, under-served populations of users, and avenues of future research. A systematic literature review was conducted on six search engines, resulting in a set of 863 papers, which were filtered in a systematic way until we established a corpus of 40 papers. We studied the technologies used for emotional self-report as well as the issues regarding these technologies, such as privacy, interaction mechanisms, and how they are evaluated.

Several initiatives have implemented collaborative applications for mobile settings as diverse as hospital work, wildlife, transportation, and museums. The changing nature of mobile technology has resulted in a wide variety of applications. We explored models, architectures, and applications developed in the past 13 years to categorize the types of existing software and extract a set of common core requirements that support mobile collaboration independently of the current technology. This paper provides an analysis of the domain of mobile collaborative systems including a proposal division into several domains of use, and a study of the types of systems that exist in each of them. In this way, developers can analyze their scenario of development to get an idea of the most important requirements that should be considered for development.

Background: Monitoring of patients may decrease treatment costs and improve quality of care. Pain is the most common health problem that people seek help for in hospitals. Therefore, monitoring patients with pain may have significant impact in improving treatment. Several studies have studied factors affecting pain; however, no previous study has reviewed the contextual information that a monitoring system may capture to characterize a patient’s situation. Objective: The objective of this study was to conduct a systematic review to (1) determine what types of technologies have been used to monitor adults with pain, and (2) construct a model of the context information that may be used to implement apps and devices aimed at monitoring adults with pain. Methods: A literature search (2005-2015) was conducted in electronic databases pertaining to medical and computer science literature (PubMed, Science Direct, ACM Digital Library, and IEEE Xplore) using a defined search string. Article selection was done through a process of removing duplicates, analyzing title and abstract, and then reviewing the full text of the article. Results: In the final analysis, 87 articles were included and 53 of them (61%) used technologies to collect contextual information. A total of 49 types of context information were found and a five-dimension (activity, identity, wellness, environment, physiological) model of context information to monitor adults with pain was proposed, expanding on a previous model. Most technological interfaces for pain monitoring were wearable, possibly because they can be used in more realistic contexts. Few studies focused on older adults, creating a relevant avenue of research on how to create devices for users that may have impaired cognitive skills or low digital literacy. Conclusions: The design of monitoring devices and interfaces for adults with pain must deal with the challenge of selecting relevant contextual information to understand the user’s situation, and not overburdening or inconveniencing users with information requests. A model of contextual information may be used by researchers to choose possible contextual information that may be monitored during studies on adults with pain.