Name
Abstract | ||
|---|---|---|
The World Health Organization predicts that by 2020, depression will be the second-most common cause of debility. Also, ubiquitous computing advances are offering people and applications the necessary information for the most diversified necessities. In this sense, researchers are using ubiquitous health in applications focused on mental health and well-being. This article proposes Higia, a model to assist in the treatment of people suffering from depression. Higia detects the need to contact the caregivers of a depressed person, based on the users' historical context, allowing a faster response action. Higia constantly evaluates patients' characteristics on social networks, emails, and interactions with smartphones, computers, or other devices. Higia also proposes the monitoring of users' displacements. A prototype was developed and applied in an evaluation involving users and psychologists. The results showed 85.7% of acceptance regarding perceived ease of use by users and that 100% agree, partially or totally, about the system utility. These results were encouraging and show the potential for implementing Higia in real-life situations. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s10209-019-00697-4 | UNIVERSAL ACCESS IN THE INFORMATION SOCIETY |
Keywords | DocType | Volume |
Depression,Tracking system,Medical ontology,Intelligent agents | Journal | 19.0 |
Issue | ISSN | Citations |
4.0 | 1615-5289 | 1 |
PageRank | References | Authors |
0.35 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Milene Martini Petry | 1 | 1 | 0.35 |
| Jorge Luis Victória Barbosa | 2 | 73 | 29.37 |
| Sandro Rigo | 3 | 185 | 24.91 |
| Lucas Pfeiffer Salomão Dias | 4 | 1 | 0.35 |
| Paulo César Büttenbender | 5 | 1 | 0.35 |