Downloads provided by UsageCounts
The aim of this chapter is to provide an overview of the concepts of electronic and mobile health and the application of the Internet of Things in healthcare. A model of mobile health which is based on wearable computing in the area of stress management and disease prevention has been proposed. Model consists of system that enables measurement of vital and environmental parameters in order to reduce stress and, thus, improve health. As a form of support to the wearable system, a mobile health application for well-being was developed, featuring relaxation content. The aim of case study is to identify the psychophysiological signals indicating stress during students’ term papers defending. Existence of differences between the measured values using the wearable system before, during and after the defense of student’s term papers points to stress or arousal during test. Mobile health application for the purpose of relaxation should minimize the excitement and impact on reducing stress during tests. The results of the case study indicate that mobile health application for well-being with features for relaxation can reduce stress when defending term papers, as well as a decrease in anxiety over the duration of the test and during the relaxation period after the test.
Internet of Things, Sensors, Wearables, eHealth, mHealth, Health, Multi-sensor Platforms, Stress management, Well-being, Mobile health application
Internet of Things, Sensors, Wearables, eHealth, mHealth, Health, Multi-sensor Platforms, Stress management, Well-being, Mobile health application
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 4 | |
| downloads | 7 |

Views provided by UsageCounts
Downloads provided by UsageCounts