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handle: 11343/272728
The articles in this special section focus on personalized pervasive health. For over more than two decades, mobile, wearable, and ambient sensor and interaction devices have grown into today’s plethora of computing platforms and tools for pervasive health. Pervasive computing is now assimilating into medicine, from disease risk prevention to diagnostics, and from treatment support to chronic-care management. Unlike more traditional medical lab technology, pervasive computing systems can be continuously available, using unobtrusive sensors, actuators, computing, and interactive interfaces to liberalize access to information on basic body functions and processes in everyday life, e.g., physical activity and vital signs. Pervasive computing platforms now natively provide practitioners and researchers with a set of functionalities that allow for the development of applications and systems that are able to make sense of complex situations, e.g., daily routines, mood, and the user’s physiology. With this potential at hand, pervasive computing systems will play a central role as enabling technology for healthcare.
Computational Theory and Mathematics, 025, Software, 004, Computer Science Applications
Computational Theory and Mathematics, 025, Software, 004, Computer Science Applications
| 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). | 10 | |
| 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. | Top 10% | |
| 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. | Top 10% |
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