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Ambient intelligence for health: advances in vital signs and gait monitoring systems within mHealth environments

Ambient intelligence for health: advances in vital signs and gait monitoring systems within mHealth environments

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This chapter presents an overview about the application of Ambient Intelligence to Healthcare environments, and how the current use of mobile devices provides new opportunities and determines new research areas such as mHealth, focused on the use of mobile technologies to improve people quality life getting clinical benefits. In this sense, monitoring is an important branch today in which researchers are working. There are many systems to monitor several factors regarding health. In our case, three kinds of monitoring systems are detailed. The first approach describes a framework-based system to monitor several diseases like diabetes taking into account the most common factors. In the second case, we present the importance of long-term gait monitoring to detect frailty symptoms in early stages by developing software system and hardware infrastructures based on a variety of sensors. Finally, we detail an analysis tool to measure the level of performance of Instrumental Activities of Daily Living (IADL) of elderly people at home. Likewise, this tool provides some functionalities to assess level stress and quality of life of caregivers by conducting questionnaires. Besides the description of the systems, we detail the evaluations carried out in each. We show the results according to system characteristics, usability, functionality and deployment of features among others.

Chapter Contents:

  • Abstract
  • 9.1 Introduction
  • 9.2 From ambient intelligence to mHealth
  • 9.3 mHealth
  • 9.3.1 Mobile monitoring
  • 9.4 Vital signs, gait and everyday activities monitoring: experimental applications and study cases
  • 9.4.1 Frameworks and mobile systems for chronic and non-chronic diseases
  • 9.4.1.1 Description of the system
  • 9.4.1.2 Evaluation and results
  • 9.4.2 Long-term gait monitoring as a tool to understand the motor control of gait
  • 9.4.2.1 Description of the systems
  • 9.4.2.2 Evaluation and results
  • 9.4.3 Analysis tools for monitoring
  • 9.4.3.1 Description of the system
  • 9.4.3.2 Evaluation and results
  • 9.5 Conclusions
  • Acknowledgements
  • References

Inspec keywords: medical computing; patient monitoring; health care; gait analysis; geriatrics; mobile computing; ambient intelligence; diseases; sensors

Other keywords: mHealth environments; mobile technologies; Instrumental Activities of Daily Living; health care environments; diabetes; vital signs; IADL; disease; sensors; gait monitoring systems; elderly people; ambient intelligence; mobile devices

Subjects: Sensing and detecting devices; Biomedical measurement and imaging; Ubiquitous and pervasive computing; Biology and medical computing; Physics of body movements; Sensing devices and transducers; Biomedical engineering

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