This chapter aims at giving an insight into a variety of available monitoring technologies and techniques, which aim to provide solutions to the issues listed in Chap. 3. First, we start with discussing possible data collection approaches, by revealing choices of available sensors and underlying constrains. Second, we provide a summary of sensors used for data acquisition in regard to needed medical applications, revealing what relevant parameters can be derived from those sensor measurements. We then summarize what common data processing and analysis techniques are used for interpreting this data, with a special focus on machine learning approaches. Third, we derive important requirements and underlying challenges for the involved machine learning strategies and discuss possible implications for applying the different monitoring approaches. Finally, we refer to a number of established standards, which are needed to be complied with, when developing and implementing home monitoring systems for older adults.

Original languageEnglish
Title of host publicationDistributed Computing and Monitoring Technologies for Older Patients
Number of pages36
PublisherSpringer VS
Publication date1 Jan 2016
ISBN (Print)978-3-319-27023-4
ISBN (Electronic)978-3-319-27024-1
Publication statusPublished - 1 Jan 2016
SeriesSpringerBriefs in Computer Science


  • Activity monitoring
  • Activity of daily living (ADL)
  • Machine learning
  • Monitoring technology
  • Patient at home
  • Physiological parameter
  • Remote sensing
  • Sensor
  • Standards
  • Wearable


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