Monitoring technology
Klonovs, Juris ; Haque, Mohammad A. ; Krueger, Volker LU
; Nasrollahi, Kamal
; Andersen-Ranberg, Karen
; Moeslund, Thomas B.
and Spaich, Erika G.
(2016)
In SpringerBriefs in Computer Science
p.49-84
- Abstract
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... (More)
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.
(Less)
- author
- Klonovs, Juris
; Haque, Mohammad A.
; Krueger, Volker
LU
; Nasrollahi, Kamal
; Andersen-Ranberg, Karen
; Moeslund, Thomas B.
and Spaich, Erika G.
- publishing date
- 2016-01-01
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Activity monitoring, Activity of daily living (ADL), Machine learning, Monitoring technology, Patient at home, Physiological parameter, Remote sensing, Sensor, Standards, Wearable
- host publication
- SpringerBriefs in Computer Science
- series title
- SpringerBriefs in Computer Science
- issue
- 9783319270234
- edition
- 9783319270234
- pages
- 36 pages
- publisher
- Springer
- external identifiers
-
- scopus:85012270700
- ISSN
- 2191-5776
- 2191-5768
- DOI
- 10.1007/978-3-319-27024-1_4
- language
- English
- LU publication?
- no
- id
- 6a48da54-bbf2-4af1-8041-2edd79cd552c
- date added to LUP
- 2019-06-28 09:18:46
- date last changed
- 2024-01-16 04:58:13
@inbook{6a48da54-bbf2-4af1-8041-2edd79cd552c,
abstract = {{<p>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.</p>}},
author = {{Klonovs, Juris and Haque, Mohammad A. and Krueger, Volker and Nasrollahi, Kamal and Andersen-Ranberg, Karen and Moeslund, Thomas B. and Spaich, Erika G.}},
booktitle = {{SpringerBriefs in Computer Science}},
issn = {{2191-5776}},
keywords = {{Activity monitoring; Activity of daily living (ADL); Machine learning; Monitoring technology; Patient at home; Physiological parameter; Remote sensing; Sensor; Standards; Wearable}},
language = {{eng}},
month = {{01}},
number = {{9783319270234}},
pages = {{49--84}},
publisher = {{Springer}},
series = {{SpringerBriefs in Computer Science}},
title = {{Monitoring technology}},
url = {{http://dx.doi.org/10.1007/978-3-319-27024-1_4}},
doi = {{10.1007/978-3-319-27024-1_4}},
year = {{2016}},
}