Sensor Networks for Continuous Health Monitoring

Neild, I.; Heatley, David; Kalawsky, Roy S.; Bowman, P. A.

doi:10.1023/b:bttj.0000047127.01462.49

Cited by 24 publications

(11 citation statements)

References 3 publications

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“…This type of 'tradeoff' highlights the potential for H-IoT to simultaneously violate and enhance privacy. A tradeoff has been observed between personal privacy and safety, particularly among the mentally impaired patients (Ojasalo et al 2010;Stowe and Harding 2010;Landau et al 2010), as well as frail elderly (Melenhorst et al 2004;Courtney 2008;Courtney et al 2008;Steele et al 2009), and chronically ill persons (Salih et al 2011;Neild et al 2004). In these contexts, it has been stressed that personal privacy can be both protected by eliminating the need for in-person care (Ojasalo et al 2010;Essén 2008) and violated by the presence of a monitoring device (Melenhorst et al 2004;Steele et al 2009;Salih et al 2011).…”

Section: Personal Privacymentioning

confidence: 99%

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Ethics of the health-related internet of things: a narrative review

Mittelstadt

2017

Ethics Inf Technol

104

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Section: Personal Privacymentioning

confidence: 99%

“…This is particularly important for cognitively impaired users unable to grant consent (Kenner 2008;Bowes et al 2012). These concerns can extend to guests of a monitored individual, which suggests the possibility of inadvertent monitoring (Neild et al 2004). …”

Section: Obtrusiveness Stigma and Autonomymentioning

confidence: 99%

Ethics of the health-related internet of things: a narrative review

Mittelstadt

2017

Ethics Inf Technol

104

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“…16 and IEEE802.20 that can cover much greater distances with better quality-of-service (QoS) support than Wi-Fi. IEEE802.16, more commonly known as WiMAX, is a wireless metropolitan area network (WirelessMAN) technology that can provide backhaul connection to WLAN hotspots.…”

Section: Pervasive Communicationsmentioning

confidence: 99%

Wireless technologies for telemedicine

Ng¹,

Sim²,

Tan³

et al. 2006

BT Technol J

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Wireless telemedicine is a new and evolving area in telemedical and telecare systems. Healthcare personnel require realtime access to accurate patient data, including clinical histories, treatments, medication, tests, laboratory results and insurance information. With large-scale wireless networks and mobile computing solutions, such as cellular 3G, Wi-Fi mesh and WiMAX, healthcare personnal can tap into vital information anywhere and at any time within the healthcare networks. The recent introduction of pervasive computing, consisting of radio frequency identification (RFID), Bluetooth, ZigBee, and wireless sensor networks, further extends the potential for exploitation of wireless telecommunications and its integration into new mobile healthcare delivery systems.In this paper, snapshots of current uses and future trends of various wireless communications in the healthcare domain are highlighted. Special attention is given to the challenges of a telemedicine environment equipped with different wireless technologies and how the resulting issues might be addressed in medical services integration to provide flexible, convenient and economical medical monitoring, consultation and healthcare.

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“…The sensor network employed in this project included [9] • passive infrared (PIR) sensors to pick up occurrences of movement in various rooms, • toggle switch sensors to detect when windows, entrances, and cupboard / kitchen appliance doors are opened • vibration and temperature sensors to detect use of water • pressure sensors to indicate occupation of chairs and bed Although this provided a very restricted dataset consisting of few specific details about household events, plenty of information could still be inferred as to the general level of activity within the home, and the changing location of the client. This made it possible to determine the state of a number of activities of daily living.…”

Section: Sensor Networkmentioning

confidence: 99%

Fuzzy Ambient Intelligence for Next Generation Telecare

Martin

Majeed²,

Lee³

et al. 2006

2006 IEEE International Conference on Fuzzy Systems

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Third generation telecare involves a customised sensor network, able to detect a person's movements and use of furniture and household items, coupled with a sophisticated fuzzy data analysis process able to answer high level queries such as "is the person eating regularly". Soft computing techniques are needed due to the high degree of uncertainty in the inference process. We describe a trial system, which has been installed in two homes. Results indicate that fuzzy analysis enables us to summarise the data in a manner which is useful to the care providers without them needing to be experts in data analysis.

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Sensor Networks for Continuous Health Monitoring

Cited by 24 publications

References 3 publications

Ethics of the health-related internet of things: a narrative review

Ethics of the health-related internet of things: a narrative review

Wireless technologies for telemedicine

Fuzzy Ambient Intelligence for Next Generation Telecare

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