A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation

Jovanov, Emil; Milenkovic, Aleksandar; Otto, Chris; Groen, Piet C. de

doi:10.1186/1743-0003-2-6

Cited by 717 publications

(137 citation statements)

References 22 publications

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“…Extensive experimentation was conducted to ensure that this body sensors configuration provided sufficient data towards classification of the set of positions needed for the application at hand. It should be noted here that, for differentiating accurately the standing and walking posture, ankle sensors coupled with hip sensors are suggested to produce best classification performance [35]. This approach could not be adopted here as one of the implementation aims is to not only minimize the number of body worn sensors (to conform with user requirements and increase wearability) but also to have the inertial sensors mounted in the same locations as the temperature sensors in the over-arching instrument (hence, the dual role of the board in figure 3, which hosts temperature sensors as well).…”

Section: Methodsmentioning

confidence: 99%

Postural activity monitoring for increasing safety in bomb disposal missions

Brusey¹,

Rednic²,

Gaura³

et al. 2009

Meas. Sci. Technol.

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In enclosed suits, such as those worn by explosive ordnance disposal (EOD) experts, evaporative cooling through perspiration is less effective and, particularly in hot environments, uncompensable heat stress (UHS) may occur. Although some suits have cooling systems, their effectiveness during missions is dependent on the operative's posture. In order to properly assess thermal state, temperature-based assessment systems need to take posture into account. This paper builds on previous work for instrumenting EOD suits with regard to temperature monitoring and proposes to also monitor operative posture with MEMS accelerometers. Posture is a key factor in predicting how body temperature will change and is therefore important in providing local or remote warning of the onset of UHS. In this work, the C4.5 decision tree algorithm is used to produce an on-line classifier that can differentiate between nine key postures from current acceleration readings. Additional features that summarize how acceleration is changing over time are used to improve average classification accuracy to around 97.2%. Without such temporal feature extraction, dynamic postures are difficult to classify accurately. Experimental results show that training over a variety of subjects, and in particular, mixing gender, improves results on unseen subjects. The main advantages of the on-line posture classification system described here are that it is accurate, does not require integration of acceleration over time, and is computationally lightweight, allowing it to be easily supported on wearable microprocessors.

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Section: Methodsmentioning

confidence: 99%

Postural activity monitoring for increasing safety in bomb disposal missions

Brusey¹,

Rednic²,

Gaura³

et al. 2009

Meas. Sci. Technol.

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“…Some key uses of smartphones are shown in Figure 7. Several platforms have been proposed to provide easy to use and cost effective solutions for remote patient doctor interaction over a cellular network [21,22]. Moreover, several specifications have been put forth to conceptualize patient data management for hospitals and other type of health care facilities [23][24][25].…”

Section: Mhealthmentioning

confidence: 99%

Prospects for Mobile Health in Pakistan and Other Developing Countries

Burney¹,

Abbas²,

Mahmood³

et al. 2013

AIT

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Pakistan is a developing country with more than half of its population located in rural areas. These areas neither have sufficient health care facilities nor a strong infrastructure that can address the health needs of the people. The expansion of Information and Communication Technology (ICT) around the globe has set up an unprecedented opportunity for delivery of healthcare facilities and infrastructure in these rural areas of Pakistan as well as in other developing countries. Mobile Health (mHealth)-the provision of health care services through mobile telephony-will revolutionize the way health care is delivered. From messaging campaigns to remote monitoring, mobile technology will impact every aspect of health systems. This paper highlights the growth of ICT sector and status of health care facilities in the developing countries, and explores prospects of mHealth as a transformer for health systems and service delivery especially in the remote rural areas.

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“…Administration of insulin for diabetics would be an example of something that the actuators could control. (Jovanov, 2005) lists some of the specific sensors that could be used in their version of a wireless BAN such as:…”

Section: Sensors and Actuatorsmentioning

confidence: 99%