37,902 research outputs found
Vision analysis in detecting abnormal breathing activity in application to diagnosis of obstructive sleep apnoea
Recognizing abnormal breathing activity from
body movement is a challenging task in machine vision. In this paper, we present a non-intrusive automatic video monitoring technique for detecting abnormal breathing activities and assisting in diagnosis of obstructive sleep apnoea. The proposed technique utilizes infrared video information and avoids imposing geometric or positional constraints on the patient. The technique also deals with fully or partially obscured patients’ body. A continuously updated breathing activity template is built
for distinguishing general body movement from breathing
behavior
Sleeping on a problem: the impact of sleep disturbance on intensive care patients - a clinical review
Sleep disturbance is commonly encountered amongst intensive care patients and has significant psychophysiological effects, which protract recovery and increases mortality. Bio-physiological monitoring of intensive care patients reveal alterations in sleep architecture, with reduced sleep quality and continuity. The etiological causes of sleep disturbance are considered to be multifactorial, although environmental stressors namely, noise, light and clinical care interactions have been frequently cited in both subjective and objective studies. As a result, interventions are targeted towards modifiable factors to ameliorate their impact. This paper reviews normal sleep physiology and the impact that sleep disturbance has on patient psychophysiological recovery, and the contribution that the clinical environment has on intensive care patients' sleep
A Study of Medium Access Control Protocols for Wireless Body Area Networks
The seamless integration of low-power, miniaturised, invasive/non-invasive
lightweight sensor nodes have contributed to the development of a proactive and
unobtrusive Wireless Body Area Network (WBAN). A WBAN provides long-term health
monitoring of a patient without any constraint on his/her normal dailylife
activities. This monitoring requires low-power operation of
invasive/non-invasive sensor nodes. In other words, a power-efficient Medium
Access Control (MAC) protocol is required to satisfy the stringent WBAN
requirements including low-power consumption. In this paper, we first outline
the WBAN requirements that are important for the design of a low-power MAC
protocol. Then we study low-power MAC protocols proposed/investigated for WBAN
with emphasis on their strengths and weaknesses. We also review different
power-efficient mechanisms for WBAN. In addition, useful suggestions are given
to help the MAC designers to develop a low-power MAC protocol that will satisfy
the stringent WBAN requirements.Comment: 13 pages, 8 figures, 7 table
Monitoring and detection of agitation in dementia: towards real-time and big-data solutions
The changing demographic profile of the population has potentially challenging social, geopolitical, and financial consequences for individuals, families, the wider society, and governments globally. The demographic change will result in a rapidly growing elderly population with healthcare implications which importantly include Alzheimer type conditions (a leading cause of dementia). Dementia requires long term care to manage the negative behavioral symptoms which are primarily exhibited in terms of agitation and aggression as the condition develops. This paper considers the nature of dementia along with the issues and challenges implicit in its management. The Behavioral and Psychological Symptoms of Dementia (BPSD) are introduced with factors (precursors) to the onset of agitation and aggression. Independent living is considered, health monitoring and implementation in context-aware decision-support systems is discussed with consideration of data analytics. Implicit in health monitoring are technical and ethical constraints, we briefly consider these constraints with the ability to generalize to a range of medical conditions. We postulate that health monitoring offers exciting potential opportunities however the challenges lie in the effective realization of independent assisted living while meeting the ethical challenges, achieving this remains an open research question remains.Peer ReviewedPostprint (author's final draft
Wireless Health Monitoring using Passive WiFi Sensing
This paper presents a two-dimensional phase extraction system using passive
WiFi sensing to monitor three basic elderly care activities including breathing
rate, essential tremor and falls. Specifically, a WiFi signal is acquired
through two channels where the first channel is the reference one, whereas the
other signal is acquired by a passive receiver after reflection from the human
target. Using signal processing of cross-ambiguity function, various features
in the signal are extracted. The entire implementations are performed using
software defined radios having directional antennas. We report the accuracy of
our system in different conditions and environments and show that breathing
rate can be measured with an accuracy of 87% when there are no obstacles. We
also show a 98% accuracy in detecting falls and 93% accuracy in classifying
tremor. The results indicate that passive WiFi systems show great promise in
replacing typical invasive health devices as standard tools for health care.Comment: 6 pages, 8 figures, conference pape
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