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Hemorrhage is a frequent complication in surgery patients; its identification and management have received increasing attention as a target for quality improvement in patient care in the Intensive Care Unit (ICU). The purposes of this work were 1) to find an early detection model for hemorrhage by exploring the range of data mining methods that are currently available, and 2) to compare prediction...
Innovative wellness gadgets are the products of convergence of science and technology in this dynamic digital era. It has not been possible before to provide just-in-time intervention to avoid unhealthy behavior. The change in behavior requires the understanding of the behavior theories and then practical implementation of the stages. Transtheoretical model supports to identify the stage of human...
Smartphone-based assessments have been considered a potential solution to passively monitor gait and mobility in early-stage Parkinson's disease (PD) patients. In the Multiple Ascending Dose clinical trial of PRX002/RG7935, 44 PD patients and 35 age-and gender-matched healthy individuals performed smartphone-based assessments for up to 24 weeks and up to 6 weeks respectively. For "passive monitoring",...
Lack of sleep can erode mental and physical well-being, often exacerbating health problems such as obesity. Wearable devices that capture and analyze sleep quality through predictive methodologies can help patients and medical practitioners make behavioral health decisions that can lead to better sleep and improved health. In the web extra at https://youtu.be/_zL-t4gk210, guest editor Katarzyna Wac...
Physical activity helps reduce the risk of cardiovascular disease, hypertension and obesity. The ability to monitor a person's daily activity level can inform self-management of physical activity and related interventions. For older adults with obesity, the importance of regular, physical activity is critical to reduce the risk of long-term disability. In this work, we present ActivityAware, an application...
Social interactions have been traditionally studied via questionnaires and participant observations, imposing high burden, low scalability and precision. The goal of my research is to explore novel techniques to detect and monitor social interactions in indoor settings. Through the development of a scalable research platform it would be possible to study social dynamics at a finer granularity. The...
In this paper, we investigate how to improve the reliability of heart–rate monitoring of a large number of people playing sports over a limited area of sports field. Densely– located nodes attached to exercisers transmit heart–rate data to a data collection node simultaneously, which negatively affects the reliability of data collection due to severe congestions caused by excessive traffic load. In...
Patient deterioration in the hospital ward is typically preceded by several hours of deranged physiology, as measured by the patient's vital signs. Estimation of the expected trajectory of a patient's future vital signs can allow us determine the degree of risk of physiological deterioration for that patient. Gaussian processes (GPs) offer a principled means of estimating vital-sign trajectories within...
In this work, we propose to use anthropometrics and physiological data to estimate cardiorespiratory fitness (CRF) in free-living and analyze the relation between estimated CRF and running performance. In particular, we use the ratio between running speed and heart rate (HR) as predictor for CRF estimation in free-living. The ratio is representative of fitness as lower HR at a given speed is expected...
Due to limited resource, noise and unreliable link, data loss and sensor faults are common in medical body sensor networks (BSN). Most available works used data reconstruction to improve data quality in traditional wireless sensor networks (WSN). However, existing data reconstruction schemes using redundant information of WSN can not provide a satisfactory accuracy for BSN. In light of this, a Bayesian...
Medical data are crucial for providing reliable mobile health services. However, its reliability may be degraded due to internal factors related to performance variations of mobile technologies used in the application and other external ones such as the environmental ones. This paper addresses this problem by proposing an ontology-based approach to deal with data and reliability management in mobile...
Intrusion Detection System (IDS) are playing a very substantial role in protecting computer networks. Still conventional IDS finds itself limited when it comes to distribute intrusion detection. An intruder may conceal its origin of attack by moving from node to node in a network. In order to conquer these limitations, alerts are to be exchanged and correlated in distributed intrusion detection system...
Ankle edema an important symptom for monitoring patients with chronic systematic diseases. It is an important indicator of onset or exacerbation of a variety of diseases that disturb cardiovascular, renal, or hepatic system such as heart, liver, and kidney failure, diabetes, etc. The current approaches toward edema assessment are conducted during clinical visits. In-clinic assessments, in addition...
Online mining is a difficult task especially when such data streams evolve over time. Evolving data stream occurs when concepts drift or change completely, is becoming one of the core issues. A large portion of change detection research are carried out in the area of supervised learning, very little has been carried out for unlabeled data specifically in the area of transactional data streams. Overall...
This paper discusses aspects of the implementation of long-term monitoring of heart action. The focus is on the analysis of deviations in the heart of the examined patient, and timely response to the emergence of this situation. It is assumed that the portable device recording ECG signals in real-time analyzes the functional condition of the patient and if necessary, generates signals warning of the...
Chronic diseases are major causes of deaths in Australia and throughout the world. This necessitates the need for a self-care, preventive, predictive and protective assisted living system where a patient can be monitored continuously using wearable and wireless sensors. In real-time home monitoring system, various biological signals of a patient are obtained continuously using a mobile device (smart...
Passive RFID tags provide a promising way to create wireless and battery-free heart rate monitors. However, the reliability of these tags is limited in the presence of common noise sources in their environment. In this paper, we propose an algorithm to improve the beat detection for RFID based heart rate monitors in noisy environments. To achieve this, a logistic regression model is first employed...
An activity classifier based on an abstract model of the human body is suitable for use in an e-textile monitoring system without the need to retrain the recognition model to accommodate different users, sensor types, or garments.
Early detection of hypertension generally requires continuous monitoring of blood pressure levels which is not facilitated by traditional methods such as the cuff, which cannot be used in the normal environment for continuous monitoring due to the regular pressurization of certain body parts. Thus there is a need for non-invasive continuous pressure monitoring mechanism. In this paper we present a...
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