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|Title:||Wearable body area sensor networks for continuous dynamic health monitoring in daily activities : case study of intelligent footwear system||Authors:||Shu, Lin||Keywords:||Wireless sensor networks.
Patient monitoring -- Data processing.
Hong Kong Polytechnic University -- Dissertations
|Issue Date:||2012||Publisher:||The Hong Kong Polytechnic University||Abstract:||The specific cares for elderly people and patients with chronic diseases such as cardiac disorder, diabetes and hypertension have placed an increasing burden upon public healthcare systems. This calls for a need of providing continuous dynamic monitoring in daily activities to save time, cost and human resources as well as to prevent diseases in early stage. Most current technologies, however, are restricted in research laboratories or hospitals, and not reliable for continuous monitoring in everyday life, due to incomparability in rigidity of sensors and skin, heavy and bulky nodes and power sources, and complicated operations in body area sensor networks. The present work is aimed to design a wearable body area sensor network and implement a case for continuous dynamic monitoring in healthcare, based on investigations of various enabling technologies including textile sensors and body area sensor networks (BASNs). Textile sensors have unique characteristics such as soft, light, highly sensitive to external force with a wide measurement range, and a long service life, which are suitable for wearable applications for long-term use. However, there is a lack of proper connections between textile sensors and electronics, such as electronic interfaces, matrixes, and relevant systems. By investigations of principles, merits and limitations of current electronic interfaces for resistive sensors, as well as mechanisms and characteristics of carbon silicone composite textile pressure sensors, a suitable electronic interface for textile resistive sensors is selected and investigated, providing wireless data acquisition with an error less than 1% and enhanced stability to wearable interferences. Based on studies of matrix structure of capacitive and resistive textile sensors, a novel textile sensor matrix readout method is proposed by solving a set of linear matrix equations, with a crosstalk error of 0.6%. It is adopted in a single-node in-shoe plantar pressure measurement and analysis system. A real-time display and analysis software is presented in the system to derive parameters such as mean pressure, peak pressure, centre of pressure (COP), and shift speed of COP. Experimental results show that this system has stable performance in both static and dynamic measurements.
Three main types of BASNs are then studied and compared in the aspects of network structure, elements and interconnections, standard, compatibility with mobile computing devices, and network delay for healthcare. Bluetooth type BASN is selected in this study for its superior compatibility with handheld mobile computing devices. Properties of this BASN are explored. A model for estimation of delay of this BASN is established by calculation of time cost in each component, layer and process of total networks, involving distribution hypothesis, Poisson process analysis, and optimized configuration. It is implemented in a three-node Bluetooth type BASN platform for the monitoring of foot conditions and respiration in daily activities. The average difference in sampling frequency between experimental and simulation results is found to be 5.73%. Optimizations of five factors with respect to delay are presented for performance enhancement, including the number of sensors and nodes, UART baud rate, buffer size, and computing ability of a mobile device. Platform and in-shoe pedography technologies for plantar pressure measurement, both research prototypes and commercial products, are comprehensively studied. By considering advantages and limitations of the existing plantar pressure measurement technologies, the intelligent footwear system, as a case of wearable BASN for continuous dynamic monitoring in daily activities, was then developed. It collects, during daily activities, foot information including plantar pressure, in-shoe temperature and humidity, centre of pressure (COP), and 3-axis foot accelerations. Textile pressure sensors, electronic interfaces, sensor matrices, Bluetooth based BASNs, are configured in the intelligent footwear system. Wear trials with ten participants show that the system has an acceptable accuracy (7.7% average difference with Novel emed®-at system in peak pressure measurement), sufficient repeatability (6.4% average variation within seven to ten days), and general wearing comfort (according to the questionnaire study). A set of 24-hour monitoring data of a subject in his normal daily activities was recorded, including plantar pressure, in-shoe temperature and humidity, COP coordinates, and foot 3-axis accelerations. Exceptionally high peak pressure was examined in the data as well as its time duration, which may cause discomfort or damage in the foot. The lasting high plantar pressure (>300kPa, for 3.2% time of the day) in the subject's left forefoot was related to a plantar callus identified, while some high plantar pressure took up a smaller partition (0.1%) in his healthy right foot. The occupational sitting time is also estimated from the COP data to evaluate the subjects' active levels in a day, and the relationship with overweight.
|Description:||xx, 187 leaves : ill. (some col.) ; 30 cm.
PolyU Library Call No.: [THS] LG51 .H577P ITC 2012 Shu
|URI:||http://hdl.handle.net/10397/5538||Rights:||All rights reserved.|
|Appears in Collections:||Thesis|
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