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Body Sensor Networks (BSN), 2010 International Conference on

Date 7-9 June 2010

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Displaying Results 1 - 25 of 64
  • [Front cover]

    Page(s): C1
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  • [Title page i]

    Page(s): i
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  • [Title page iii]

    Page(s): iii
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  • [Copyright notice]

    Page(s): iv
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  • Table of contents

    Page(s): v - ix
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  • Welcome message from the BSN 2010 General Chair

    Page(s): x
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  • Welcome message from the BSN 2010 Technical Programme Chair

    Page(s): xi
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  • BSN 2010 Organization

    Page(s): xii
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  • BSN 2010 Technical Progamme Committee

    Page(s): xiii
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  • Dr. Ahmed Elsaify Memorial Award

    Page(s): xiv
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  • Invited speakers

    Page(s): xv - xix
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    Provides an abstract for each of the invited presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • A Pilot Study on Evaluating Recovery of the Post-Operative Based on Acceleration and sEMG

    Page(s): 3 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1009 KB) |  | HTML iconHTML  

    Although abdominal operation is a kind of important clinical surgery, recovery of the post-operative is usually evaluated by the judgment of doctors. This traditional medical care mode may take much time of medical staffs and meanwhile increase the expense of patients. In this paper, a recovery evaluation system is established for the abdominal post-operative by using body sensor networks (BSN). The evaluation system can collect acceleration signals from five parts of human body and surface electro myographic (sEMG)signals from abdomen muscle group (AMG) during a user'sdaily activities. An experiment as a pilot study has been conducted to test the validity and feasibility of the system. The experimental results showed the evaluation system may effectively acquire the relationship between a user's daily activities and intensity of AMG. The study work in this paper may be used as a basis for further study on evaluating recovery level of the actual post-operative. View full abstract»

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  • Quantitative Assessment of the Motion of the Lumbar Spine and Pelvis with Wearable Inertial Sensors

    Page(s): 9 - 15
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (588 KB) |  | HTML iconHTML  

    Chronic Low Back Pain (CLBP) is a leading cause of disability with significant economic costs and severe psychological and social consequences. LBP patients also have the tendency to change the movement of the back and hold the pelvis rigid. Currently, the clinical assessment of a LBP patient is undertaken at a single point in time during clinic visits rather than through continuous monitoring. To monitor motion of the lumbar spine and pelvis, we have developed a wearable prototype sensor based on inertial sensor technology combined with the Body Sensor Network (BSN) platform. The device enables quantitative assessment of motion, especially the proportion of pelvic to lumbar movement. The developed device has been tested in a pilot study with healthy volunteers for a range of movements and results validated by optical tracking. This paper presents our approach and exemplifies the quantitative assessment of the lateral flexion movement. The next stage of the project will involve testing with patients. View full abstract»

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  • A Device-Orientation Independent Method for Activity Recognition

    Page(s): 19 - 23
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (461 KB) |  | HTML iconHTML  

    This paper describes an orientation-independent method for detecting activities of daily living based on reference coordinate transformation. With the proposed method, a classification model can be trained using data acquired during a specific sensor orientation and applied to other input signals regardless of the orientation of the device. The technique is validated using activity recognition experiments with four different orientations of a single tri-axial accelerometer placed on the waist of 13 subjects performing a sub-class of activities of daily living. A high subject-independent accuracy of 90.42% has been achieved, reflecting a significant improvement of 11.74% and 16.58%, compared with classification without input transformation and classification with orientation-specific models, respectively. View full abstract»

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  • Sensor Placement for Activity Detection Using Wearable Accelerometers

    Page(s): 24 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1170 KB) |  | HTML iconHTML  

    Activities of daily living are important for assessing changes in physical and behavioural profiles of the general population over time, particularly for the elderly and patients with chronic diseases. Although accelerometers are widely integrated with wearable sensors for activity classification, the positioning of the sensors and the selection of relevant features for different activity groups still pose interesting research challenges. This paper investigates wearable sensor placement at different body positions and aims to provide a framework that can answer the following questions: (i) What is the ideal sensor location for a given group of activities? (ii) Of the different time-frequency features that can be extracted from wearable accelerometers, which ones are most relevant for discriminating different activity types? View full abstract»

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  • Elderly Risk Assessment of Falls with BSN

    Page(s): 30 - 35
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (345 KB) |  | HTML iconHTML  

    Due to the natural aging process, the risks associated with falling can increase significantly. For the elderly, this usually marks a rapid deterioration of their health. While there are identified strategies that can be adopted to reduce the number of falls, it is still not possible to prevent all falls. Clinically, the Tinetti Gait and Balance Assessment has been widely used to assess the risk of falls in elderly by examining balance and gait. This paper presents our initial results of using an ear-worn BSN sensor to detect aspects of the Tinetti Gait and Balance Assessment to predict the risk of falls compared to a healthy control cohort. For this study, data was collected from a control cohort of 12 healthy volunteers and a cohort of 16 elderly fallers of varying degrees of risk. The results derived have shown that it is possible to directly detect some aspects of the Tinetti Gait and Balance Assessment and the Timed Up and Go test, demonstrating the potential value of using the platform for continuous assessment in a home environment. View full abstract»

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  • Multisensor Fusion in Smartphones for Lifestyle Monitoring

    Page(s): 36 - 43
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (832 KB) |  | HTML iconHTML  

    Smartphones with diverse sensing capabilities are becoming widely available and pervasive in use. With the phone becoming a mobile personal computer, integrated applications can use multi-sensory data to derive information about the user's actions and the context in which these actions occur. This paper develops a novel method to assess daily living patterns using a smartphone equipped with microphones and inertial sensors. We develop a feature-space combination approach for fusion of information from sensors sampled at different rates and present a computationally light-weight algorithm to identify various high level activities. Preliminary results from an initial deployment among eight users indicate the potential for accurate, context-aware, and personalized sensing. View full abstract»

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  • Rapid Prototyping of a Low-Power, Wireless, Reflectance Photoplethysmography System

    Page(s): 47 - 51
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (356 KB) |  | HTML iconHTML  

    In this investigation we have prototype a low-power, wireless, reflectance photoplethysmography (PPG) system. The PPG system consisted of a PPG sensor and a workstation. An amplifier circuit is stacked on the bottom of a commercial wireless sensor node to achieve the PPG sensor of wearable size. The PPG sensor detects the local bio-signals and radios the signals to the workstation for display and storage. This work demonstrates the feasibility of using WSN-based technology for fast prototyping of a body sensor system. View full abstract»

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  • Supporting Mobility in Body Sensor Networks

    Page(s): 52 - 55
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (215 KB) |  | HTML iconHTML  

    Body Sensor Networks (BSNs) form a promising technology to supply healthcare to an ageing population. A large number of sensor devices, radios and MAC protocols are being developed. However, current solutions all assume a single-hop topology, while research results confirm the need for multi-hop topologies. In these multi-hop networks, because of the small scale of a BSN, node mobility will arise frequently. This work presents the first algorithm to support such Mobile BSNs, while remaining energy efficient. View full abstract»

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  • Breathing Feedback System with Wearable Textile Sensors

    Page(s): 56 - 61
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    Breathing exercises form an essential part of the treatment for respiratory illnesses such as cystic fibrosis. Ideally these exercises should be performed on a daily basis. This paper presents an interactive system using a wearable textile sensor to monitor breathing patterns. A graphical user interface provides visual real-time feedback to patients. The aim of the system is to encourage the correct performance of prescribed breathing exercises by monitoring the rate and the depth of breathing. The system is straight forward to use, low-cost and can be installed easily within a clinical setting or in the home. Monitoring the user with a wearable sensor gives real-time feedback to the user as they perform the exercise, allowing them to perform the exercises independently. There is also potential for remote monitoring where the user's overall performance over time can be assessed by a clinician. View full abstract»

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  • Minimizing Energy Consumption in Body Sensor Networks via Convex Optimization

    Page(s): 62 - 67
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (321 KB) |  | HTML iconHTML  

    Body Sensor Networks (BSNs) consist of miniature sensors deployed on or implanted into the human body for health monitoring. Conserving the energy of these sensors, while guaranteeing a required level of performance, is a key challenge in BSNs. In terms of communication protocols, this translates to minimizing energy consumption while limiting the latency in data transfer. In this paper, we focus on polling-based communication protocols for BSNs, and address the problem of optimizing the polling schedule to achieve minimal energy consumption and latency. We show that this problem can be posed as a geometric program, which belongs to the class of convex optimization problems, solvable in polynomial time. We also introduce a dynamic priority vector for each sensor, based on the observation that relative priorities of sensors in a BSN change over time. This vector is used to develop a decision-tree based approach for resolving scheduling conflicts among devices. The proposed framework is applicable to a broad class of periodic polling-based communication protocols. We design one such protocol in detail and show that it achieves an improvement of approximately 45% over the widely accepted standard IEEE 802.15.4 MAC protocol. View full abstract»

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  • Environment Control System Using Correlation Dimension of Alpha Wave

    Page(s): 68 - 70
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    Electroencephalograph has been used in some Environment Control System to help severe disabled people to improve their quality of life. This paper studied the difference of correlation dimension of alpha wave between eye opening and eye closure and proposed a method to control device on and off using correlation dimension of alpha wave. By modifying Grassberger and Procaccia method, the correlation dimension could be achieved automatically. The experiment showed that correlation dimension of alpha wave could be used to distinguish eye opening and closure and help severe disabled people. View full abstract»

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  • An RFID Communication System for Medical Applications

    Page(s): 71 - 75
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3366 KB) |  | HTML iconHTML  

    During the last years the significance of RFID systems has increased rapidly. In fact, its use is expected to increase by a factor of twenty until 2016. Medical applications are expected to be a main cause of this development. Currently, RFID systems are primary identification systems, based on the transmission of a key number or little further information. Using new technical developements and higher integration levels, it may be possible to extend these systems to measure and transmit data. Such RFID systems can be used in different areas of medical technology, because of the combination of application flexibility with the possibility of identification and data collection. For example, they can be used to identify patients or pharmaceuticals, monitor blood preservations or for medical implant communication. View full abstract»

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  • Real-Time Monitoring of the Heart Rate Response to Power Output for Cyclists

    Page(s): 76 - 79
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    Every cyclist responds individually to a certain training intensity. This response can influence the effectiveness of predefined training schedules. In this study, real-time measurements of physiological responses that cyclist already use (e.g. heart rate, power measurements), were used in an algorithm that could accurately monitor different individual heart rate responses to training intensities. The developed algorithm used data-based model structures to estimate the relation between heart rate and training intensity recursively. Two different model structures were tested, namely an ARX model structure and an output error model structure (OE). The average RT2 of the simulated heart rates with the two different model structures were 0.86 ± 0.15 and 0.89 ± 0.13 respectively. This algorithm allows accurate modeling of the heart rate response to training intensity in real-time. In future research, such algorithms could be implemented in a body sensor network for training optimization. The real-time estimated model characteristics could then be used to calculate the needed training intensity during training in order to acquire the optimal training effect for an individual at any given moment. View full abstract»

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  • Off-Body Radio Channel Characterisation Using Ultra Wideband Wireless Tags

    Page(s): 80 - 83
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (347 KB) |  | HTML iconHTML  

    This paper presents an experimental investigation of off-body radio propagation channels based on commercially available UWB wireless tags. The tags operate at frequency band of 5.9~7.2 GHz. A measurement campaign was performed both in the chamber and in an indoor environment for comparison. The path loss for nine different channels is shown with parameters describing the radio channel derived through statistical analysis. View full abstract»

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