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IEEE International Workshop on Measurements And Networking (M&N)

作者： Ando, B. Baglio, S. Lombardo, C. O. Marletta, V. Univ Catania Dept Elect Elect & Informat Engn DIEEI I-95124 Catania Italy

ISBN: (纸本)9781479918607

This paper deals with the development of a multi-user assistive system for the monitoring of elders and people with neurological pathologies (e.g. Alzheimer) during their staying in social care or health facilities. The system adopts wearable devices to monitor the dynamics of the users and a dedicated wireless network for communication. The wearable device is able to recognize critical events like falls or prolonged inactivity, to monitor the user posture and to send an alarm to a centralized monitoring system which will broadcast the alarm to caregivers alert devices. The paper focuses on the smart algorithms developed for the classification of the ADL (Activities of Daily Living) which use the information from the inertial sensors installed on the user device. In particular a novel, with respect to the State Of The Art, multi-sensor data fusion approach, combining data from the onboard accelerometer and the gyroscope is presented. Apart from alerts management, the information provided by this system is useful to track the evolution of the user pathology, also during rehabilitation tasks.

关键词： AAL ADL Fall Detection Inertial Sensors threshold algorithm WSN User Posture User Safety Monitoring

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Prediction of appropriate ICD-therapy using infarct heterogeneity from CMR in patients with coronary artery disease

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Journal of Cardiovascular Magnetic Resonance 2015年第SUPPL 1期17卷 P165-P165页

作者： Robert Jablonowski Uzma Chaudhry Henrik Engblom Håkan Arheden Einar Heiberg Rasmus Borgquist Marcus Carlsson Cardiac MR group Lund Dept of Clinical Physiology Lund University Lund Sweden Dept. of Cardiology Arrhytmia Clinic Skane University Hospital Lund University Lund Sweden Dept. of Biomedical Engineering Faculty of Engineering Lund University Lund Sweden

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Optimal and Compact Control Policies for Energy Storage Units With Single and Multiple Batteries

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IEEE TRANSACTIONS ON SMART GRID 2014年第3期5卷 1308-1317页

作者： Erseghe, Tomaso Zanella, Andrea Codemo, Claudio G. Univ Padua Dipartimento Ingn Informaz Padua Italy

In this paper we investigate the use of energy storage units (ESUs) to reduce the average cost of power supply. Using a dynamic programming (DP) argument, we first show that the optimal control policy for a single-battery ESU, under piecewise linear cost functions, has a threshold structure that can be expressed and stored in a very compact form. We then extend the analysis to an ESU with multiple (heterogeneous) batteries, where DP is generally impractical because of the explosion of the computational complexity with the number of batteries. We hence define a simple method to map the optimal solution of a suitable single-battery ESU into an admissible policy for the multiple-battery ESU, whose complexity grows only linearly with the number of batteries. Extensive simulation results show that the proposed approach can yield significant cost reduction in comparison with other policies, under realistic users' power requests, and with different costs functions. Furthermore, the admissible policy for the multiple-battery ESU is shown to achieve almost optimal performance under realistic assumptions on the battery parameters.

关键词： Dynamic programming energy storage multiple batteries optimization smart grid threshold algorithm

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A feasibility study of using smartphone built-in accelerometers to detect fall portents

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AUTOMATION IN CONSTRUCTION 2014年 38卷 74-86页

作者： Dzeng, Ren-Jye Fang, Yi-Cho Chen, I-Chung Natl Chiao Tung Univ Dept Civil Engn Hsinchu Taiwan

Fall accidents contribute to nearly half of all fatalities in the construction industry in Taiwan. Detecting fall portents using a smartphone, which many people carry daily, may help reduce fall accidents if the accuracy is acceptable. We designed two experiments with three algorithms to evaluate how well a smartphone can detect both falls and fall portents in a tiling operation scenario. The experiments show that work-related motions barely affected the detection of falls, and the result had a sensitivity and specificity of 100% and 96.1%, respectively. However, for detecting portents, the work-related motions had quite a large impact on the gyroscope-based algorithm, which demonstrated an accuracy rate of only 4.3%, but had only limited impact on the accelerometer-based algorithm, which still show acceptable accuracy rates of 73.5% and 88.5%. We conclude that using a smartphone to detect falls and portents in a construction site is feasible. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Smartphone Accelerometer Fall detection Portent threshold algorithm Construction safety

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A smartphone-based detection of fall portents for construction workers

A smartphone-based detection of fall portents for constructi...

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Creative Construction Conference (CC)

作者： Fang, Yi-Cho Dzeng, Ren-Jye Natl Chiao Tung Univ Dept Civil Engn 1001 Ta Hsueh Rd Hsinchu 30010 Taiwan

The construction industry accounts for nearly half of all industry-related fatalities in Taiwan. Identified as the leading cause of such fatalities for several decades, falls also contribute to almost half of work-related fatalities. Given the strenuous nature of construction work, workers are prone to loss of awareness and balance, increasing the safety risk and number of fall accidents. Previous studies have indicated that loss of awareness may be the major cause of occupational injuries or fatalities, and identified the strong correlation between falls and loss of balance. Thus, real-time monitoring of the mental and balance conditions of workers may help identify fall portents, and thus prevent falls from happening. This paper describes a framework for developing a personal safety monitoring system based on a smartphone, which receives external signals wirelessly from motion sensors and brain wave sensors attached to a vest and inside a helmet, and transmit these signals to a monitoring server for further analysis. This paper also presents an experiment with preliminary findings regarding the detection of fall portents, using the internal motion sensors of a smartphone. In the experiment, participants performed a tiling task on a scaffold under four physiological statuses. We identified the fall portents based on the self-awareness of the participants, hazardous actions performed by the participants, and outsider observations by experiment administrators. An accelerometer-based threshold algorithm was tested, and its performance was evaluated against the identified fall portents. The results indicated that the work-related motions had a limited impact on the detection algorithm. The accuracy for the sleepiness, fatigue, normal, and inebriation statuses were 92.3%, 90.4%, 77.3%, and 68.8%, respectively. The algorithm exhibited an overall accuracy of 86%, thus, we conclude that using a smartphone to detect fall portents in a working scenario is feasible, and deser

关键词： accelerometer construction safety fall portent detection smartphone threshold algorithm

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Design and Realization of an Early Pre-impact Fall Alarm System Based on MEMS Inertial Sensing Units

Design and Realization of an Early Pre-impact Fall Alarm Sys...

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4th International Conference of Bionic Engineering (ICBE 2013)

作者： Li, Huiqi Liang, Ding Ning, Yunkun Zhang, Qi Zhao, Guoru Chinese Acad Sci Shenzhen Key Lab Low Cost Healthcare Shenzhen 518055 Peoples R China

ISBN: (纸本)9783037859322

Falls are the second leading cause of unintentional injury deaths worldwide, so how to prevent falls has become a safety and security problem for elderly people. At present, because the sensing modules of most fall alarm devices generally only integrate the single 3-axis accelerometer, so the measured accuracy of sensing signals is limited. It results in that these devices can only achieve the alarm of post-fall detection but not the early pre-impact fall recognition in real fall applications. Therefore, this paper aimed to develop an early pre-impact fall alarm system based on high-precision inertial sensing units. A multi-modality sensing module embedded fall detection algorithm was developed for early pre-impact fall detection. The module included a 3-axis accelerometer, a 3-axis gyroscope and a 3-axis magnetometer, which could arouse the information of early pre-impact fall warning by a buzzer and a vibrator. Total 81 times fall experiments from 9 healthy subjects were conducted in simulated fall conditions. By combination of the early warning threshold algorithm, the result shows that the detection sensitivity can achieve 98.61% with a specificity of 98.61%, and the average pre-impact lead time Is 300ms. In the future, GPS, GSM electronic modules and wearable protected airbag will be embedded in the system, which will enhance the real-time fall protection and timely immediate aid immensely for the elderly people.

关键词： early fall alarm inertial sensor threshold algorithm

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Evaluation of Electrical Capacitance Tomography thresholding Techniques for Void Fraction Measurement of Gas-liquid System 3

Evaluation of Electrical Capacitance Tomography Thresholding...

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3rd International Conference on Process Engineering and Advanced Materials (ICPEAM)

作者： Mei, Irene Lock Sow Ismail, Idris B. Abdullah, Bawadi B. Shafquet, Areeba Univ Teknol PETRONAS Dept Chem Engn Bandar Sri Iskandar 31750 Perak Malaysia Univ Teknol PETRONAS Elect & Elect Engn Dept Bandar Sri Iskandar 31750 Perak Malaysia

ISBN: (纸本)9783038351818

An analysis on the void fraction measurement for binary phase gas-liquid dielectric materials inside an Electrical Capacitance Tomography (ECT) sensor has been performed on the tomogram images by using different thresholding techniques. The analysis is pertinent to improve the accuracy of the application of thresholding technique for void fraction measurements in pipelines and reactors since the currently available information is limited in terms of accuracy. This preliminary investigation was performed to evaluate the accuracy of three different thresholding algorithms: Otsu's, Niblack's and Kuo's Method based on the void fraction measurement for a binary phase oil-air system. The experimental and image processing analysis enables one to determine the optimal threshold method by selecting the threshold algorithm which produces the highest accuracy and consistency in the void fraction measurement as compared to the actual value.

关键词： Electrical Capacitance Tomography threshold algorithm Otsu's algorithm Niblack's algorithm Kuo's algorithm Void Fraction Measurement Multiphase System

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A method of wavelet-based dual thresholding de-noising for ECG Signal

A method of wavelet-based dual thresholding de-noising for E...

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International Congress on Image and Signal Processing

作者： Liu Yi Yu-qing Song Sch. of Comput. Sci. & Telecommun. Eng. Jiangsu Univ. Zhenjiang China

ISBN: (纸本)9781479958368

ECG (Electrocardiography) signal is one of important means of clinical diagnosis for heart disease which has great significance in clinical medicine. De-noising is a critical task in the preprocess of ECG signal. This paper proposed a dual thresholding function and a level-dependent threshold estimator by the different thresholds estimated based on wavelet coefficients in different layers. Experiments were carried out and the results suggest that the proposed new threshold algorithm is suitable to remove the ECG signal noise and has potential in ECG signal processing field.

关键词： diseases electrocardiography medical signal processing signal denoising wavelet transforms ECG signal noise ECG signal preprocessing ECG signal processing field clinical diagnosis clinical medicine dual thresholding function heart disease level-dependent threshold estimator threshold algorithm wavelet coefficients wavelet-based dual thresholding denoising Electrocardiography Noise reduction Signal processing algorithms Signal to noise ratio Wavelet coefficients De-noising ECG Signal threshold De-noising Wavelet

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Extraction and Segmentation of Sputum Cells for Lung Cancer Early Diagnosis

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algorithmS 2013年第3期6卷 512-531页

作者： Taher, Fatma Werghi, Naoufel Al-Ahmad, Hussain Donner, Christian Khalifa Univ Dept Elect & Comp Engn Sharjah U Arab Emirates Univ Osnabrueck Dept Comp Engn Osnabruck Germany

Lung cancer has been the largest cause of cancer deaths worldwide with an overall 5-year survival rate of only 15%. Its symptoms can be found exclusively in advanced stages where the chances for patients to survive are very low, thus making the mortality rate the highest among all other types of cancer. The present work deals with the attempt to design computer-aided detection or diagnosis (CAD) systems for early detection of lung cancer based on the analysis of sputum color images. The aim is to reduce the false negative rate and to increase the true positive rate as much as possible. The early detection of lung cancer from sputum images is a challenging problem, due to both the structure of the cancer cells and the stained method which are employed in the formulation of the sputum cells. We present here a framework for the extraction and segmentation of sputum cells in sputum images using, respectively, a threshold classifier, a Bayesian classification and mean shift segmentation. Our methods are validated and compared with other competitive techniques via a series of experimentation conducted with a data set of 100 images. The extraction and segmentation results will be used as a base for a CAD system for early detection of lung cancer which will improve the chances of survival for the patient.

关键词： lung cancer detection image segmentation sputum cells threshold algorithm bayesian classification mean shift algorithm

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A Mallat Based Wavelet ECG De-noising algorithm

A Mallat Based Wavelet ECG De-noising Algorithm

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International Conference on Information Technology and Management Innovation (ICITMI2012)

作者： Zhang Sheng Gao Jie Yang Jie Yu Shun Zhejiang Normal Univ Coll Math Phys & Informat Engn Jinhua Peoples R China

ISBN: (纸本)9783037855744

A Mallat based wavelet de-noising algorithm in ECG analysis is studied. We use bior3.7 wavelet based on Mallat algorithm for ECG decomposition. Then we choose composite threshold and wavelet reconfiguration algorithm for signal de-noising to achieve an effective result. Data get from MIT/BIH is examined using the method. The result shows that it can not only remove the power frequency disturbance, EMG interference and baseline drift emerging in ECG, but also preserve the ECG characteristics.

关键词： ECG De-noising Mallat algorithm threshold algorithm Wavelet Transform

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