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23rd International Conference on Engineering, Technology and Innovation (ICE/ITMC)

作者： Ando, B. Baglio, S. Marletta, V. Crispino, R. Univ Catania Dept Elect Elect & Informat Engn DIEEI Catania Italy

ISBN: (纸本)9781538607749

Falls represent a serious issue which can have catastrophic consequences and the need for ICT based solutions aimed to improve the life quality and autonomy of frail people, is hence emerging, with particular regards to falls' detection and classification. Although two main computing approaches for fall detection are threshold based algorithms and machine learning methods, it can be affirmed that up today a well-accepted solution has not been yet identified. In this paper, the experience in developing reliable fall detector of the research group working in the field of assistive technologies at the DIEEI of the University of Catania-Italy is reported, with specific regards to the investigation of a NeuroFuzzy based approach.

关键词： Assistive Technology ADL Fall Detection Smartphone Inertial Sensors threshold algorithm NeuroFuzzy paradigm

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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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An Adaptive Extracting Method for Motion-blurred Stars

An Adaptive Extracting Method for Motion-blurred Stars

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Chinese Automation Congress (CAC)

作者： Liu, Lin Bao, Qilian Zheng, Xunjiang Sun, Shuodong Shanghai Jiao Tong Univ Dept Instrument Sci & Engn Shanghai Peoples R China Shanghai Aerosp Control Technol Inst Shanghai Peoples R China

ISBN: (纸本)9781728140940

In this paper, a novel method for extracting difficult to determine a suitable global threshold, and a large motion-blurred stars in high dynamic imaging environment amount of noise causes the connected domain analysis to take affected by stray light is proposed. According to the characteristic of the background noise, an adaptive threshold estimation algorithm for each pixel with down sampling method and block weighted least squares fitting is presented. Furthermore, based on the scanning method and DBSCAN clustering, a new algorithm for extracting pixels of each star is also proposed. The experimental results indicate that the proposed method can improve the accuracy and real-time performance of star image processing even affected by inhomogeneous stray light under high dynamic conditions. The centroid error can be reduced to less than 1 pixel even if the star is motion-blurred to more than 30 pixels and the peak gray value is relatively low.

关键词： star sensor threshold algorithm star point extraction clustering algorithm

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A Unified Processing Paradigm for Interactive Location-based Web Search 18

A Unified Processing Paradigm for Interactive Location-based...

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11th ACM International Conference on Web Search and Data Mining

作者： Wang, Sheng Bao, Zhifeng Huang, Shixun Zhang, Rui RMIT Univ Melbourne Vic Australia Univ Melbourne Melbourne Vic Australia

ISBN: (纸本)9781450355810

This paper studies the location-based web search and aims to build a unified processing paradigm for two purposes: (1) efficiently support each of the various types of location-based queries (kNN query, top-k spatial-textual query, etc.) on two major forms of geo-tagged data, i.e., spatial point data such as geo-tagged web documents, and spatial trajectory data such as a sequence of geo-tagged travel blogs by a user;(2) support interactive search to provide quick response for a query session, within which a user usually keeps refining her query by either issuing different query types or specifying different constraints (e.g., adding a keyword and/or location, changing the choice of k, etc.) until she finds the desired results. To achieve this goal, we first propose a general Top-k query called Monotone Aggregate Spatial Keyword query-MASK, which is able to cover most types of location-based web search. Next, we develop a unified indexing (called Textual-Grid-Point Inverted Index) and query processing paradigm (called ETAIL algorithm) to answer a single MASK query efficiently. Furthermore, we extend ETAIL to provide interactive search for multiple queries within one query session, by exploiting the commonality of textual and/or spatial dimension among queries. Last, extensive experiments on four real datasets verify the robustness and efficiency of our approach.

关键词： inverted index threshold algorithm spatial keyword search

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A Multi-User Assistive System for the User Safety Monitoring in Care Facilities 3

A Multi-User Assistive System for the User Safety Monitoring...

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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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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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Cryptographic Methods for Securing the YML Framework

Cryptographic Methods for Securing the YML Framework

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1st International Conference on Systems and Computer Science (ICSCS)

作者： Lv, Xin Petiton, Serge G. Shang, Ling Wang, Zhijian Xu, Feng Univ Sci & Technol Lille LIFL MAP Team Villeneuve Dascq France Hohai Univ Coll Comp & Informat Nanjing Jiangsu Peoples R China North China Univ Water Conservancy & Elect Power Sch Informat Engn Zhengzhou Peoples R China

ISBN: (纸本)9781467306737;9781467306720

YML framework is a well-adapted advanced tool to support designing and executing portable parallel applications over large scale peer to peer and grid middlewares. We believe that it is necessary to consider the crucial security concerns for the improvement and extension of the framework. In this paper, two security mechanisms were introduced for the first time. To ensure the computing resources being utilized properly and legitimately, a lightweight authentication protocol was proposed, enabling the user to log in YML with 2 XOR and 1 HASH operation, meanwhile, a splitting way was adopted to distribute the secret key, making only the application requester can obtain the result. To safeguard the process of data exchanging, an efficient threshold encryption scheme was proposed. By generating a set of matched pieces of key, the data can be transformed into efficiently-recoverable half-ciphertext, which is able to transfer in public channel securely. Furthermore, dynamical addition of peers is supported in the scheme.

关键词： front end data repository key-splitting lightweight authentication threshold algorithm half-ciphertext

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Mean threshold and ARNN algorithms for Identification of Eye Commands in an EEG-Controlled Wheelchair

Mean Threshold and ARNN Algorithms for Identification of Eye...

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The 7th International Conference on Management and Service Science(MASS 2013)

作者： Nguyen Thanh Hai Nguyen Van Trung Vo Van Toi Biomedical Engineering Department International UniversityVietnam National UniversityHo Chi Minh CityVietnam

This paper represented Autoregressive Neural Network(ARNN) and meant threshold methods for recognizing eye movements for control of an electrical wheelchair using EEG *** eye movements such as eyes open,eyes blinks,glancing left and glancing right related to a few areas of human brain were investigated.A Hamming low pass filter was applied to remove noise and artifacts of the eye signals and to extract the frequency range of the measured *** autoregressive model was employed to produce coefficients containing features of the EEG eye *** coefficients obtained were inserted the input layer of a neural network model to classify the eye *** addition,a mean threshold algorithm was employed for classifying eye *** methods were compared to find the better one for applying in the wheelchair control to follow users to reach the desired *** results of controlling the wheelchair in the indoor environment illustrated the effectiveness of the proposed approaches.

关键词： Autoregressive NN Model threshold algorithm EEG Technology Eye Activity and Electrical Wheelchair

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A Comparison among Different Strategies to Detect Potential Unstable Behaviors in Postural Sway

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SENSORS 2022年第19期22卷 7106页

作者： Ando, Bruno Baglio, Salvatore Graziani, Salvatore Marletta, Vincenzo Dibilio, Valeria Mostile, Giovanni Zappia, Mario Univ Catania Dept Elect Elect & Informat Engn DIEEI I-95125 Catania Italy Univ Catania Dept Med Surg Sci & Adv Technol GF Ingrassia I-95100 Catania Italy Oasi Res Inst IRCCS I-94018 Troina Italy

Assistive Technology helps to assess the daily living and safety of frail people, with particular regards to the detection and prevention of falls. In this paper, a comparison is provided among different strategies to analyze postural sway, with the aim of detecting unstable postural status in standing condition as precursors of potential falls. Three approaches are considered: (i) a time-based features threshold algorithm, (ii) a time-based features Neuro-Fuzzy inference system, and (iii) a Neuro-Fuzzy inference fed by Discrete-Wavelet-Transform-based features. The analysis was performed across a wide dataset and exploited performance indexes aimed at assessing the accuracy and the reliability of predictions provided by the above-mentioned strategies. The results obtained demonstrate valuable performances of the three considered strategies in correctly distinguishing among stable and unstable postural status. However, the analysis of robustness against noisy data highlights better performance of Neuro-Fuzzy inference systems with respect to the threshold-based algorithm.

关键词： postural stability wearable devices accelerometer threshold algorithm Neuro-Fuzzy inference Discrete Wavelet Transform

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