Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631748
Motoi Shirai, Sumika Omata, T. Sugiyama
Spectrum suppressed transmission that increases the frequency utilization efficiency (throughput / required bandwidth) by suppressing the required bandwidth (3dB bandwidth) has been proposed to solve the frequency band exhaustion. However, in spectrum suppressed transmission, transmission quality degrades due to ISI (Inter Symbol Interference) caused by suppressing the required bandwidth to less than the Nyquist bandwidth. In this paper, in order to further improve transmission quality degradation and frequency utilization efficiency, we have proposed spectrum suppressed transmission applying MLD (Maximum Likelihood Detection) in addition to a powerful FEC (forward error correction). Then, we have quantitatively evaluated bit error rate performances and the frequency utilization efficiency in the proposed scheme by computer simulations.
{"title":"Frequency Utilization Efficiency Improvement by Using MLD in Spectrum Suppressed Transmission","authors":"Motoi Shirai, Sumika Omata, T. Sugiyama","doi":"10.1109/ICSPCS.2018.8631748","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631748","url":null,"abstract":"Spectrum suppressed transmission that increases the frequency utilization efficiency (throughput / required bandwidth) by suppressing the required bandwidth (3dB bandwidth) has been proposed to solve the frequency band exhaustion. However, in spectrum suppressed transmission, transmission quality degrades due to ISI (Inter Symbol Interference) caused by suppressing the required bandwidth to less than the Nyquist bandwidth. In this paper, in order to further improve transmission quality degradation and frequency utilization efficiency, we have proposed spectrum suppressed transmission applying MLD (Maximum Likelihood Detection) in addition to a powerful FEC (forward error correction). Then, we have quantitatively evaluated bit error rate performances and the frequency utilization efficiency in the proposed scheme by computer simulations.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123860071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631779
A. Bashar, Nazeeruddin Mohammad, Shahabuddin Muhammed
The proliferation of cloud technologies hosting complex applications has taken availability, scalability and affordabil-ity of IT services to the next level. Live VM migration is one of the core tools that automates the process of workload transfer without interfering with the applications running in dynamic cloud environments. In this paper we propose and implement a probabilistic model checking framework to study live VM migration process. In particular, we modeled well-known precopy live migration approach and evaluated the influence of various system parameters on the performance of live migration. The proposed implementation can be used as a stepping stone for modeling more complex live migration scenarios, and it can be a very beneficial tool for cloud service providers in predetermining various critical performance parameters of their cloud data centers in relation to the optimized utilization of the valuable IT resources.
{"title":"Modeling and Evaluation of Pre-Copy Live VM Migration Using Probabilistic Model Checking","authors":"A. Bashar, Nazeeruddin Mohammad, Shahabuddin Muhammed","doi":"10.1109/ICSPCS.2018.8631779","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631779","url":null,"abstract":"The proliferation of cloud technologies hosting complex applications has taken availability, scalability and affordabil-ity of IT services to the next level. Live VM migration is one of the core tools that automates the process of workload transfer without interfering with the applications running in dynamic cloud environments. In this paper we propose and implement a probabilistic model checking framework to study live VM migration process. In particular, we modeled well-known precopy live migration approach and evaluated the influence of various system parameters on the performance of live migration. The proposed implementation can be used as a stepping stone for modeling more complex live migration scenarios, and it can be a very beneficial tool for cloud service providers in predetermining various critical performance parameters of their cloud data centers in relation to the optimized utilization of the valuable IT resources.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122512909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631725
Dorian House, M. Lech, Melissa N. Stolar
Solar photovoltaic (PV) installation businesses frequently encounter problems with lead generation. A commonly used approach to identify credible customers involves cold-calling contacts from a purchased database containing very limited information or information that is inaccurate, out of date, and doesn't identify whether the building already has solar PV installed. This process of contacting potential customers, therefore, is often time-consuming, cost-ineffective, and inefficient, which results in increased costs for customers to account for these limitations. The objective of the current research project is to propose a method of automating this industry problem by applying Deep Neural Networks (DNNs). A Semantic Segmentation Network (SegNet) will be utilized, with a database of satellite images and corresponding pixel label images. The SegN et will seek to identify buildings from satellite imagery, and to in turn identify whether buildings have pre-existing solar installations, using a cascaded Convolutional Neural Network (CNN). Transfer learning on the CNN will fine-tune the network to classify roofs of buildings into two categories of having solar PV installed and not having solar PV installed. The CNN will be trained and tested on separate augmented databases to improve the classification accuracy with the output of the system recording a database of buildings without solar PV installed. By automating what was previously a time-consuming manual process, the savings incurred can be passed onto customers. Results of the current project demonstrate successful segmentation of buildings and identification of pre-existing solar PV installations. Implications of results are discussed.
{"title":"Using Deep Learning to Identify Potential Roof Spaces for Solar Panels","authors":"Dorian House, M. Lech, Melissa N. Stolar","doi":"10.1109/ICSPCS.2018.8631725","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631725","url":null,"abstract":"Solar photovoltaic (PV) installation businesses frequently encounter problems with lead generation. A commonly used approach to identify credible customers involves cold-calling contacts from a purchased database containing very limited information or information that is inaccurate, out of date, and doesn't identify whether the building already has solar PV installed. This process of contacting potential customers, therefore, is often time-consuming, cost-ineffective, and inefficient, which results in increased costs for customers to account for these limitations. The objective of the current research project is to propose a method of automating this industry problem by applying Deep Neural Networks (DNNs). A Semantic Segmentation Network (SegNet) will be utilized, with a database of satellite images and corresponding pixel label images. The SegN et will seek to identify buildings from satellite imagery, and to in turn identify whether buildings have pre-existing solar installations, using a cascaded Convolutional Neural Network (CNN). Transfer learning on the CNN will fine-tune the network to classify roofs of buildings into two categories of having solar PV installed and not having solar PV installed. The CNN will be trained and tested on separate augmented databases to improve the classification accuracy with the output of the system recording a database of buildings without solar PV installed. By automating what was previously a time-consuming manual process, the savings incurred can be passed onto customers. Results of the current project demonstrate successful segmentation of buildings and identification of pre-existing solar PV installations. Implications of results are discussed.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121523253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631754
Yonggu Lee, E. Hwang, Jinho Choi
Advanced metering infrastructure (AMI) systems play a crucial role in smart grid, where smart meters have two-way communications to remotely send meter readings up on request. While wireless technologies are highly desirable for flexible, adaptable, and cost-effective smart metering deployments, there are a number of issues to be addressed in terms of security and privacy. In this paper, we study a compressive sensing (CS) based physical layer authentication scheme over a multicarrier system and analyze its security performance against impersonation attack. In particular, we derive conditional distributions for the hypothesis testing used in authentication. From them, we are able to guarantee security performances in terms of the probabilities of false alarm and authentication error.
{"title":"Performance Analysis of Compressive Sensing Based Physical Layer Authentication for AMI","authors":"Yonggu Lee, E. Hwang, Jinho Choi","doi":"10.1109/ICSPCS.2018.8631754","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631754","url":null,"abstract":"Advanced metering infrastructure (AMI) systems play a crucial role in smart grid, where smart meters have two-way communications to remotely send meter readings up on request. While wireless technologies are highly desirable for flexible, adaptable, and cost-effective smart metering deployments, there are a number of issues to be addressed in terms of security and privacy. In this paper, we study a compressive sensing (CS) based physical layer authentication scheme over a multicarrier system and analyze its security performance against impersonation attack. In particular, we derive conditional distributions for the hypothesis testing used in authentication. From them, we are able to guarantee security performances in terms of the probabilities of false alarm and authentication error.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127566220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631750
U. Elahi, Z. Khalid, R. Kennedy
Spherical microphone arrays sample the sound field on the sphere in both space and time. The performance of spherical microphone arrays is typically limited by spatial aliasing which introduces side-lobes in the array beam pattern. In order to reduce the aliasing error, anti-aliasing filters, both ideal and spatially constrained, have been presented in the literature. In this paper, we propose a slepian eigenfunction window which spatially truncate the ideal anti-aliasing filter used in literature to design a spatially constrained anti-aliasing filter. We also provide an illustration to show that the aliasing on the beam pattern is reduced by the use of the proposed anti-aliaisng filter and compare the results with the spatially constrained filters obtained by applying rectangular and hamming windows. Robustness analysis such as measurement of the white noise gain and directivity index shows the superiority of the proposed filter over other spatially constrained anti-aliasing filters.
{"title":"Spatially Constrained Anti-Aliasing Filter Using Slepian Eigenfunction Window on the Sphere","authors":"U. Elahi, Z. Khalid, R. Kennedy","doi":"10.1109/ICSPCS.2018.8631750","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631750","url":null,"abstract":"Spherical microphone arrays sample the sound field on the sphere in both space and time. The performance of spherical microphone arrays is typically limited by spatial aliasing which introduces side-lobes in the array beam pattern. In order to reduce the aliasing error, anti-aliasing filters, both ideal and spatially constrained, have been presented in the literature. In this paper, we propose a slepian eigenfunction window which spatially truncate the ideal anti-aliasing filter used in literature to design a spatially constrained anti-aliasing filter. We also provide an illustration to show that the aliasing on the beam pattern is reduced by the use of the proposed anti-aliaisng filter and compare the results with the spatially constrained filters obtained by applying rectangular and hamming windows. Robustness analysis such as measurement of the white noise gain and directivity index shows the superiority of the proposed filter over other spatially constrained anti-aliasing filters.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129231004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631726
Bhagya Nathali Silva, Murad Khan, Jihun Seo, Diyan Muhammad, Yongtak Yoon, Jihun Han, K. Han
The smart city notion facilitate interoperation among multiple disciplines to improve the Quality of Life (QoL) of urban citizens. Unceasingly growing urban networks has significantly increased the data processing complexity. In consequence, real-time data processing and analysis has become a major concern in modern smart city designing and implementation. Considering the challenges of existing smart cities, in this work we propose a smart city architecture embedded with Big Data Analytics (BDA). The utmost goal of the proposed scheme is to enhance the quality of real-time decision-making through efficient Big Data (BD) processing. The proposed architecture is in three folds to manage data collection, data processing, and data application. We evaluate the proposed BDA embedded smart city using authentic datasets on water consumption, traffic congestion, parking management, and air pollution measurements. The analysis offer useful insights for the community development, while ensuring the performance improvement of the proposed framework in terms of processing time and throughput.
{"title":"Exploiting Big Data Analytics for Urban Planning and Smart City Performance Improvement","authors":"Bhagya Nathali Silva, Murad Khan, Jihun Seo, Diyan Muhammad, Yongtak Yoon, Jihun Han, K. Han","doi":"10.1109/ICSPCS.2018.8631726","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631726","url":null,"abstract":"The smart city notion facilitate interoperation among multiple disciplines to improve the Quality of Life (QoL) of urban citizens. Unceasingly growing urban networks has significantly increased the data processing complexity. In consequence, real-time data processing and analysis has become a major concern in modern smart city designing and implementation. Considering the challenges of existing smart cities, in this work we propose a smart city architecture embedded with Big Data Analytics (BDA). The utmost goal of the proposed scheme is to enhance the quality of real-time decision-making through efficient Big Data (BD) processing. The proposed architecture is in three folds to manage data collection, data processing, and data application. We evaluate the proposed BDA embedded smart city using authentic datasets on water consumption, traffic congestion, parking management, and air pollution measurements. The analysis offer useful insights for the community development, while ensuring the performance improvement of the proposed framework in terms of processing time and throughput.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131658878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631783
Lina Xu
Multiple-In-Multiple-Out (MIMO) technologies have been widely deployed in order to realise 5G communication goals. Due to the large coverage and fast speed, cellular involved IoT backhaul with MIMO capability is becoming a popular approach adopted by many Internet of Things (IoT) systems. With more communication interfaces available, it is easy to see that the system will consume more energy. If considering network coverage is the most critical metric for an IoT system, and then the problem is: is MIMO always necessary and beneficial? Our argument is that the answer is highly depending on the deployment and applications. Through the demonstration of the management of Smart-BEEM, this paper has investigated the impact of MIMO on the network coverage. The results have revealed that the gain that MIMO can bring to an IoT network coverage highly depends on the energy cost for idle listening. Without proper sleeping scheduling mode implemented on the devices, using MIMO may undermine the overall network coverage. In an IoT network with specific tasks, involving massive communication interfaces may cause redundant communication capability problem and waste energy from unnecessary idle listening.
{"title":"The Impact of MIMO on IoT Network Coverage: Case Study with Smart-BEEM","authors":"Lina Xu","doi":"10.1109/ICSPCS.2018.8631783","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631783","url":null,"abstract":"Multiple-In-Multiple-Out (MIMO) technologies have been widely deployed in order to realise 5G communication goals. Due to the large coverage and fast speed, cellular involved IoT backhaul with MIMO capability is becoming a popular approach adopted by many Internet of Things (IoT) systems. With more communication interfaces available, it is easy to see that the system will consume more energy. If considering network coverage is the most critical metric for an IoT system, and then the problem is: is MIMO always necessary and beneficial? Our argument is that the answer is highly depending on the deployment and applications. Through the demonstration of the management of Smart-BEEM, this paper has investigated the impact of MIMO on the network coverage. The results have revealed that the gain that MIMO can bring to an IoT network coverage highly depends on the energy cost for idle listening. Without proper sleeping scheduling mode implemented on the devices, using MIMO may undermine the overall network coverage. In an IoT network with specific tasks, involving massive communication interfaces may cause redundant communication capability problem and waste energy from unnecessary idle listening.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116664189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631759
Keith Hermiston
Latin squares are combinatorial constructions that have found widespread application in communication systems through frequency hopping designs, error correcting codes and encryption algorithms. In this paper, a new, lower bound on the cardinality of the critical sets of all Latin squares of order n is shown to be Ω(n!(n-3)!) where Ω is the summatory prime factorisation function (with multiplicities). The proof draws on the direct product of the symmetric groups Sn and Sn-3. The smallest critical set cardinalities of the new bound align with its known, calculated values and reduce previously proven bounds for n > 8. The proof refutes the long standing Nelder conjecture.
{"title":"The Smallest Critical Sets of Latin Squares","authors":"Keith Hermiston","doi":"10.1109/ICSPCS.2018.8631759","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631759","url":null,"abstract":"Latin squares are combinatorial constructions that have found widespread application in communication systems through frequency hopping designs, error correcting codes and encryption algorithms. In this paper, a new, lower bound on the cardinality of the critical sets of all Latin squares of order n is shown to be Ω(n!(n-3)!) where Ω is the summatory prime factorisation function (with multiplicities). The proof draws on the direct product of the symmetric groups Sn and Sn-3. The smallest critical set cardinalities of the new bound align with its known, calculated values and reduce previously proven bounds for n > 8. The proof refutes the long standing Nelder conjecture.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115192488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631761
Q. Chaudhari
In the digital domain, a Square-Root Raised Cosine Filter (SRRC) has historically been used in most of the wireless standards for shaping the spectrum at the Tx and matched filtering the signal at the Rx (the combination forms a Raised Cosine (RC) filter). However, the performance of an SRRC filter in terms of peak ISI and peak sidelobe attenuation is fairly average, to say the least. A transformed lowpass filter designed according to Parks-McClellan algorithm is an alternative pulse shaping technique which is generally believed to be optimal due to the lowpass filter coefficients being the optimal solution based on Remez exchange algorithm and Chebyshev approximation theory such that the maximum error between the desired and the actual frequency response is minimized. In this paper, we show that another technique proposed in [3] based on an optimized frequency domain window convolved with a rectangular spectrum matches fairly well against the lowpass filter based method at all instances in terms of peak ISI and sidelobe attenuation.
{"title":"A Case for Frequency Domain Window Based Nyquist Filter Design","authors":"Q. Chaudhari","doi":"10.1109/ICSPCS.2018.8631761","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631761","url":null,"abstract":"In the digital domain, a Square-Root Raised Cosine Filter (SRRC) has historically been used in most of the wireless standards for shaping the spectrum at the Tx and matched filtering the signal at the Rx (the combination forms a Raised Cosine (RC) filter). However, the performance of an SRRC filter in terms of peak ISI and peak sidelobe attenuation is fairly average, to say the least. A transformed lowpass filter designed according to Parks-McClellan algorithm is an alternative pulse shaping technique which is generally believed to be optimal due to the lowpass filter coefficients being the optimal solution based on Remez exchange algorithm and Chebyshev approximation theory such that the maximum error between the desired and the actual frequency response is minimized. In this paper, we show that another technique proposed in [3] based on an optimized frequency domain window convolved with a rectangular spectrum matches fairly well against the lowpass filter based method at all instances in terms of peak ISI and sidelobe attenuation.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124282356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631760
Christina Kozia, R. Herzallah, D. Lowe
Respiration Rate (RR) is an important physiological indicator and plays a major role in health deterioration monitoring. Despite that, it has been neglected in hospital wards due to inadequate nursing skills and insufficient equipment. ECG signal, which is always monitored in a clinical setting, is modulated by respiration which renders it a highly enticing mean for the automatic RR estimation. In addition, accurate QRS detection is pivotal to RR estimation from the ECG signal. The investigation of QRS complexes is a continuing concern in ECG analysis because current methods are still inaccurate and miss heart beats. This paper presents a frequency domain RR estimation method which uses a novel real-time QRS detector based on Empirical Mode Decomposition (EMD). Another novelty of the proposed work stems from the RR estimation in the frequency domain as opposed to some of the current methods which rely on a time domain analysis. As will be shown later, the RR extraction in the frequency domain provides more accurate results compared to the time domain methods. Moreover, our novel QRS detector uses an adaptive threshold over a sliding window and differentiates large Q- from R-peaks, facilitating a more accurate RR estimation. The performance of our methods was tested on real data from Capnobase dataset. An average mean absolute error of less than 0.5 breath per minute was achieved using our frequency domain method, compared to 6 breaths per minute of the time domain analysis. Moreover, our modified QRS detector shows comparable results to other published methods. achieving a detection rate over 99.80%.
{"title":"ECG-Derived Respiration Using a Real-Time QRS Detector Based on Empirical Mode Decomposition","authors":"Christina Kozia, R. Herzallah, D. Lowe","doi":"10.1109/ICSPCS.2018.8631760","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631760","url":null,"abstract":"Respiration Rate (RR) is an important physiological indicator and plays a major role in health deterioration monitoring. Despite that, it has been neglected in hospital wards due to inadequate nursing skills and insufficient equipment. ECG signal, which is always monitored in a clinical setting, is modulated by respiration which renders it a highly enticing mean for the automatic RR estimation. In addition, accurate QRS detection is pivotal to RR estimation from the ECG signal. The investigation of QRS complexes is a continuing concern in ECG analysis because current methods are still inaccurate and miss heart beats. This paper presents a frequency domain RR estimation method which uses a novel real-time QRS detector based on Empirical Mode Decomposition (EMD). Another novelty of the proposed work stems from the RR estimation in the frequency domain as opposed to some of the current methods which rely on a time domain analysis. As will be shown later, the RR extraction in the frequency domain provides more accurate results compared to the time domain methods. Moreover, our novel QRS detector uses an adaptive threshold over a sliding window and differentiates large Q- from R-peaks, facilitating a more accurate RR estimation. The performance of our methods was tested on real data from Capnobase dataset. An average mean absolute error of less than 0.5 breath per minute was achieved using our frequency domain method, compared to 6 breaths per minute of the time domain analysis. Moreover, our modified QRS detector shows comparable results to other published methods. achieving a detection rate over 99.80%.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123400918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：