scholarly journals A Computational Framework for Data Fusion in MEMS-Based Cardiac and Respiratory Gating

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4137 ◽  
Author(s):  
Mojtaba Jafari Tadi ◽  
Eero Lehtonen ◽  
Jarmo Teuho ◽  
Juho Koskinen ◽  
Jussi Schultz ◽  
...  
Keyword(s):  
Data Fusion ◽  
Cardiac Cycle ◽  
Respiratory Gating ◽  
Component Analysis ◽  
Cardiac Motion ◽  
Future Research ◽  
Time Interval ◽  
Strong Positive Correlation ◽  
Prospective Gating ◽  
Dual Sensor

Dual cardiac and respiratory gating is a well-known technique for motion compensation in nuclear medicine imaging. In this study, we present a new data fusion framework for dual cardiac and respiratory gating based on multidimensional microelectromechanical (MEMS) motion sensors. Our approach aims at robust estimation of the chest vibrations, that is, high-frequency precordial vibrations and low-frequency respiratory movements for prospective gating in positron emission tomography (PET), computed tomography (CT), and radiotherapy. Our sensing modality in the context of this paper is a single dual sensor unit, including accelerometer and gyroscope sensors to measure chest movements in three different orientations. Since accelerometer- and gyroscope-derived respiration signals represent the inclination of the chest, they are similar in morphology and have the same units. Therefore, we use principal component analysis (PCA) to combine them into a single signal. In contrast to this, the accelerometer- and gyroscope-derived cardiac signals correspond to the translational and rotational motions of the chest, and have different waveform characteristics and units. To combine these signals, we use independent component analysis (ICA) in order to obtain the underlying cardiac motion. From this cardiac motion signal, we obtain the systolic and diastolic phases of cardiac cycles by using an adaptive multi-scale peak detector and a short-time autocorrelation function. Three groups of subjects, including healthy controls (n = 7), healthy volunteers (n = 12), and patients with a history of coronary artery disease (n = 19) were studied to establish a quantitative framework for assessing the performance of the presented work in prospective imaging applications. The results of this investigation showed a fairly strong positive correlation (average r = 0.73 to 0.87) between the MEMS-derived (including corresponding PCA fusion) respiration curves and the reference optical camera and respiration belt sensors. Additionally, the mean time offset of MEMS-driven triggers from camera-driven triggers was 0.23 to 0.3 ± 0.15 to 0.17 s. For each cardiac cycle, the feature of the MEMS signals indicating a systolic time interval was identified, and its relation to the total cardiac cycle length was also reported. The findings of this study suggest that the combination of chest angular velocity and accelerations using ICA and PCA can help to develop a robust dual cardiac and respiratory gating solution using only MEMS sensors. Therefore, the methods presented in this paper should help improve predictions of the cardiac and respiratory quiescent phases, particularly with the clinical patients. This study lays the groundwork for future research into clinical PET/CT imaging based on dual inertial sensors.

scholarly journals Measuring Walkability with Street Connectivity and Physical Activity: A Case Study in Iran

World ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 49-61
Author(s):  
Pouya Molaei ◽  
Liyaning Tang ◽  
Mary Hardie
Keyword(s):  
Physical Activity ◽  
Urban Areas ◽  
International Physical Activity Questionnaire ◽  
Physical Activities ◽  
Future Research ◽  
Strong Positive Correlation ◽  
Street Connectivity ◽  
Walking Time ◽  
Activity Questionnaire

The walkability of urban areas is an important criterion related to the level of physical activity and public health of citizens. This research aims to measure this parameter in Golsar town located in Rasht, Iran. Two methods were used in this research: Street connectivity and International Physical Activity Questionnaire (IPAQ). The principal variables of street connectivity were measured in four districts of Golsar by Geographic Information System (GIS) to rank each one. Then, the acquired results were compared by the average walking time of the respondents of the questionnaire. The comparison explicitly indicated that there is a strong positive correlation between the measures of street connectivity and people’s tendency to walk. As well, District 1 had the highest value of connectivity and the highest average time for walking amongst the four districts. This supports the contention that walkability and the level of outdoor physical activities of people in each district are undoubtedly under the influence of the variables of street connectivity. Nevertheless, the evaluation of other indexes such as proximity, land use mix, safety, and density in Golsar, in future research. can expand our perception of the walkability of this region.

scholarly journals A Review on Remote Sensing Data Fusion with Generative Adversarial Networks (GAN)

2021 ◽  
Author(s):  
Peng Liu
Keyword(s):  
Remote Sensing ◽  
Data Fusion ◽  
Remote Sensing Data ◽  
Generative Adversarial Networks ◽  
Future Research ◽  
Observation Data ◽  
Sensing Data ◽  
Advantages And Disadvantages ◽  
Adversarial Networks ◽  
Active Research

In the past decades, remote sensing (RS) data fusion has always been an active research community. A large number of algorithms and models have been developed. Generative Adversarial Networks (GAN), as an important branch of deep learning, show promising performances in variety of RS image fusions. This review provides an introduction to GAN for remote sensing data fusion. We briefly review the frequently-used architecture and characteristics of GAN in data fusion and comprehensively discuss how to use GAN to realize fusion for homogeneous RS data, heterogeneous RS data, and RS and ground observation data. We also analyzed some typical applications with GAN-based RS image fusion. This review takes insight into how to make GAN adapt to different types of fusion tasks and summarizes the advantages and disadvantages of GAN-based RS data fusion. Finally, we discuss the promising future research directions and make a prediction on its trends.

Investigating the adoption of social media in the construction industry: empirical evidence from project teams in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guofeng Ma ◽  
Shan Jiang ◽  
Jianyao Jia
Keyword(s):  
Social Media ◽  
Project Management ◽  
Environmental Factors ◽  
Construction Industry ◽  
Structural Equation ◽  
Project Teams ◽  
Equation Modeling ◽  
Future Research ◽  
Time Interval ◽  
Content Type

PurposeA lack of reliable and effective communication tools poses major barriers impeding the performance of construction projects consisting of diverse participants. Although some construction project teams (CPTs) begin to apply social media (SM) as an available approach for project management the entire mechanism of SM adoption in this specific context remains understudied. Therefore, this study aims to adopt a CPT's lens to investigate the critical antecedents and associated effects underlying SM adoption in the construction industry.Design/methodology/approachBased on the technology–organization–environment (TOE) theory, a conceptual model was proposed and tested by empirical data collected from 159 CPTs in China. Structural equation modeling technique was employed for data analysis.FindingsThe results demonstrate that all the five extracted TOE-based antecedents including two technological factors (i.e. compatibility and expected cost), one organizational factor (i.e. top management support) and two environmental factors (i.e. project partner collaboration and project fit) are crucial to the adoption of SM in CPTs. Besides, SM acceptance is found to mediate the relationships between organizational and environmental factors and SM use. Moreover, SM use significantly predicts the communication effectiveness of CPTs.Research limitations/implicationsA questionnaire study based on cross-sectional data from China may only unveil the logic of SM adoption in the context of Chinese construction industry within a shorter time interval. It is recommended that future research could develop longitudinal studies among various construction practitioners in different countries to further specify and generalize the current findings.Originality/valueThis paper provides a comprehensive understanding of SM adoption in the construction industry by exploring the preadoption antecedents and postadoption effects from the perspective of project teams. The empirical findings advance the current web-based project management literature and afford new insights for construction practitioners into better managing SM application to reap its full capabilities in projects.

scholarly journals Information Fusion for Multi-Source Material Data: Progress and Challenges

2019 ◽  
Vol 9 (17) ◽  
pp. 3473 ◽  
Author(s):  
Zhou ◽  
Hong ◽  
Jin
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Data Fusion ◽  
Manufacturing Industry ◽  
Data Representation ◽  
Source Material ◽  
Future Research ◽  
Unified Framework ◽  
Open Problems ◽  
Material Data

The development of material science in the manufacturing industry has resulted in a huge amount of material data, which are often from different sources and vary in data format and semantics. The integration and fusion of material data can offer a unified framework for material data representation, processing, storage and mining, which can further help to accomplish many tasks, including material data disambiguation, material feature extraction, material-manufacturing parameters setting, and material knowledge extraction. On the other side, the rapid advance of information technologies like artificial intelligence and big data, brings new opportunities for material data fusion. To the best of our knowledge, the community is currently lacking a comprehensive review of the state-of-the-art techniques on material data fusion. This review first analyzes the special properties of material data and discusses the motivations of multi-source material data fusion. Then, we particularly focus on the recent achievements of multi-source material data fusion. This review has a few unique features compared to previous studies. First, we present a systematic categorization and comparison framework for material data fusion according to the processing flow of material data. Second, we discuss the applications and impact of recent hot technologies in material data fusion, including artificial intelligence algorithms and big data technologies. Finally, we present some open problems and future research directions for multi-source material data fusion.

MR Measurement of Pulse Wave Velocity in the Spinal Canal

2008 ◽  
Author(s):  
Bryn A. Martin ◽  
Francis Loth ◽  
Wojciech Kalata ◽  
John N. Oshinski
Keyword(s):  
Pulse Wave Velocity ◽  
Wave Velocity ◽  
Velocity Gradient ◽  
Cardiac Cycle ◽  
Pulse Wave ◽  
Sagittal Plane ◽  
Maximum Velocity ◽  
Time Shift ◽  
Time Interval ◽  
Velocity Measurements

Non-invasive measurement of pulse wave velocity (PWV) in the cerebrospinal fluid (CSF) system is of interest as a potential indicator of subarachnoid space pressure and compliance, both of which play a role in the development of craniospinal diseases. However, measurement of PWV has eluded researchers primarily due to either a lack of access to CSF velocity measurements or to poor temporal resolution. Here, we present PWV measurements using a novel MR technique that acquires unsteady velocity measurements during the cardiac cycle with a time interval <10 ms. Axial CSF velocity measurements were obtained in the sagittal plane of the cervical spinal region on three patients without cranio-spinal disorders. PWV was estimated by using the time shift identified by the maximum temporal velocity gradient during the cardiac cycle. Based on the maximum velocity gradient, the mean PWV in the three cases was calculated to be 4.6 m/s (stdev 1.7 m/s, p<0.005) during systolic acceleration. The measurements of PWV agree with previously published values.

P6544A real world study of high frequency atrial anti-tachycardia pacing in new algorithm for atrial arrhythmia

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M Fukunaga ◽  
T Morinaga ◽  
K Yamaji ◽  
M Nagashima ◽  
K Ando
Keyword(s):  
Real World ◽  
Atrial Arrhythmia ◽  
Independent Effect ◽  
Future Research ◽  
Time Interval ◽  
Single Episode ◽  
Preventive Pacing ◽  
Cardiac Devices ◽  
The Impact

Abstract Background Advanced pacemakers feature atrial antitachycardia pacing (aATP) therapies for terminating atrial arrhythmia. Previous studies showed the efficacy of combined atrial preventive pacing and aATP in patients with pacemakers. The independent effect of aATP and the impact for patients outside the clinical trials has not been well elucidated. Methods In a single center, prospective, all-comers trial, we enrolled 567 patients implanted cardiac devices with Reactive ATP function. History of permanent atrial fibrillation (AF) was not included. After device interrogation of the AF burden and the longest AF duration in the last 6 months, aATP was programmed as a bit more aggressive setting than MINERVA trial (time interval was set as every 2 hours). As for newly implanted devices, aATP was activated after at least 3 months run-in period. Primary and secondary outcomes were the longest AF duration and cumulative percentage of progression into permanent AF, respectively. Results Of 541 eligible patients, aged 75.3±10.7 years, 356 pacemaker, 82 ICD and 103 CRT patients, the longest single episode of AF lasted ≤6 min in 439 patients (81.1%), >6 min to 6 h in 43 (8.0%), >6–24 h in 33 (6.1%), and >24 h in 26 (4.8%) at the enrollment. During mean follow-up of 1.9 years, the longest AF episode lasted >24 h in 49 patients (9.1%) and 14 patients (2.6%) progressed into permanent AF. According with baseline longest single episode of AF, patients with AF ≤6 min developed an episode >24 h in 0.8% at 1 year and 3.2% at 2 years follow up; patients with AF >6 min to 6 h developed an episode >24 h in none at 1 year and 7% at 2 years follow up; and patients with AF >6–24 h developed an episode >24 h in 19% at 1 year and 42% at 2 years follow up, respectively. In a subgroup analysis of in 192 patients with at least 1 aATP, 46 patients with high efficacy (>44%) did not developed an episode >24 h. Only one patient developed into permanent AF without aATP therapy. On multivariate analysis, neither ICD nor CRT was independent risk factor for developing the longest AF episode >24 h. Conclusions The independent use of aATP without atrial preventive pacing was effective for preventing AF progression in a real world cohort. Even without the previous AF episodes, aATP could prevent AF development, especially in patients showing high aATP efficacy. Future research is required to enhance the aATP success rate.

Effects of the characteristics of online multimedia synergy on consumers’ message acceptance and message response

2017 ◽  
Vol 41 (5) ◽  
pp. 710-727 ◽  
Author(s):  
Xuebing Dong ◽  
Yaping Chang ◽  
Xiaojun Fan
Keyword(s):  
Information Seeking ◽  
Moderating Effect ◽  
Future Research ◽  
Online Media ◽  
Time Interval ◽  
Least Squares Regression ◽  
Sources Of Information ◽  
Content Type ◽  
Perceived Credibility ◽  
Message Acceptance

Purpose Marketers recognize that the internet is crucial in the lives of consumers; thus, they invest money on online advertisements. Using multiple online media primarily influences the message acceptance of consumers. The synergistic effect of online multimedia relies on form, content, and sources of information, and time. The paper aims to discuss these issues. Design/methodology/approach A model that reflects the influence of the characteristics of online multimedia on message response through message acceptance is established based on theories of information persuasion, encoding variability, and multiple-source assumption. Based on a survey of 411 online media users, the study applies partial least-squares regression to test the research model. Findings The results show that variety of forms, complementary of contents, diversity of sources, and time interval influence message response via message strength. Complementary of contents and diversity of sources affect message response via perceived credibility. Synergy type moderates the relationship between variety of forms and perceived credibility and between diversity of sources and perceived credibility. Research limitations/implications The current study mainly tests the effect of these characteristics on message response and the moderating effect of synergy type. Future research can examine the effect of these characteristics on information seeking and consumption behavior and the moderating effect of the cognitive mode of consumers. Practical implications This study provides insight into the characteristics of synergy and contributes to the literature on integrated marketing communication. The results provide guidance for practitioners to effectively plan online multimedia practices. Originality/value This study explored the influence of the characteristics of online media synergy on message response through message acceptance. The study also discussed the moderating effect of the type of online multimedia synergy.

Understanding variation in the timeliness of diagnosis of cancer in symptomatic patients.

2014 ◽  
Vol 32 (30_suppl) ◽  
pp. 301-301
Author(s):  
Georgios Lyratzopoulos
Keyword(s):  
Primary Care ◽  
Family Doctor ◽  
Patient Characteristics ◽  
Care Physician ◽  
Future Research ◽  
Time Interval ◽  
Stage At Diagnosis ◽  
Specialist Referral ◽  
Diagnosis Of Cancer ◽  
Diagnostic Intervals

301 Background: Diagnosing cancer promptly in symptomatic patients is a priority for healthcare systems worldwide, but little is known about how initiatives can be targeted to patients at greater risk. Methods: UK data on the number of consultations with a family doctor before specialist referral (‘pre-referral consultations’); the time interval from presentation to referral (‘primary care interval’); and stage at diagnosis, were analysed using multivariable regression models. Results: Both patient experience (41,299 patients, 24 cancers) and clinical audit (13,031 patients, 18 cancers) data indicated wide variation in two correlated measures* of the difficulty of suspecting the diagnosis of cancer once the patient had presented to their family doctor. For example, >30% of patients with multiple myeloma, pancreatic and lung cancer experienced three or more pre-referral consultations; in contrast, this was true for <10% of patients with breast cancer and melanoma (p<0.001). Adjusting for diagnostic case-mix, younger and ethnic minority patients, and women, were more likely to experience three or more pre-referral consultations. Data from 88,657 patients (10 cancers) suggested socio-demographic disparities in stage at diagnosis for some only cancers: For patients with melanoma, breast and endometrial cancer, lower socioeconomic status was associated with higher risk of advanced stage at diagnosis and for, these three cancers, the same was true for older age. Conclusions: Different diagnostic intervals vary widely by cancer diagnosis and patient characteristics. Notable disparities in stage at diagnosis are apparent for ‘easy-to-suspect’ cancers (which are associated with minimal delay post-presentation), strongly implicating psychosocial patient factors as the source of these disparities. These findings can help to appropriately target early diagnosis policy initiatives and future research to patients at greater risk of prolonged diagnostic intervals. *Number of pre-referral consultations with a primary care physician and length of primary care interval (Spearman’s r=0.70).

scholarly journals Aortic root dynamics and surgery: from craft to science

2007 ◽  
Vol 362 (1484) ◽  
pp. 1407-1419 ◽  
Author(s):  
Allen Cheng ◽  
Paul Dagum ◽  
D. Craig Miller
Keyword(s):  
Aortic Valve ◽  
Fifteenth Century ◽  
Aortic Root ◽  
Cardiac Cycle ◽  
Three Dimensional ◽  
Future Research ◽  
Root Dynamics ◽  
Post Intervention ◽  
Structural Valve Deterioration ◽  
Root Deformation

Since the fifteenth century beginning with Leonardo da Vinci's studies, the precise structure and functional dynamics of the aortic root throughout the cardiac cycle continues to elude investigators. The last five decades of experimental work have contributed substantially to our current understanding of aortic root dynamics. In this article, we review and summarize the relevant structural analyses, using radiopaque markers and sonomicrometric crystals, concerning aortic root three-dimensional deformations and describe aortic root dynamics in detail throughout the cardiac cycle. We then compare data between different studies and discuss the mechanisms responsible for the modes of aortic root deformation, including the haemodynamics, anatomical and temporal determinants of those deformations. These modes of aortic root deformation are closely coupled to maximize ejection, optimize transvalvular ejection haemodynamics and—perhaps most importantly—reduce stress on the aortic valve cusps by optimal diastolic load sharing and minimizing transvalvular turbulence throughout the cardiac cycle. This more comprehensive understanding of aortic root mechanics and physiology will contribute to improved medical and surgical treatment methods, enhanced therapeutic decision making and better post-intervention care of patients. With a better understanding of aortic root physiology, future research on aortic valve repair and replacement should take into account the integrated structural and functional asymmetry of aortic root dynamics to minimize stress on the aortic cusps in order to prevent premature structural valve deterioration.

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