scholarly journals Considerations for integration of a physiological radar monitoring system with gold standard clinical sleep monitoring systems

2013 ◽  
Author(s):  
Aditya Singh ◽  
Mehran Baboli ◽  
Xiaomeng Gao ◽  
Ehsan Yavari ◽  
Bryson Padasdao ◽  
...  
Keyword(s):  
Monitoring System ◽  
Gold Standard ◽  
Monitoring Systems ◽  
Sleep Monitoring ◽  
Radar Monitoring

scholarly journals Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review

10.2196/20921 ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. e20921
Author(s):  
Qiang Pan ◽  
Damien Brulin ◽  
Eric Campo
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Monitoring System ◽  
The Body ◽  
Monitoring Systems ◽  
Sleep Monitoring ◽  
Advantages And Disadvantages ◽  
System Solution

Background Sleep is essential for human health. Considerable effort has been put into academic and industrial research and in the development of wireless body area networks for sleep monitoring in terms of nonintrusiveness, portability, and autonomy. With the help of rapid advances in smart sensing and communication technologies, various sleep monitoring systems (hereafter, sleep monitoring systems) have been developed with advantages such as being low cost, accessible, discreet, contactless, unmanned, and suitable for long-term monitoring. Objective This paper aims to review current research in sleep monitoring to serve as a reference for researchers and to provide insights for future work. Specific selection criteria were chosen to include articles in which sleep monitoring systems or devices are covered. Methods This review investigates the use of various common sensors in the hardware implementation of current sleep monitoring systems as well as the types of parameters collected, their position in the body, the possible description of sleep phases, and the advantages and drawbacks. In addition, the data processing algorithms and software used in different studies on sleep monitoring systems and their results are presented. This review was not only limited to the study of laboratory research but also investigated the various popular commercial products available for sleep monitoring, presenting their characteristics, advantages, and disadvantages. In particular, we categorized existing research on sleep monitoring systems based on how the sensor is used, including the number and type of sensors, and the preferred position in the body. In addition to focusing on a specific system, issues concerning sleep monitoring systems such as privacy, economic, and social impact are also included. Finally, we presented an original sleep monitoring system solution developed in our laboratory. Results By retrieving a large number of articles and abstracts, we found that hotspot techniques such as big data, machine learning, artificial intelligence, and data mining have not been widely applied to the sleep monitoring research area. Accelerometers are the most commonly used sensor in sleep monitoring systems. Most commercial sleep monitoring products cannot provide performance evaluation based on gold standard polysomnography. Conclusions Combining hotspot techniques such as big data, machine learning, artificial intelligence, and data mining with sleep monitoring may be a promising research approach and will attract more researchers in the future. Balancing user acceptance and monitoring performance is the biggest challenge in sleep monitoring system research.

Good Night: Sleep Monitoring Using a Physiological Radar Monitoring System Integrated with a Polysomnography System

2015 ◽  
Vol 16 (6) ◽  
pp. 34-41 ◽  
Author(s):  
Mehran Baboli ◽  
Aditya Singh ◽  
Bruce Soll ◽  
Olga Boric-Lubecke ◽  
Victor M. Lubecke
Keyword(s):  
Monitoring System ◽  
Night Sleep ◽  
Sleep Monitoring ◽  
Good Night ◽  
Radar Monitoring

scholarly journals Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review (Preprint)

2020 ◽  
Author(s):  
Qiang Pan ◽  
Damien Brulin ◽  
Eric Campo
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Monitoring System ◽  
The Body ◽  
Monitoring Systems ◽  
Sleep Monitoring ◽  
Advantages And Disadvantages ◽  
System Solution

BACKGROUND Sleep is essential for human health. Considerable effort has been put into academic and industrial research and in the development of wireless body area networks for sleep monitoring in terms of nonintrusiveness, portability, and autonomy. With the help of rapid advances in smart sensing and communication technologies, various sleep monitoring systems (hereafter, sleep monitoring systems) have been developed with advantages such as being low cost, accessible, discreet, contactless, unmanned, and suitable for long-term monitoring. OBJECTIVE This paper aims to review current research in sleep monitoring to serve as a reference for researchers and to provide insights for future work. Specific selection criteria were chosen to include articles in which sleep monitoring systems or devices are covered. METHODS This review investigates the use of various common sensors in the hardware implementation of current sleep monitoring systems as well as the types of parameters collected, their position in the body, the possible description of sleep phases, and the advantages and drawbacks. In addition, the data processing algorithms and software used in different studies on sleep monitoring systems and their results are presented. This review was not only limited to the study of laboratory research but also investigated the various popular commercial products available for sleep monitoring, presenting their characteristics, advantages, and disadvantages. In particular, we categorized existing research on sleep monitoring systems based on how the sensor is used, including the number and type of sensors, and the preferred position in the body. In addition to focusing on a specific system, issues concerning sleep monitoring systems such as privacy, economic, and social impact are also included. Finally, we presented an original sleep monitoring system solution developed in our laboratory. RESULTS By retrieving a large number of articles and abstracts, we found that hotspot techniques such as big data, machine learning, artificial intelligence, and data mining have not been widely applied to the sleep monitoring research area. Accelerometers are the most commonly used sensor in sleep monitoring systems. Most commercial sleep monitoring products cannot provide performance evaluation based on gold standard polysomnography. CONCLUSIONS Combining hotspot techniques such as big data, machine learning, artificial intelligence, and data mining with sleep monitoring may be a promising research approach and will attract more researchers in the future. Balancing user acceptance and monitoring performance is the biggest challenge in sleep monitoring system research.

scholarly journals Detection of Road-Surface Anomalies Using a Smartphone Camera and Accelerometer

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 561
Author(s):  
Taehee Lee ◽  
Chanjun Chun ◽  
Seung-Ki Ryu
Keyword(s):  
Monitoring System ◽  
Poor Performance ◽  
Road Surface ◽  
Monitoring Systems ◽  
Advantages And Disadvantages ◽  
Acceleration Data ◽  
Road Surfaces ◽  
Road Surface Monitoring ◽  
Surface Monitoring ◽  
Acquisition Method

Road surfaces should be maintained in excellent condition to ensure the safety of motorists. To this end, there exist various road-surface monitoring systems, each of which is known to have specific advantages and disadvantages. In this study, a smartphone-based dual-acquisition method system capable of acquiring images of road-surface anomalies and measuring the acceleration of the vehicle upon their detection was developed to explore the complementarity benefits of the two different methods. A road test was conducted in which 1896 road-surface images and corresponding three-axis acceleration data were acquired. All images were classified based on the presence and type of anomalies, and histograms of the maximum variations in the acceleration in the gravitational direction were comparatively analyzed. When the types of anomalies were not considered, it was difficult to identify their effects using the histograms. The differences among histograms became evident upon consideration of whether the vehicle wheels passed over the anomalies, and when excluding longitudinal anomalies that caused minor changes in acceleration. Although the image-based monitoring system used in this research provided poor performance on its own, the severity of road-surface anomalies was accurately inferred using the specific range of the maximum variation of acceleration in the gravitational direction.

scholarly journals Noncontact Sleep Monitoring System under a Mattress

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Xu Jiao ◽  
Xiaosha Wang ◽  
Xiaohang Wang ◽  
Zipeng Liu
Keyword(s):  
Monitoring System ◽  
Sleep Monitoring

Development of an Acoustic-Based Riser Monitoring System

2009 ◽  
Author(s):  
Dai Wei ◽  
Yong Bai
Keyword(s):  
Gulf Of Mexico ◽  
Monitoring System ◽  
Fatigue Damage ◽  
Monitoring Systems ◽  
Design Tools ◽  
Complex Behavior ◽  
Maintenance And Repair ◽  
Future Design ◽  
Integrity Assurance ◽  
Deepwater Risers

Recent incidents with drilling risers in the Gulf of Mexico have led the industry’s application of more stringent integrity assurance requirements to its deepwater risers. Riser monitoring provides information that enables the operator to measure riser configurations and fatigue damage, confirm the integrity of the riser, assist with operational decisions, optimize inspection, maintenance and repair schedules /procedures and calibrate design tools. Monitoring can also improve the understanding of complex behavior of risers for the improvement to future design and analysis tools. This paper presents the characters of three different monitoring systems that suit specific objectives and requirements. An example project of acoustic approach is introduced with its working mode and design scheme.

Compressor Computerized Performance Monitoring System CPMS

2021 ◽  
Author(s):  
Vadim Goryachikh ◽  
Fahad Alghamdi ◽  
Abdulrahman Takrouni
Keyword(s):  
Natural Gas ◽  
Real Time ◽  
Monitoring System ◽  
Performance Monitoring ◽  
Compressibility Factor ◽  
Background Information ◽  
Monitoring Systems ◽  
Turbo Expander ◽  
Time Calculation ◽  
Performance Deterioration

Abstract Background information Natural gas liquid (NGL) production facilities, typically, utilize turbo-expander-brake compressor (TE) to generate cold for C2+ separation from the natural gas by isentropic expansion of feed stream and use energy absorbed by expansion to compress residue gas. Experience shows that during operational phase TE can exposed to operation outside of design window that may lead to machine integrity loss and consequent impact on production. At the same time, there is a lack of performance indicators that help operator to monitor operating window of the machine and proactively identify performance deterioration. For instance, TE brake compressor side is always equipped with anti-surge protection system, including surge deviation alarms and trip. However, there is often gap in monitoring deviation from stonewall region. At the same time, in some of the designs (2×50% machines) likelihood of running brake compressor in stonewall is high during one machine trip or train start-up, turndown operating modes. Also, typical compressor performance monitoring systems does not have enough dynamic parameters that may indicate machine process process performance deterioration proactively (real-time calculation of actual polytrophic efficiency, absorbed power etc.) and help operator to take action before catastrophic failure occurs. In addition, typical compressor monitoring systems are based on assumed composition and fixed compressibility factor and do not reflect actual compositions variations that may affect machine performance monitoring. To overcome issues highlighted above, Hawiyah NGL (HNGL) team has developed computerized monitoring and advisory system to monitor the performance of turbo-expander-brake compressor, proactively, identify potentially unsafe conditions or performance deterioration and advice operators on taking necessary actions to avoid unscheduled deferment of production. Computerized performance monitoring system has been implemented in HNGL DCS (Yokogawa) and utilized by control room operators on day-to-day basis. Real-time calculation, analysis and outputs produced by performance monitoring system allow operator to understand how current operating condition are far from danger zone. Proactive deviation alarms and guide messages produce by the system in case of deviation help operators to control machine from entering unsafe region. Actual polytrophic efficiency, adsorbed power calculations provide machine condition status and allow identifying long-term performance deterioration trends.

NEW APPROACHES TO THE SYNTHESIS OF AUTOMATIC SEISMIC MONITORING SYSTEMS

2020 ◽  
pp. 73-81
Author(s):  
B. M. Shubik ◽  
Keyword(s):  
Monitoring System ◽  
Traditional Approach ◽  
Automatic Monitoring ◽  
Seismic Monitoring ◽  
Monitoring Systems ◽  
Computational Techniques ◽  
Frequency Model ◽  
Complexity Of Algorithms ◽  
New Approaches ◽  
Detection And Localization

The processes of development of hydrocarbon deposits are accompanied, as a rule, by an increase in the level of seismicity and, in particular, by the occurrence of technogenic earthquakes and other deformation phenomena associated with changes in the geodynamic regime. To monitor deformation and geodynamic processes, a seismic monitoring service should be organized. A similar monitoring system is also required for the analysis of aftershock and volcanic activity. Monitoring technology should be based on the use of reliable and fast methods of automatic detection and localization of seismic events of various scales. Traditional approaches to the detection and localization of earthquake epicenters and hypocenters are based on the analysis of data recorded by one or more single seismic stations. In that case, seismic event coordinates are estimated by means of signal extraction from noise and accurately measuring arrival times of a number of specific phases of the seismic signal at each recording point. Existing computational techniques have inherited this traditional approach. However, automatic procedures based on the ideology of manual processing turn out to be extremely laborious and ineffective due to the complexity of algorithms adequate to the actions of an experienced geophysicist-interpreter. The article contains a description of new approaches to the synthesis of automatic monitoring systems, which are based on the principles of emission tomography, use of spatial registration systems, energy analysis of wave fields and methods of converting real waveforms into low-frequency model signals (so-called filter masks/templates). The monitoring system was successfully tested in the process of detecting and locating the epicenters and hypocenters of 19 weak local earthquakes in Israel, as well as a quarry explosion.

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