A Real Time Attachment Free, Psycho Physiological Stress and Heart Rate Measurement System

2011 ◽  
Vol 1 (2) ◽  
pp. 1-13 ◽  
Author(s):  
Anthony Psaltis ◽  
Constantinos Mourlas
Keyword(s):  
Real Time ◽  
Physiological Stress ◽  
Emotional Responses ◽  
User Profiling ◽  
Computer User ◽  
Web Based ◽  
Computer Mouse ◽  
Educational Environments ◽  
E Learning ◽  
Improve Reliability

The challenges in the development of a system performing real time detection of physiological parameters are fundamentally aversive because of the incommodities caused by the wires and sensing attachments onto the user, making the measurement sessions uncomfortable. Another factor is that the sensing accessories influence the plausibility of the measurements. In this paper, the authors introduce a system based on a device that can acquire physiological signals from a computer user with no prerequisites, postural, kinetic, or other constraints in the environment of normal usage of the home computer for the detection of their psychosomatic state and optimally their affect and emotional responses. The authors also discuss issues that could otherwise compromise the credibility of the results. Redundancy and special adaptive and corrective algorithms have been developed to improve reliability and achieve acceptable standards of quality. Measurements include skin conductance (SC) and reart rate (HR) detected by sensors positioned on the vertical sides of a computer mouse. The system is intended for interactive educational environments, during assessment, e-learning, psychosomatic user profiling, mobile and web based interfaces, and for Human Computer Interaction (HCI) platforms.

A Real Time Attachment Free, Psycho Physiological Stress and Heart Rate Measurement System

2013 ◽  
pp. 74-86 ◽  
Author(s):  
Anthony Psaltis ◽  
Constantinos Mourlas
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Physiological Stress ◽  
User Profiling ◽  
Physiological Signals ◽  
Web Based ◽  
Computer Mouse ◽  
Educational Environments ◽  
E Learning ◽  
Improve Reliability

The challenges in the development of a system performing real time detection of physiological parameters are fundamentally aversive because of the incommodities caused by the wires and sensing attachments onto the user, making the measurement sessions uncomfortable. Another factor is that the sensing accessories influence the plausibility of the measurements. In this paper, the authors introduce a system based on a device that can acquire physiological signals from a computer user with no prerequisites, postural, kinetic, or other constraints in the environment of normal usage of the home computer for the detection of their psychosomatic state and optimally their affect and emotional responses. The authors also discuss issues that could otherwise compromise the credibility of the results. Redundancy and special adaptive and corrective algorithms have been developed to improve reliability and achieve acceptable standards of quality. Measurements include skin conductance (SC) and heart rate (HR) detected by sensors positioned on the vertical sides of a computer mouse. The system is intended for interactive educational environments, during assessment, e-learning, psychosomatic user profiling, mobile and web based interfaces, and for Human Computer Interaction (HCI) platforms.

Virtual Microscopy in Haematology and Histopathology Education

2018 ◽  
pp. 140-152 ◽  
Author(s):  
Vinod Gopalan ◽  
Abishek B. Santhakumar ◽  
Indu Singh
Keyword(s):  
Real Time ◽  
Case Studies ◽  
Virtual Microscopy ◽  
Student Interaction ◽  
Web Based ◽  
Routine Diagnostics ◽  
Technological Advances ◽  
E Learning ◽  
Class Room ◽  
Technical Considerations

Virtual microscopy is a method by which real-time microscopic illustrations get transmitted digitally via computer networks. There is increasing evidence to suggest that virtual microscopy combined with other didactic methods in teaching make significant improvements in student interaction and curiosity in histopathology and haematology teaching. The introduction of virtual microscopy has opened up a big arena in the field of e-learning in histopathology and haematology curriculum. Case studies prove the technological benefits of virtual microscopy in interacting off-campus students and educators. Recent technological advances have improved the use of virtual microscopy and enabled them to complement students learning in class room as well as for routine diagnostics. In this chapter, the authors discuss the significance, usefulness, and limitations of virtual microscopy in education. In addition, the chapter has provided several technical considerations to develop a friendly web-based virtual microscopy tool in teaching.

High Performance Publisher/Subscriber Communication for Adaptive, Collaborative Web-Based Learning

2011 ◽  
pp. 664-676
Author(s):  
Yugyung Lee ◽  
Markus Junginger ◽  
James Geller
Keyword(s):  
Real Time ◽  
High Performance ◽  
Learning Systems ◽  
Learning System ◽  
Web Based ◽  
Course Materials ◽  
Web Based Learning ◽  
New Learning ◽  
E Learning ◽  
Tool Set

The inability of current Internet-based learning systems to deal with different kinds of learners and the high cost of developing a new learning system are well-known problems in e-learning. To overcome these problems, we have designed a learning middleware suite, called the Collaborative and Sharable Learning (CoSL) system. CoSL is a tool set for building e-learning systems and for developing course materials for an e-learning environment. Given the geographic distribution of the components of a Web-based e-learning system, it is crucial to support fast communication between providers and consumers of e-learning course materials. In this paper, a high performance Publisher/Subscriber communication system has been designed for real-time communication between participants. CoSL allows us to build and manage global real-time learning systems in a distributed and heterogeneous environment.

Building Web-based e-learning application for operating system course

2008 ◽  
Author(s):  
Sun Weijun ◽  
Sun Weijun ◽  
Zhang Defen ◽  
Zhang Defen ◽  
Yan Yu-Qing ◽  
...  
Keyword(s):  
Operating System ◽  
Web Based ◽  
E Learning

scholarly journals Deep-Framework: A Distributed, Scalable, and Edge-Oriented Framework for Real-Time Analysis of Video Streams

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4045
Author(s):  
Alessandro Sassu ◽  
Jose Francisco Saenz-Cogollo ◽  
Maurizio Agelli
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Video Data ◽  
Video Analytics ◽  
Web Based ◽  
Real Time Analysis ◽  
Open Source Framework ◽  
Cluster Configuration ◽  
Time Requirements ◽  
High Level

Edge computing is the best approach for meeting the exponential demand and the real-time requirements of many video analytics applications. Since most of the recent advances regarding the extraction of information from images and video rely on computation heavy deep learning algorithms, there is a growing need for solutions that allow the deployment and use of new models on scalable and flexible edge architectures. In this work, we present Deep-Framework, a novel open source framework for developing edge-oriented real-time video analytics applications based on deep learning. Deep-Framework has a scalable multi-stream architecture based on Docker and abstracts away from the user the complexity of cluster configuration, orchestration of services, and GPU resources allocation. It provides Python interfaces for integrating deep learning models developed with the most popular frameworks and also provides high-level APIs based on standard HTTP and WebRTC interfaces for consuming the extracted video data on clients running on browsers or any other web-based platform.

Real-time imaging-based assessment model for improving teaching performance and student experience in e-learning

2017 ◽  
Vol 13 (3) ◽  
pp. 491-504 ◽  
Author(s):  
Muhammad Farhan ◽  
Muhammad Aslam ◽  
Sohail Jabbar ◽  
Shehzad Khalid ◽  
Mucheol Kim
Keyword(s):  
Real Time ◽  
Student Experience ◽  
Assessment Model ◽  
Teaching Performance ◽  
Real Time Imaging ◽  
E Learning
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