A Review of Intelligent Sensor-Based Systems for Pressure Ulcer Prevention

Pressure ulcers are a critical issue not only for patients, decreasing their quality of life, but also for healthcare professionals, contributing to burnout from continuous monitoring, with a consequent increase in healthcare costs. Due to the relevance of this problem, many hardware and software approaches have been proposed to ameliorate some aspects of pressure ulcer prevention and monitoring. In this article, we focus on reviewing solutions that use sensor-based data, possibly in combination with other intrinsic or extrinsic information, processed by some form of intelligent algorithm, to provide healthcare professionals with knowledge that improves the decision-making process when dealing with a patient at risk of developing pressure ulcers. We used a systematic approach to select 21 studies that were thoroughly reviewed and summarized, considering which sensors and algorithms were used, the most relevant data features, the recommendations provided, and the results obtained after deployment. This review allowed us not only to describe the state of the art regarding the previous items, but also to identify the three main stages where intelligent algorithms can bring meaningful improvement to pressure ulcer prevention and mitigation. Finally, as a result of this review and following discussion, we drew guidelines for a general architecture of an intelligent pressure ulcer prevention system.

Research on the Influence of Sports and Nutrition Matching on Improving Students’ Physique Based on Intelligent Sensor

With the continuous development of social economy, students’ learning is paid more and more attention, but at the same time, their physical condition also deserves attention. In view of these problems and limitations, this paper is based on intelligent sensors, which is different from the traditional physical education teaching, adopts the corresponding prescription for sports teaching, combines teaching with fun for the corresponding health intervention, and realizes the two-way dimensional analysis of compound sports prescription through comprehensive nutrition collocation, so as to improve students’ physical and mental health, in order to improve students’ physical fitness. The simulation results show that the intelligent sensor is effective, which can improve the systematicness and scientificity of students’ participation in exercise in sports activities and improve students’ learning and physical fitness.

Motion Capture Based on Intelligent Sensor in Snow and Ice Sports

With the development of motion capture technology, it has become a reality to efficiently and quickly obtain realistic human motion information. Motion capture technology has been successfully applied in many fields such as sports competitions, animation games, and film and television production. This article is aimed at studying the application of motion capture technology based on smart sensors in ice and snow sports. Put forward the idea of applying smart sensor-based motion capture technology to ice and snow sports. This article introduces in detail smart sensors, motion capture technology, and related content of ice and snow sports and conducts specific experiments on the application of smart sensor-based motion capture technology in ice and snow sports. The experimental results show that motion capture based on smart sensor technology can help athletes improve their skills and tactics. At the same time, motion capture technology based on smart sensors is also loved by most coaches and athletes, and everyone’s satisfaction with this technology has reached more than 70%.

Smart Sensors for Augmented Electrical Experiments

With the recent increase in the use of augmented reality (AR) in educational laboratory settings, there is a need for new intelligent sensor systems capturing all aspects of the real environment. We present a smart sensor system meeting these requirements for STEM (science, technology, engineering, and mathematics) experiments in electrical circuits. The system consists of custom experiment boxes and cables combined with an application for the Microsoft HoloLens 2, which creates an AR experiment environment. The boxes combine sensors for measuring the electrical voltage and current at the integrated electrical components as well as a reconstruction of the currently constructed electrical circuit and the position of the sensor box on a table. Combing these data, the AR application visualizes the measurement data spatially and temporally coherent to the real experiment boxes, thus fulfilling demands derived from traditional multimedia learning theory. Following an evaluation of the accuracy and precision of the presented sensors, the usability of the system was evaluated with n=20 pupils in a German high school. In this evaluation, the usability of the system was rated with a system usability score of 94 out of 100.

Application of Intelligent Sensor Algorithm in Student Management Information Fusion

In order to improve the effectiveness of college student management and promote the integration of college student management information, this paper applies intelligent sensor algorithms to student management. Moreover, this paper combines uncertainty theory with multisensor data fusion technology to establish a complete set of multisensor data processing tools for student information and provides a complete mathematical theoretical framework for the principles of student management information fusion. In addition, in view of the problem of comparing a large number of mixed data of information sources, it is necessary to transfer the information fragments obtained by each sensor to a common set so that the information fragments expressed in different sets can be integrated. Finally, this paper constructs an intelligent student management model and conducts research in combination with simulation experiments. Through simulation research, it can be known that the method proposed in this paper can effectively improve the effect of student management.

Intelligent System for Training and Assessment of Basketball Referee in Sports Event Using Intelligent Sensor

Aiming at the problem of the fairness of the judgment results in the traditional basketball referee training and evaluation process affected by external factors, an intelligent system for training and assessment of basketball referees in sports events based on intelligent sensors is proposed. We collect the judged poses of basketball referees by wearing intelligent sensor devices, store the collected information in the database using the converter, and analyze the pose data with the quaternion pose solution method based on complementary filters. According to the comparator, the analysis result is compared with the standard judgment information, and the action is judged whether the action conforms to the basketball judgment rules of the sports event. The judge’s action pose score is evaluated according to the judgment result, and the training assessment result is outputted. The results show that the system can clearly simulate the acceleration and pose angle data of the referee’s complex actions, the recognition rate of various basketball penalty poses is high, and the error of the pitch, yaw, and roll pose calculations is small. The response time of this system is 4 ms, when the number of requests sent by the client is 200 which is unanimously approved by the referees.

Development of Extrospective Systems for Mobile Robotic Vehicles.

<p>Extrospection is the process of receiving knowledge of the outside world through the senses. On robotic platforms this is primarily focussed on determining distances to objects of interest and is achieved through the use of ranging sensors. Any hardware implemented on mobile robotic platforms, including sensors, must ideally be small in size and weight, have good power efficiency, be self-contained and interface easily with the existing platform hardware. The development of stable, expandable and interchangeable mobile robot based sensing systems is crucial to the establishment of platforms on which complex robotic research can be conducted and evaluated in real world situations. This thesis details the design and development of two extrospective systems for incorporation in the Victoria University of Wellington's fleet of mobile robotic platforms. The first system is a generic intelligent sensor network. Fundamental to this system has been the development of network architecture and protocols that provide a stable scheme for connecting a large number of sensors to a mobile robotic platform with little or no dependence on the existing hardware configuration of the platform. A prototype sensor network comprising fourteen infrared position sensitive detectors providing a short to medium distance ranging system (0.2 - 3 m) with a 360' field of view has been successfully developed and tested. The second system is a redesign of an existing prototype full-field image ranger system. The redesign has yielded a smaller, mobile version of the prototype system capable of ranging medium to long distances (0 - 15 m) with a 22.2' - 16.5' field-of-view. This ranger system can now be incorporated onto mobile robotic platforms for further research into the capabilities of full-field image ranging as a form of extrospection on a mobile platform.</p>

Development of Extrospective Systems for Mobile Robotic Vehicles.

<p>Extrospection is the process of receiving knowledge of the outside world through the senses. On robotic platforms this is primarily focussed on determining distances to objects of interest and is achieved through the use of ranging sensors. Any hardware implemented on mobile robotic platforms, including sensors, must ideally be small in size and weight, have good power efficiency, be self-contained and interface easily with the existing platform hardware. The development of stable, expandable and interchangeable mobile robot based sensing systems is crucial to the establishment of platforms on which complex robotic research can be conducted and evaluated in real world situations. This thesis details the design and development of two extrospective systems for incorporation in the Victoria University of Wellington's fleet of mobile robotic platforms. The first system is a generic intelligent sensor network. Fundamental to this system has been the development of network architecture and protocols that provide a stable scheme for connecting a large number of sensors to a mobile robotic platform with little or no dependence on the existing hardware configuration of the platform. A prototype sensor network comprising fourteen infrared position sensitive detectors providing a short to medium distance ranging system (0.2 - 3 m) with a 360' field of view has been successfully developed and tested. The second system is a redesign of an existing prototype full-field image ranger system. The redesign has yielded a smaller, mobile version of the prototype system capable of ranging medium to long distances (0 - 15 m) with a 22.2' - 16.5' field-of-view. This ranger system can now be incorporated onto mobile robotic platforms for further research into the capabilities of full-field image ranging as a form of extrospection on a mobile platform.</p>

Design of meteorological intelligent sensor based on POE Technology

An application scheme of Poe based Ethernet technology in meteorological intelligent sensor system is designed. The working principle and implementation method of Ethernet power supply system (POE) based on IEEE802.3af Ethernet power supply industry standard are experimentally analyzed. The power supply part of the meteorological intelligent sensor makes full use of Poe technology to provide current on the network cable transmitting data, which greatly reduces the complexity of the power supply system and improves the reliability of the system power supply design. Through the test of the actual system, the function and performance of the meteorological intelligent transmission system have achieved the expected results.