Abstract
In this paper, multiple sensors are used to track human physiological parameters during physical exercise, and data information fusion technology is used to extract useful information for monitoring and analyzing the effects of physical exercise. This paper explores the interaction and developmental dynamics of multisensor information fusion technology and physical exercise data monitoring based on the interrelationship and interpenetration between the two. The design ideas and principles that should be followed for the software designed in this study are discussed from the perspective of the portable design of measurement instruments and the perspective of multisensor information fusion, and then, the overall architecture and each functional module are studied to propose a scientific and reasonable design model. The general methodological model to be followed for the development of this resource is designed, and the basic development process of the model is explained and discussed, especially the requirement analysis and structural design, and how to build the development environment are explained in detail; secondly, based on the course unit development process in this model, we clarify the limitations of the system through meticulous analysis of the measurement results, which provides a solid foundation for the next step of system optimization. Finally, with a focus on future development, we elaborate on the potential possible role and development trend of multisensor information fusion in the future period. In this paper, we propose to apply the multisensor data fusion algorithm to the monitoring, analysis, and evaluation of the effect of physical exercise, by collecting multiple human physiological parameters during physical exercise through multiple sensors and performing data fusion processing on the collected physiological parameters to finally evaluate the effect of physical exercise.
Highlights
The method of tracking single sensor measurement data can no longer meet the growing requirements, and people have begun to explore the use of multiple sensor measurement data combined to maximize the extraction of useful information contained in the measurement data to achieve the tracking of moving targets [1]
The emergence of multisensor information fusion technology is a good solution to this dilemma
Due to the high intensity of life and work pressure in modern society, people have less and less time to participate in physical exercise, and increased people are in a subhealthy or even unhealthy state
Summary
The method of tracking single sensor measurement data can no longer meet the growing requirements, and people have begun to explore the use of multiple sensor measurement data combined to maximize the extraction of useful information contained in the measurement data to achieve the tracking of moving targets [1]. How to effectively fuse the measurement data from multiple sensors to obtain tracking performance that cannot be achieved by a single sensor has become the focus of research and attention in multisensor data fusion technology in the field of target tracking. Due to the rich information provided by many sensor data in the system that needs to be extracted and utilized, to better process the sensor data, combining intelligent theory with information fusion technology is an inevitable trend in the development of sensor information fusion technology. The development of multisensor information fusion technology has a wide range of applications in areas such as intelligent transportation, robotics, space navigation, and even military aspects. Information fusion is increasingly used in life, and scholars around
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