Exploration of human-computer interaction and product design of wearable weaponry based on digital technology

status signs and data characteristics through this device. First of all, the overall system of the product contains temperature and humidity module, blood pressure detection module, heart rate measurement module and display module, and the extracted feature data are subjected to data intelligence preprocessing. Then the pre-processed feature data is functionally compressed and an artificial intelligence feature classification model is constructed, through which the compressed feature data is analyzed and displayed. Finally, the interactive performance of the wearable device is completed through data intelligent processing and device relevance calculation. After application analysis, it is found that the actual monitoring error is below 0.1 under different fatigue levels, and the specificity and positive prediction value of the wearable system can reach up to 100%. The highest accuracy of monitoring the physical state of military personnel is 99.31%, in addition to monitoring the heart rate in sedentary state and exercise state, with an average error value of 1.24 and 1.29. Therefore, the smart wearable device designed in this paper can well realize human-computer interaction, and the performance of product design is superior.

Authors

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-15
DOI
https://doi.org/10.61091/jcmcc127a-044
Citations
1
Primary Topic
Simulation and Modeling Applications
Type
article
Field-Weighted Citation Impact
1.21

Funders

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article

Exploration of human-computer interaction and product design of wearable weaponry based on digital technology

Lin Lu, Fei Li
1 citations
Journal of Combinatorial Mathematics and Combinatorial Computing
Simulation and Modeling Applications
1.21
article

Exploration of human-computer interaction and product design of wearable weaponry based on digital technology

Lin Lu, Fei Li
article en
1 citations

Abstract

status signs and data characteristics through this device. First of all, the overall system of the product contains temperature and humidity module, blood pressure detection module, heart rate measurement module and display module, and the extracted feature data are subjected to data intelligence preprocessing. Then the pre-processed feature data is functionally compressed and an artificial intelligence feature classification model is constructed, through which the compressed feature data is analyzed and displayed. Finally, the interactive performance of the wearable device is completed through data intelligent processing and device relevance calculation. After application analysis, it is found that the actual monitoring error is below 0.1 under different fatigue levels, and the specificity and positive prediction value of the wearable system can reach up to 100%. The highest accuracy of monitoring the physical state of military personnel is 99.31%, in addition to monitoring the heart rate in sedentary state and exercise state, with an average error value of 1.24 and 1.29. Therefore, the smart wearable device designed in this paper can well realize human-computer interaction, and the performance of product design is superior.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127a
National Natural Science Foundation of China
Openalex Percentile: Top 23%
Simulation and Modeling Applications
1.21
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