Abstract
Due to the marked increase in the prevalence of overweight and obesity worldwide and an environment leading to a series of chronic diseases, physical exercise is an important way to prevent chronic diseases. Additionally, a good exercise smart bracelet can bring convenience to physical exercise. Quick and accurate evaluation of smart sports bracelets has become a hot topic and draws attention from both academic researchers and public society. In the literature, the analytic hierarchy process (AHP) and entropy weight method (EWM) were used to obtain the weights from both subjective and objective perspectives, which were integrated by the comprehensive weighting method, and furthermore the performance of sports smart bracelet was evaluated through fuzzy comprehensive evaluation. Also, to avoid complex weight calculations caused by the comprehensive weighting method, machine learning methods are used to model the structure and contribute to the comprehensive evaluation process. However, few studies have investigated all previous elements in the comprehensive evaluation process. In this study, we consider all previous parts when evaluating smart sports bracelets. In particular, we use the sparrow search algorithm (SSA) to optimize the backpropagation (BP) neural network for constructing the comprehensive score prediction model of the sports smart bracelet. Results show that the sparrow search algorithm-optimized backpropagation (SSA-BP) neural network model has good predictive ability and can quickly obtain evaluation results on the premise of effectively ensuring the accuracy of the evaluation results.
Highlights
In recent years, the frequency of overweight and obesity has increased significantly worldwide [1]
An in-depth interview was conducted with three industrial design experts; open questions were set on the rationality and integrity of the model indicators; and indicators were modified and improved according to the experts’ opinions. ese amendments were as follows: (1) Integration of indicator elements: integrate similar concepts, such as the appearance of the features of the “shell,” “interface” into the “size,” “easy to use interface navigation,” “reasonable interface design,” “clear interface,” and other indicators into the “touch interface”
Facing a series of chronic diseases caused by obesity and overweight, physical exercise is an effective way to prevent these chronic diseases
Summary
The frequency of overweight and obesity has increased significantly worldwide [1]. Studies have shown that overweight and obesity induce chronic diseases such as hypertension, diabetes, and cardiovascular diseases and can lead to shortened life expectancy [3, 4]. Regular exercise is helpful to prevent chronic diseases, improve quality of life, and promote physical and mental health [5, 6]. Erefore, participation in sports and appropriate physical activities plays an important role in preventing chronic disease [7]. According to a number of studies, AI sports equipment with exercise programs may increase positivity [8, 9]. By collecting data and browsing health records, sports smart bracelets can monitor physiological data during exercise [12]
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