CrossRef Open Access 2022 14 sitasi

Physical Activity Recommendation System Based on Deep Learning to Prevent Respiratory Diseases

Usharani Bhimavarapu M. Sreedevi Nalini Chintalapudi Gopi Battineni

Abstrak

The immune system can be compromised when humans inhale excessive cooling. Physical activity helps a person’s immune system, and influenza seasonally affects immunity and respiratory tract illness when there is no physical activity during the day. Whenever people chill excessively, they become more susceptible to pathogens because they require more energy to maintain a healthy body temperature. There is no doubt that exercise improves the immune system and an individual’s fitness. According to an individual’s health history, lifestyle, and preferences, the physical activity framework also includes exercises to improve the immune system. This study developed a framework for predicting physical activity based on information about health status, preferences, calorie intake, race, and gender. Using information about comorbidities, regions, and exercise/eating habits, the proposed recommendation system recommends exercises based on the user’s preferences.

Penulis (4)

Usharani Bhimavarapu

M. Sreedevi

Nalini Chintalapudi

Gopi Battineni

Format Sitasi

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Bhimavarapu, U., Sreedevi, M., Chintalapudi, N., Battineni, G. (2022). Physical Activity Recommendation System Based on Deep Learning to Prevent Respiratory Diseases. https://doi.org/10.3390/computers11100150

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Total Sitasi: 14×
Sumber Database: CrossRef
DOI: 10.3390/computers11100150
Akses: Open Access ✓