A fitness app is an application that can be downloaded on any mobile device and used anywhere to get fit. Fitness apps are designed to help with exercise, other types of physical training, nutrition and diet, and other ways to get fit.

As of 2015, the number of health-related apps released on the two leading platforms, iPhone operating system (iOS) and Android, had reached more than 165,000.[1] Apps can perform various functions such as allowing users to set fitness goals, tracking caloric intake, gathering workout ideas, and sharing progress on social media to facilitate healthy behavior change. They can be used as a platform to promote healthy behavior change with personalized workouts, fitness advice and nutrition plans. Fitness apps can work in conjunction with wearable devices to synchronize their health data to third-party devices for easier accessibility. Through using gamification elements and creating competition among friends and family, fitness apps can help incentive users to be more motivated. Running and workout apps allow users to run or work out to music in the form of DJ mixes that can be personalized based on the user's steps per minute, heart rate or ideal cadence thus boosting and enhancing performance during exercise.

Recent advancements have seen fitness apps[2] evolve to utilize artificial intelligence to provide even more personalized fitness guidance. Utilizing symbolic AI, some apps now interpret physical activity and sedentary behavior guidelines from organizations like the WHO and ACSM to offer tailored exercise recommendations, enhancing the precision of fitness plans.[3]

See also

References

  1. ↑ "More than 165,000 mobile health apps now available - iMedicalApps". iMedicalApps. 2015-09-17. Retrieved 2017-12-10.
  2. ↑ "10 Best Fitness Apps Of 2024". Forbes Health. 2023-02-13. Retrieved 2024-01-08.
  3. ↑ Allocca, Carlo; Jilali, Samia; Ail, Rohit; Lee, Jaehun; Kim, Byungho; Antonini, Alessio; Motta, Enrico; Schellong, Julia; Stieler, Lisa; Haleem, Muhammad Salman; Georga, Eleni; Pecchia, Leandro; Gaeta, Eugenio; Fico, Giuseppe (January 2022). "Toward a Symbolic AI Approach to the WHO/ACSM Physical Activity & Sedentary Behavior Guidelines". Applied Sciences. 12 (4): 1776. doi:10.3390/app12041776. ISSN 2076-3417.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.