Ai Fitness Workout Assistant Using Nlp Techniques
Year: 2025
Type: article
Abstract: This paper presents an AI fitness workout assistant utilizing Natural Language Processing (NLP) techniques, specifically Multilayer Perceptron (MLP) algorithm, to enhance user experience and engagement in personalized exercise routines. The proposed system employs NLP to comprehend and interpret user input, such as fitness goals, preferences, and constraints, extracted from textual descriptions or voice commands. The Multilayer Perceptron algorithm is utilized for its capability to model complex non- linear relationships between input and output variables, enabling efficient learning from user interactions and historical workout data. Through continuous interaction, the assistant tailor workout recommendations and provides real-time feedback, adapting to user progress and preferences. Experimental results demonstrate the effectiveness of the MLP- based NLP approach in accurately understanding user intents and generating personalized workout plans, fostering a more engaging and productive fitness experience.
Authors: Shoail Nizam -, Ranjeet Saw -, S. Arjun -, Dr. M. Sujitha -, Ms. G. Priyanka -
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408943162