Adaptive Exercise Recommendation Chatbot for Missed Workouts

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Solution Overview

Problem

Conventional exercise systems provide inflexible health recommendations that do not account for individual user lifestyle, attitude, or motivational styles, leading to inefficiencies in exercise adherence.

Innovation Solution

An exercise recommendation system that utilizes an exercise chatbot to interact with users, gather additional information through queries, and apply a recommendation model to generate personalized exercise recommendations based on user-specific data, including missed workout identification and health habit analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If pre-determined exercise systems are used, then implementation simplicity is improved, but adaptability to individual user lifestyle and motivational styles deteriorates

Engineering Contradiction:

Improveimplementation simplicityVSAvoidadaptability to user lifestyle

Core Design Contradiction:

Ease of manufactureVSAdaptability or versatility

Solution Approach 1:

The exercise system transitions from static pre-determined plans to dynamic adaptive plans that automatically adjust based on real-time user data from wearables, app interactions, and feedback mechanisms, allowing the system to evolve with individual user needs and lifestyles

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements continuous feedback loops where user performance data, adherence metrics, and motivational responses are collected and used to refine and personalize exercise recommendations, creating a responsive adaptive experience

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If personalized exercise recommendations are generated through interactive queries, then adaptability to user-specific factors is improved, but device complexity and interaction time increase

Engineering Contradiction:

Improvepersonalization accuracyVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary data collection and analysis by integrating with wearable devices and mobile apps to gather user metrics before generating recommendations, reducing the need for complex real-time interactions while maintaining high personalization accuracy

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Mobile applications and wearable devices serve as intermediaries that handle complex data processing and user interaction tasks, allowing the core exercise recommendation system to remain relatively simple while achieving sophisticated personalization

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20250229135A1Devices, systems, and methods to generate exercise recommendations

Publication Date: 2025.07.17 IFIT INC

AI summary

An exercise recommendation system may receive exercise information for a user. An exercise recommendation system may, based on the exercise information, identify a missed exercise activity. An exercise recommendation system may, based on the missed exercise activity and using an exercise chatbot, present the user with a query, the query including a request for additional information related to the missed exercise activity. An exercise recommendation system may receive a response to the query. An exercise recommendation system may apply a recommendation model to the response to generate an exercise recommendation.