Music-Based Exercise Program Generation
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Solution Overview
Problem
Existing exercise program generation methods fail to consider an athlete's musical preferences and require time-consuming, resource-intensive analysis to create playlists that fit exercise intervals, often leading to less engaging workouts.
Innovation Solution
A computer-implemented method that analyzes music tracks to identify sections based on musical characteristics and generates exercise programs with intervals matching the timing, duration, and intensity of these sections, optionally using metadata or user history to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional playlist fitting methods are used to match music to exercise intervals, then the exercise program can be structured with defined intensity levels, but the process requires time-consuming scanning and much processing power
Solution Approach 1:
The patent applies preliminary action by pre-analyzing music tracks and storing their characteristics (tempo, energy, sections) in a database before exercise program generation. This allows the system to quickly retrieve and match pre-characterized music sections to exercise intervals without performing time-consuming analysis during playlist creation, resolving the contradiction between reliable matching and time consumption.
2Productivity
If simple music analysis is used to create playlists based on energy consumption, then the process is faster, but it does not take the athlete's musical preferences and motivation into consideration
Solution Approach 1:
The patent segments music tracks into distinct sections (intro, verse, chorus, bridge, outro) and characterizes each section separately with musical attributes. This segmentation allows the system to efficiently process music while preserving detailed information about different parts, enabling both fast processing and personalized selection based on athlete preferences for specific music sections or styles.
Solution Approach 2:
The system incorporates feedback mechanisms where athlete preferences, historical data, and motivation factors are fed back into the playlist generation process. The system learns from previous selections and adjusts music recommendations to match individual athlete tastes while maintaining the structural integrity of exercise intervals, thus achieving both speed and personalization.
3Extent of automation
If songs are selected based on previous exercise energy consumption, then playlists can be generated automatically, but the selection is random and does not account for natural challenges affecting energy consumption
Solution Approach 1:
The patent changes the approach from using energy consumption as the primary parameter to using direct musical parameters (tempo, energy level, rhythm) that can be objectively measured and matched to exercise intensity. This parameter change eliminates the inaccuracies introduced by environmental factors affecting energy consumption measurements, while maintaining automatic playlist generation through objective music characteristics.
4Ease of manufacture
If each song is treated as a single exercise intensity level, then the exercise program is simple to generate, but it is less engaging and does not utilize the dynamic structure within music tracks
Solution Approach 1:
The system performs preliminary analysis of music tracks to identify sections with different energy levels and characteristics before exercise program generation. This pre-characterization allows the system to easily assign different exercise intensities to different music sections during program creation, maintaining simplicity while significantly enhancing engagement by utilizing the dynamic structure within tracks.
Data Source
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AI summary
The present invention relates to a computer-implemented method for generating an exercise program comprising a plurality of exercise intervals, the method comprising the steps of: - providing a playlist comprising at least one music track, - identifying a plurality of music sections in the at least one music track, wherein each music section is identified based on identification of musical characteristics such as musical elements and time flow, - generating an exercise program, the exercise program comprising a plurality of exercise intervals, wherein at least the timing and intensity of each exercise interval correspond to one or more consecutive identified music sections of the at least one music track in the playlist. Thereby, the user, e.g. the athlete or an instructor, can end up with an exercise program, where there is a fit between the exercise intervals in the exercise program and the music accompanying the training program. An intuitive feel of intensity is obtained based on the songs in the playlist accompanying the training program, because the exercise program and its exercise intervals have been generated based on the music and the music sections in the music.