Body-Part Motion Tracking for Personalized Exercise Feedback
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Solution Overview
Problem
Existing physical training systems fail to evaluate the quality of movements during exercises, cannot assess individual user performance, and do not provide personalized feedback to enhance training success.
Innovation Solution
A system comprising a tracker with a sensor unit to detect body part movements, a model generation arrangement to create an individual movement model, and an analysis arrangement to evaluate current motions against the model using dynamic time warping, providing personalized feedback and instructions for improvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing monitoring systems focus on device movement rather than person movement, then device training results can be displayed, but the quality of user movement cannot be evaluated
Solution Approach 1:
The patent introduces an intermediary component (sensor unit attached to the body part) that bridges the gap between device-based monitoring and actual body movement tracking. This sensor acts as a mediator that directly captures user movement data, enabling quality evaluation without requiring complex system restructuring.
Solution Approach 2:
The patent replaces mechanical device-based monitoring with an electronic sensor-based system that directly measures body part movement. This substitution enables precise movement quality evaluation by using electronic sensors to capture kinematic data, replacing the indirect mechanical monitoring approach.
2Adaptability or versatility
If standardized exercises from a library are provided, then needs of multiple users can be met, but individual user performance and movement quality cannot be assessed
Solution Approach 1:
The patent applies preliminary action by having users perform reference movements before actual training to establish personalized reference profiles. This pre-capture of individual movement characteristics enables subsequent comparison and feedback during training, providing personalized assessment without requiring complex real-time adaptation algorithms.
Solution Approach 2:
The patent implements feedback by comparing real-time sensor data against stored reference profiles and providing information about movement quality. This feedback mechanism enables individual performance assessment by continuously comparing current movements with the user's own reference movements, maintaining adaptability while preventing information loss.
3Productivity
If simple movement counting is implemented, then training effort can be quantified, but movement quality and compliance cannot be evaluated
Solution Approach 1:
The patent applies segmentation by dividing movement analysis into multiple components: basic movement counting for productivity tracking, and detailed kinematic parameter analysis for quality assessment. This segmentation allows the system to simultaneously provide simple productivity metrics and comprehensive quality evaluation without compromising either function.
Solution Approach 2:
The patent transitions from one-dimensional movement counting to multi-dimensional movement analysis by incorporating spatial coordinates, temporal parameters, and kinematic variables. This dimensional expansion enables simultaneous measurement of training quantity (productivity) and movement quality (precision) through comprehensive sensor data capture.
Data Source
Figure 1
AI summary
A system for physical training of a body part comprises a tracker (1) having a mounting structure configured to fasten the tracker (1) at a particular body part of a user and a sensor unit configured to detect a movement of the body part. The system further comprises a model generation arrangement (2) connectable to the tracker (1) and configured to obtain first sensor data (5) about a sequence of motion detected by the tracker (1) and to generate an individual movement model (6) based on the first sensor data (5). The system also comprises an analysis arrangement (3) connectable to the tracker (1) and configured to evaluate second sensor data (7) about a current motion of the body part and to check compliance of the second sensor data (7) with respect to the individual movement model (6). The system can be used for a method of physically training a body part of a user that includes the steps of generating the individual movement model (6) based on the first sensor data (5) and checking compliance of the second sensor data (7) with respect to the individual movement model (6).