Real-Time Motion Feedback via Baseline-Adjusted Sensor Analysis
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Solution Overview
Problem
Existing data acquisition systems lack the capability to provide real-time feedback and comprehensive analysis of user motion, particularly in sports and physical activities, failing to account for multiple variables and trends over time, and do not offer immediate, clinically relevant indications for deviations from desired motion profiles.
Innovation Solution
The system employs inertial motion capture sensors to collect real-time data from golf clubs, body-worn devices, and other equipment, calculating multi-dimensional motion profiles and providing immediate feedback through graphical interfaces, tactile, visual, and auditory signals, while also allowing for remote monitoring and adaptation of motion templates based on progress and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time sensor data collection and multi-dimensional motion profile calculation are implemented, then measurement precision and feedback timeliness are improved, but device complexity and computational requirements increase
Solution Approach 1:
The system segments motion analysis into multiple independent dimensions (e.g., swing path, club head speed, face angle, temporal parameters) that can be measured and analyzed separately by different sensors and processing modules, then integrated to provide comprehensive feedback without overwhelming a single processing unit
Solution Approach 2:
The patent introduces intermediate processing layers including motion capture sensors that convert physical motion into digital signals, buffer memory that temporarily stores sensor data streams, and layered processing algorithms that handle different aspects of motion analysis separately before integration, reducing peak computational demands
2Loss of time
If real-time feedback and instantaneous motion analysis are provided, then feedback timeliness is improved, but processing speed requirements and energy consumption increase
Solution Approach 1:
The system implements periodic sampling of sensor data at optimized intervals rather than continuous processing, analyzing motion profiles at key phases of the athletic movement (e.g., address, backswing, downswing, impact, follow-through) to reduce computational load while maintaining perceptual feedback continuity
Solution Approach 2:
The patent pre-calculates and stores template motion profiles for ideal athletic techniques, allowing real-time comparison against these pre-prepared references rather than computing optimal trajectories from scratch during performance, significantly reducing processing time and energy requirements
3Loss of information
If multiple motion variables and environmental factors are tracked simultaneously, then measurement comprehensiveness is improved, but data processing complexity and analysis time increase
Solution Approach 1:
The system applies different processing and analysis depths to different motion variables based on their importance and variability - critical parameters like impact timing and club path receive detailed real-time analysis, while less critical variables are monitored at lower resolution or aggregated over longer periods, optimizing processing resources
Data Source
AI summary
This disclosure relates to systems, media, and methods for quantifying and monitoring exercise parameters and/or motion parameters, including performing data acquisition, analysis, and providing scientifically valid, clinically relevant, and/or actionable diagnostic feedback. Embodiments may be related to systems, devices, methods, and computer-readable media for providing baseline-adjusted real-time feedback to a user. Embodiments may include determining a type of activity for the user. Embodiment may include receiving data from the one or more motion sensors indicating a time-dependent series of three axis acceleration data and three-axis orientation data. Embodiments additionally may include providing a graphical user interface with a real-time representation of the received data. The real-time representation may include a scaled representation of at least one dimension of the time-dependent series of three axis acceleration data and three-axis orientation data for at least one of the one or more motion sensors based on the updated baseline adjustment.