Spinal Posture Monitoring with Dynamic Recalibration Feedback
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Solution Overview
Problem
Existing posture monitoring devices fail to dynamically adjust to individual user preferences and varying exercises, limiting their effectiveness in monitoring and correcting spinal position during different activities.
Innovation Solution
A dynamic posture monitoring system with integrated position sensors, an electronic control unit, and a mobile application that allows real-time spinal position monitoring and recalibration based on user-defined preferences, providing haptic feedback and visual representation to correct spinal alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system uses a fixed ideal position for posture monitoring, then it can accurately detect deviations from that position, but it cannot adapt to different exercises and individual user preferences
Solution Approach 1:
The system implements dynamic recalibration that allows the ideal position to be adjusted based on different exercises and individual user preferences. The calibration data structure stores exercise-specific ideal positions, enabling the system to adapt from static to dynamic monitoring requirements across various activities
Solution Approach 2:
The system changes the reference position parameter dynamically based on the selected exercise type and user preferences. By storing multiple ideal positions for different exercises (squat, lunge, press up, plank, bridge) and allowing user-specific calibration, the system maintains measurement precision for each specific context while achieving overall versatility
2Adaptability or versatility
If the system is designed for specific exercises only, then it can provide accurate monitoring for those exercises, but it cannot be used for various types of exercises without changes
Solution Approach 1:
The system is designed with universal applicability across multiple exercise types (squat, lunge, press up, plank, bridge) by implementing a calibration framework that stores exercise-specific ideal positions. The same hardware and processing unit handle all exercise types, achieving multi-functionality without requiring separate systems for each exercise
Solution Approach 2:
The system performs preliminary calibration for each exercise type to establish the ideal position before actual monitoring begins. By pre-storing calibration data for different exercises and allowing user-specific calibration, the system prepares the reference framework in advance, enabling seamless transition between exercise types without complex real-time reconfiguration
3Ease of operation
If the system enforces a single ideal position, then it can provide clear feedback for that position, but it prevents users from actively maintaining different postures
Solution Approach 1:
The system transitions from enforcing a single static ideal position to dynamically adapting to user-selected ideal positions. Users can actively choose and recalibrate their preferred posture for each exercise type, and the system reliably provides feedback relative to that user-defined reference, maintaining both autonomy and reliability
Solution Approach 2:
The system provides feedback relative to the user-defined ideal position rather than a predetermined standard. By allowing users to set their preferred posture and then monitoring deviations from that personalized reference, the system maintains measurement reliability while enabling user autonomy in posture selection
Data Source
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AI summary
The present application discloses a novel spinal posture monitoring system designed to enhance user awareness and encourage proper posture habits; wherein the system may utilize two Arduino flex sensors strategically positioned back-to-back along the user's spine, accurately capturing and mimicking the natural movements of the spine in both flexion and extension movements. The acquired data may be transmitted in real-time to a dedicated mobile application allowing the user to correct the poor posture habits promptly. The mobile application may facilitate recalibration of sensor data based on the desired back position of the wearer.