Adaptive Exercise Threshold System for Neurological Response
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing exercise protocols use generalized frequency and power thresholds that are ineffective for individuals with atypical neurological patterns or those outside the statistical average, failing to provide personalized exercise guidance for maximizing neurological responses in conditions like Parkinson's Disease and Progressive Supranuclear Palsy.
Innovation Solution
A system that uses real-time data from sensors to determine and adjust individual exercise thresholds by calculating and displaying cues for frequency and power, utilizing a system controller, exercise equipment with sensors, and a display to guide participants to maintain optimal neurological responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If generalized frequency and power thresholds are used for all participants, then the exercise protocol is simple to implement, but it fails to maximize neurological responses for individuals with atypical neurological patterns
Solution Approach 1:
The system dynamically adjusts frequency and power thresholds in real-time based on individual participant responses during exercise. Sensors continuously monitor physiological parameters and the controller modifies threshold values to optimize neurological responses, transforming static generalized thresholds into adaptive personalized thresholds
Solution Approach 2:
The system automatically determines and adjusts individual exercise thresholds without requiring pre-exercise testing or manual calibration for each participant. The sensors and controller work together to self-calibrate the thresholds based on real-time performance data, eliminating the need for complex setup procedures
2Reliability
If pre-exercise data collection and testing are required to establish thresholds, then personalized thresholds can be determined, but the exercise protocol becomes complex and time-consuming
Solution Approach 1:
The system performs preliminary threshold determination automatically during the first exercise session without requiring separate testing procedures. The sensors collect initial performance data and the controller establishes baseline thresholds that are then used to guide subsequent exercise sessions
Solution Approach 2:
The system replaces manual threshold determination methods with an automated electronic system consisting of sensors and a controller. This substitution eliminates the need for complex manual testing and data analysis procedures, automatically calculating thresholds from sensor data
3Stability of the object's composition
If historical performance data is used to set thresholds, then the system can provide consistent guidance, but the thresholds become outdated and ineffective for current exercise sessions
Solution Approach 1:
The system continuously monitors current exercise performance through sensors and uses this real-time feedback to adjust thresholds. The controller compares actual performance against target thresholds and modifies the thresholds based on current session data, ensuring they remain current and effective
Solution Approach 2:
The system maintains continuous monitoring and adjustment of thresholds throughout exercise sessions rather than relying on discrete historical data points. This continuous action ensures thresholds are always based on the most current performance information available
Data Source
AI summary
A system to determine and dictate individual exercise thresholds to maximize desired neurological responses.