Wearable Compression Therapy With Sensor-Based Recovery Adjustment
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Solution Overview
Problem
Existing dynamic compression therapy systems lack the ability to customize and adjust therapy parameters based on individual recovery levels of subjects, leading to suboptimal exercise recovery outcomes.
Innovation Solution
A wearable compression system with inflatable chambers controlled by a controller device that adjusts operation parameters based on cardiac-related data and exercise data from sensors, such as a HealthKit data from an APPLE® watch or embedded PPG/ECG sensors, to provide personalized dynamic compression therapy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dynamic compression therapy is applied with fixed parameters, then the therapy can be easily implemented, but the recovery effectiveness is suboptimal due to lack of customization
Solution Approach 1:
The compression system transitions from fixed parameters to dynamic, adjustable parameters that respond to real-time sensor data. The controller automatically modifies compression intensity, duration, and frequency based on measured physiological indicators such as heart rate and movement, enabling the system to adapt to individual recovery needs without requiring manual reconfiguration.
Solution Approach 2:
The system incorporates sensors that continuously monitor physiological parameters and feed this information back to the controller. Based on this feedback loop, the system adjusts compression therapy parameters in real-time to optimize recovery effectiveness for each user, transforming a static therapy device into an adaptive, response-driven system.
2Adaptability or versatility
If compression therapy parameters are manually adjusted, then therapy can be customized to individual needs, but the ease of operation is reduced
Solution Approach 1:
The system performs self-adjustment by automatically interpreting sensor data and modifying compression parameters without user intervention. The controller analyzes physiological signals and autonomously optimizes therapy settings, eliminating the need for users to manually configure complex parameters while still achieving personalized recovery protocols.
Solution Approach 2:
The manual mechanical adjustment process is replaced with an automated electronic control system. Instead of requiring users to physically adjust compression settings, the system uses electronic sensors and controllers to automatically regulate therapy parameters based on real-time physiological data, simplifying operation while maintaining customization.
3Reliability
If real-time sensor monitoring is implemented, then therapy can be optimized based on actual recovery levels, but the device complexity and cost increase
Solution Approach 1:
The sensor system is designed with multi-functionality, where a single sensor array serves multiple purposes: monitoring heart rate, detecting movement, and assessing recovery status. This universal approach reduces overall system complexity by consolidating sensor functions rather than requiring separate dedicated sensors for each measurement type.
Solution Approach 2:
The system monitors changes in physiological parameters over time to assess recovery progression. By tracking parameter trends rather than requiring complex real-time analysis, the system achieves reliable recovery optimization through simpler data processing methods that focus on parameter transitions and patterns.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances exercise recovery by improving blood flow, reducing muscle soreness, and expediting the recovery process through customized pressure, frequency, and duration adjustments based on real-time feedback from sensors.
Implementation Method 1
Dynamic compression therapy (DCT), also known as intermittent pneumatic compression (IPC), is a type of compression therapy that uses inflatable garments to apply sequential, pulsating pressure to the limbs
Implementation Method 2
health data (such as, cardiac-rate related data) and/or exercise/activity data from a related sensor associated with the subject
Implementation Method 3
continuous input from suitable sensors, such as, heart-related sensors (such as, for example, PPG or ECG sensor)
Data Source
AI summary
Provided herein is a compression system for providing adjusted dynamic compression therapy for recovery from exercise to a subject in need thereof, wherein the operation parameters are adjusted based on health and/or activity data, including, cardiac-related data, derived from signals obtained from a related sensor associated with the subject. Further provided are methods of using the system for determining and/or facilitating recovery from exercise.