AI-Adjustable CAM Boot Control for Real-Time Support Adaptation
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Solution Overview
Problem
Traditional CAM boots offer a static solution to dynamic foot and ankle movements, failing to accommodate individual user variations, leading to discomfort and reduced performance.
Innovation Solution
An AI-based system that integrates sensors, machine learning algorithms, and wireless communication to automate real-time adjustments of CAM boots based on predictive analytics of live sensory data, using a CAM Boot Control Server (CBCS) to process data from multiple sources and generate adjustment commands for actuators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If static design parameters are used in CAM boots, then manufacturing complexity is reduced and ease of manufacture is improved, but adaptability to individual user variations deteriorates
Solution Approach 1:
The patent implements dynamic adjustment mechanisms that allow the CAM boot to change its structural parameters in real-time based on user needs. The boot includes adjustable components such as lateral movement constraints, heel elevation, and toe elevation that can be modified dynamically through actuators controlled by a microprocessor, transforming a static device into an adaptive one without requiring complex custom manufacturing for each user.
Solution Approach 2:
The system changes physical parameters of the boot structure through automated adjustment mechanisms. The microprocessor controls actuators that modify lateral movement constraints, heel elevation angles, and toe elevation angles, allowing the same boot to adapt to different users and conditions by changing its structural parameters rather than requiring different boot designs.
2Adaptability or versatility
If manual mechanical adjustments are provided, then adaptability is improved, but ease of operation deteriorates due to user burden
Solution Approach 1:
The CAM boot system performs self-adjustment through automated actuators controlled by a microprocessor that responds to sensor input and pre-programmed instructions. The device adjusts its own structural parameters including lateral movement constraints and elevation angles without requiring manual intervention from the user, making the system both adaptive and easy to operate.
Solution Approach 2:
The system incorporates sensors that monitor user movement, pressure, and positional data, providing feedback to the microprocessor which automatically adjusts the boot parameters in response. This closed-loop feedback mechanism enables the boot to adapt to user needs automatically, eliminating the need for manual adjustment while maintaining high adaptability.
3Loss of information
If sensor integration is added to monitor activity, then information capability is improved, but device complexity increases
Solution Approach 1:
The microprocessor-based control system serves multiple functions: it processes data from various sensors (pressure sensors, motion sensors), controls multiple actuators for different adjustment mechanisms, stores user profiles and preferences, and communicates with external devices. This multi-functional approach consolidates complexity into a single intelligent controller rather than requiring separate systems for each function.
Solution Approach 2:
The patent combines sensor integration, data processing, actuator control, and user interface functions into a unified microprocessor-based system. The control system merges multiple subsystems (sensors, actuators, memory, communication modules) into an integrated architecture, reducing overall system complexity while enabling comprehensive monitoring and adjustment capabilities.
4Adaptability or versatility
If automated real-time adjustments are implemented, then adaptability and user comfort are improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The system implements dynamic adjustment capabilities through a microprocessor-controlled actuator system that can modify boot parameters in real-time. The actuators are integrated into the boot structure and can be controlled to adjust lateral movement constraints, heel elevation, and toe elevation dynamically, providing high adaptability through automated real-time changes.
Solution Approach 2:
The automated system changes physical parameters of the boot structure through controlled actuation. The microprocessor regulates the position and movement of adjustable components, modifying lateral constraints and elevation angles in response to sensor feedback and user needs, enabling real-time parameter changes that enhance adaptability.
Data Source
AI summary
A system for an automated remotely adjustable Controlled Ankle Movement (CAM) boot including a processor of a CAM boot control server node configured to host a machine learning (ML) module and connected to at least one user mobile device connected to at least one target CAM boot controller over a wireless network connection and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: acquire sensory data from a plurality of sensors integrated into a base of the at least one target CAM boot; process the sensory data for noise reduction and fluctuation consistency; derive a plurality of features reflecting metrics related to wearing of the at least one target CAM boot by a user; generate at least one classifier vector based on the plurality of features; provide the at least one classifier vector to the ML module configured to generate a predictive model for producing at least one CAM boot adjustment parameter; generate a control command for adjustment of the CAM boot based on the at least one CAM boot adjustment parameter and send the control command to the at least one target CAM boot controller.