Adaptive Stroke Care App Interface for Dynamic Recovery Support
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Solution Overview
Problem
Current stroke care management systems are inadequate in providing comprehensive support and resources for stroke survivors post-discharge, as they fail to effectively address the dynamic needs and impairments of individuals, leading to a long and arduous recovery process.
Innovation Solution
A mobile software application that tracks the state of stroke survivors post-discharge and generates dynamic user interfaces, including ribbons for learning content tailored to their impairments, with metrics analysis and adaptive content delivery to enhance recovery management and communication with healthcare teams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing stroke care management systems are used post-discharge, then basic medical monitoring is provided, but comprehensive support and resources for stroke survivors are inadequate
Solution Approach 1:
The system dynamically adapts the user interface and learning content delivery based on the stroke survivor's current state, impairment type, and recovery progress. The interface adjusts its complexity, format, and content in real-time to match the user's cognitive and physical capabilities, ensuring comprehensive support that evolves with the patient's needs rather than remaining static
Solution Approach 2:
The system segments learning content into modular units organized by impairment type and recovery stage. Each segment can be independently selected, viewed, and revisited based on the user's specific needs, allowing comprehensive coverage of multiple impairments without overwhelming the user with a monolithic information structure
2Quantity of substance
If learning content is provided without segmentation, then all information is available, but content overwhelming occurs and accessibility decreases
Solution Approach 1:
Learning content is divided into discrete, manageable segments organized by impairment category (e.g., mobility, speech, cognition) and recovery phase. Users access only the segments relevant to their specific impairments, reducing cognitive load while maintaining comprehensive content availability in the background
Solution Approach 2:
The system tailors the presentation quality and format of learning content to match the user's specific impairment profile. For example, visual content may be enhanced for users with hearing impairments, or text may be simplified for users with cognitive impairments, ensuring that the full quantity of content remains accessible to diverse user needs
3Ease of manufacture
If uniform learning content delivery is used, then implementation is simple, but personalization to individual impairments is lost
Solution Approach 1:
The system automatically configures personalized learning content delivery based on impairment profiles without requiring complex manual setup. The personalization logic is embedded in the system architecture, allowing it to adapt to different impairment types and combinations while maintaining a unified implementation framework that doesn't increase complexity
Solution Approach 2:
A single learning content library serves multiple impairment types and recovery stages through a universal delivery system. The same infrastructure delivers personalized content by filtering and adapting based on user profile, eliminating the need for separate content delivery systems for each impairment type while maintaining full personalization capability
Data Source
AI summary
Devices, systems, and methods for generating and updating one or more user interfaces of a mobile software application operating on a smart phone of a stroke survivor having an impairment. The method can include tracking a first state of stroke survivor post discharge. The method can also include generating a first user interface configured to be displayed on the smart phone and is dynamically updated based on the tracked first state of the stroke survivor. Further, the method can include a first ribbon in the first user interface corresponding to a first learning content. Moreover, the method can include splitting the learning content based on the impairment associated with the stroke survivor and a first property of the first learning content. Lastly, the method can include a second ribbon in the first user interface corresponding to a second learning content.


