Ambient Stimuli Selection System for Stress Reduction
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Solution Overview
Problem
Current ambient stimuli systems in hospitals lack the ability to adapt to individual patients' characteristics and stress levels, making it difficult to select effective stimuli for stress reduction.
Innovation Solution
A control system that filters and selects ambient stimuli from a database based on user characteristics, stress reduction capabilities, and user preferences, using a combination of filtering, selecting, and feedback mechanisms to provide personalized and adaptive stimuli.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If ambient stimuli are selected without adaptation to individual patient characteristics, then the system is simple and easy to operate, but the stress reduction effectiveness is limited
Solution Approach 1:
The system performs preliminary actions by collecting patient characteristics and physiological data before stimulus selection, creating a personalized profile that enables subsequent adaptive stimulus selection. This preliminary data collection and profile creation allows the system to adapt to individual patients while maintaining automated operation.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring physiological measurements and stress levels, then using this feedback to adjust and optimize stimulus selection. The feedback loop enables the system to learn from patient responses and improve stress reduction effectiveness over time while maintaining automated operation.
2Device complexity
If ambient stimuli are selected without considering stress reduction capabilities, then the selection process is simple, but the stress reduction effectiveness is poor
Solution Approach 1:
The system changes parameters by evaluating multiple stimulus descriptors based on their associated stress reduction capabilities and patient-specific factors. It selects stimuli by comparing parameter values such as stress reduction potential, patient characteristics, and physiological state, enabling reliable stress reduction through systematic parameter optimization.
Solution Approach 2:
The system performs self-service by automatically evaluating stimulus descriptors and selecting optimal ambient stimuli based on stored stress reduction capability data and current patient state. This automated self-selection process eliminates manual intervention while ensuring reliable stress reduction through data-driven decisions.
3Reliability
If a personalized profile is created through extensive patient interaction, then the stress reduction is highly effective, but the time and complexity required increases significantly
Solution Approach 1:
The system performs preliminary actions by collecting and storing patient characteristic data and physiological measurements in advance, creating a ready-to-use personalized profile. This preliminary data collection enables rapid stimulus selection without requiring extensive real-time interaction, reducing time loss while maintaining effectiveness.
Solution Approach 2:
The system replaces manual mechanical processes of profile creation with automated electronic data collection and processing. By substituting automated sensor-based physiological measurement and computer-based profile generation for manual interaction, the system reduces time requirements while maintaining or improving profile accuracy and stress reduction effectiveness.
Data Source
AI summary
In summary the invention relates to a stimuli control system configured for finding ambient stimuli from a database in a way so that the ambient stimuli having the most promising effect on stress reduction is selected. The selection may be performed based on a probability distribution created for describing how likely it is that a given ambient stimuli has a positive effect on the stress level for a given patient or other user. The database is a multiuser database which may be updated based on experiences from users' already registered ambient stimuli.