Mood Adjusting System Using Real-Time Biosensor Feedback
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Solution Overview
Problem
Current mood-adjusting systems and methods, such as those used in relaxation platforms like Calm and Headspace, are inefficient and ineffective in automatically tuning to the right settings for individual users, requiring laborious production and a one-size-fits-all approach, which results in mediocre outcomes and lack of personalized experiences.
Innovation Solution
A system that uses real-time biosensors and artificial intelligence to adjust sensory stimuli, such as soundscapes, based on measured biosignals from the subject, providing a personalized and automated relaxation experience by generating soundscape signals to induce desired mood changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time biosensors and AI are used to adjust sensory stimuli, then productivity and effectiveness of mood adjustment is improved, but device complexity increases
Solution Approach 1:
The system automatically monitors biosignals and adjusts sensory stimuli without requiring manual intervention or professional operation. The AI algorithm self-regulates the mood adjustment process by continuously analyzing biosignal data and autonomously modifying stimulus parameters, enabling the system to serve itself and eliminating the need for complex manual control interfaces.
Solution Approach 2:
The system implements closed-loop feedback by continuously monitoring biosignals (heart rate, skin conductance, respiration) and using this real-time data to dynamically adjust sensory stimuli. The AI algorithm processes the feedback from biosensors and automatically modifies stimulus intensity and type to achieve optimal mood adjustment, creating an adaptive control system that responds to individual user needs.
2Reliability
If personalized and automated relaxation experience is provided, then effectiveness and efficiency of stress relief is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The system uses a single integrated platform that can deliver multiple mood adjustment programs and stimulus types (auditory, visual, tactile) through one device. The AI algorithm serves as a universal controller that adapts to different user needs and conditions, eliminating the need for multiple specialized devices or complex manual configuration systems, thereby simplifying manufacturing while maintaining personalized effectiveness.
Solution Approach 2:
The system automatically personalizes the relaxation experience by monitoring individual biosignals and adapting stimuli without requiring manual programming or professional setup. This self-personalization capability eliminates the need for complex manufacturing processes that would be required to create multiple pre-configured personalized systems, while still delivering tailored effectiveness to each user.
3Ease of manufacture
If one-size-fits-all approach is used, then device complexity is reduced, but effectiveness and efficiency of mood adjustment deteriorates
Solution Approach 1:
The system transitions from static pre-programmed stimuli to dynamic real-time adjustment based on biosignal monitoring. The AI algorithm continuously adapts stimulus parameters (intensity, frequency, type) according to the user's current physiological state, enabling the simple device to deliver personalized and efficient mood adjustment that responds to changing user needs throughout the session.
Solution Approach 2:
The system incorporates real-time biosignal feedback to automatically personalize the relaxation experience. By monitoring heart rate, skin conductance, and respiration patterns, the AI algorithm adjusts stimuli to match individual user responses, eliminating the need for complex manual personalization while significantly improving mood adjustment efficiency compared to generic one-size-fits-all approaches.
Data Source
AI summary
Methods, systems, and apparatuses for adjusting a mood of a subject, the method including applying one or more sensory stimuli to a subject, obtaining one or more biosignals from the subject, the one or more biosignals being indicative or correlative of a mood of the subject, generating a stimuli signal to adjust the sensory stimuli applied to the subject, and adjusting the one or more sensory stimuli applied to the subject based on stimuli signal to obtain a desired mood in the subject.