Sensor Garment Massage Control With AI Relaxation Feedback
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Solution Overview
Problem
Conventional massage devices and systems fail to automatically adjust massage programs to suit an individual's real-time physiological and psychological state, lacking continuous monitoring and learning from user feedback, resulting in suboptimal relaxation and ineffective personalization.
Innovation Solution
A system comprising a full-body fitting garment with sensors and low-frequency pads, a control unit, and an external information processing device, utilizing an artificial intelligence module to analyze biometric data, generate personalized massage instructions, and learn from user feedback to iteratively improve the massage experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional fixed-pattern massage systems are used, then device complexity is low, but adaptability to individual user states is poor
Solution Approach 1:
The massage system transitions from fixed patterns to dynamic adjustment based on real-time biometric data. The control unit continuously receives biometric information from sensors and automatically modifies massage parameters (intensity, duration, pattern) to adapt to the user's current physiological state, making the system dynamically responsive rather than statically predetermined.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where biometric sensors continuously monitor the user's physiological state (heart rate, skin conductance, temperature), transmit this data to the control unit, which then adjusts the massage output accordingly. This feedback loop enables automatic adaptation without requiring manual user input or complex manual adjustments.
2Adaptability or versatility
If real-time biometric monitoring is implemented, then personalization capability is improved, but device complexity increases
Solution Approach 1:
The control unit serves multiple functions: it manages the massage pad operations, processes biometric data from multiple sensors, generates personalized massage programs, and communicates with the user's smartphone. By consolidating these diverse functions into a single control unit, the system achieves high personalization capability without proportionally increasing overall system complexity.
Solution Approach 2:
The control unit acts as an intermediary between the biometric sensors and the massage pads. It receives raw biometric data from sensors, processes this information to determine appropriate massage parameters, and translates these parameters into control signals for the massage pads. This intermediary role simplifies the system architecture by centralizing the intelligence required for personalization.
3Reliability
If continuous monitoring and learning from feedback are implemented, then massage effectiveness is improved, but loss of time for data processing increases
Solution Approach 1:
The control unit continuously processes biometric data in real-time during the massage session, rather than waiting until the end. It maintains a running analysis of the user's physiological state and makes incremental adjustments to the massage program throughout the session. This preliminary and continuous processing ensures the massage remains effective without requiring lengthy post-session analysis.
Solution Approach 2:
The system maintains continuous monitoring and adjustment throughout the entire massage session. The control unit constantly receives biometric data, processes it, and modifies the massage output in real-time, ensuring the useful action of personalized massage delivery continues without interruption. This eliminates idle processing time and maintains optimal effectiveness throughout the session.
Data Source
AI summary
The system includes a processor that works with a full-body fitting garment equipped with internal sensors and low-frequency pads. It collects biometric data, connects wirelessly to an external device via a control unit, and uses an AI module to visualize the user's relaxation state. Based on this, it generates instructions to optimize relaxation and controls the pads accordingly.