Biofeedback System Using Adaptive Heart Rate Pulse Modulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wearable devices are insufficient in providing effective insights that induce significant physiological responses in users, relying on insufficient feedback methods such as audio, haptic, and visible light pulses based on heart rate data.
Innovation Solution
A system comprising wearable devices and user devices that collect physiological data, select feedback responses (audio, haptic, or visible light pulses) with adjustable parameters like magnitude, duration, and frequency, to regulate or adjust heart rate, using machine learning models and circadian rhythm adjustments for personalized biofeedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional feedback methods (audio, haptic, visible light pulses) are used to provide heart rate insights, then device complexity is reduced, but the effectiveness of inducing significant physiological responses in users deteriorates
Solution Approach 1:
The system implements a closed-loop feedback mechanism where heart rate data is continuously collected, analyzed against target heart rates, and used to dynamically adjust feedback pulse characteristics (intensity, duration, frequency). This adaptive feedback loop ensures physiological responses are effectively induced while maintaining system manageability through automated control algorithms.
Solution Approach 2:
The patent varies multiple parameters of feedback pulses including intensity, duration, frequency, and timing based on real-time heart rate measurements and user profiles. By dynamically adjusting these parameters, the system achieves effective physiological responses without requiring complex hardware, as the intelligence is embedded in the parameter modulation software.
2Reliability
If generic feedback responses are provided to all users, then device complexity is minimized, but the personalization and effectiveness of biofeedback deteriorates
Solution Approach 1:
The system tailors feedback characteristics to individual users by creating personalized profiles that store preferred pulse types, intensity preferences, and physiological characteristics. Each user receives locally optimized feedback parameters rather than generic responses, achieving personalization through software configuration rather than complex adaptive hardware.
Solution Approach 2:
Users complete setup questionnaires and provide physiological data in advance to create personalized profiles before actual biofeedback sessions. This preliminary action pre-configures feedback parameters for each user, eliminating the need for complex real-time personalization algorithms during active use while maintaining high personalization effectiveness.
3Speed
If post-activity analysis is used to provide insights, then device complexity is reduced, but the timeliness and ability to regulate heart rate in real-time deteriorates
Solution Approach 1:
The system continuously collects heart rate data throughout the activity and performs real-time comparison with target heart rates, providing immediate feedback rather than waiting for post-activity analysis. This continuous monitoring and immediate response capability enables real-time heart rate regulation while using simple computational logic that avoids excessive processing complexity.
Solution Approach 2:
Target heart rates and feedback parameters are pre-determined before activity based on user profiles and activity type. During activity, the system only needs to compare real-time measurements against these pre-set targets, achieving fast real-time response with minimal processing complexity since the decision logic is prepared in advance.
Data Source
AI summary
Methods, systems, and devices for biofeedback are described. A user device may acquire physiological data associated with a user from a wearable device. The user device may select a feedback response that may include one or more of audio, haptic, or visible light feedback. The user device may determine parameters for the feedback response. The parameters may include one or more of a magnitude, a duration, or a frequency, associated with one or more of the audio, haptic, or visible light feedback. The user device or the wearable device may output the feedback response indicative for regulating the physiological data associated with the user.