Audio-Visual Device Health Data Aggregation
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Solution Overview
Problem
Conventional audio/visual devices do not effectively address user health and wellness issues during content consumption, leading to adverse effects such as nausea, eyestrain, and headaches, as users often unknowingly suffer from these issues until after media consumption.
Innovation Solution
A system that aggregates health and wellness data from sensors and healthcare providers to automatically adjust A/V device settings, such as volume and brightness, to minimize adverse health effects by determining optimal user preferences based on sensed and provided data, and shares these preferences across multiple devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If A/V device settings are manually calibrated by users, then device complexity is reduced, but user health and wellness issues are not effectively addressed
Solution Approach 1:
The system performs preliminary health assessments and sensor calibrations before media consumption begins. Health data is collected in advance from wearables and healthcare providers, and A/V settings are pre-adjusted based on this data to prevent adverse health effects rather than reacting to them afterward.
Solution Approach 2:
The system automatically monitors user health metrics through integrated sensors and wearables, then self-adjusts A/V device settings without requiring manual user intervention. The system serves itself by using its own collected health data to make real-time adjustments to brightness, volume, and other parameters.
2Reliability
If A/V device settings are automatically adjusted based on real-time sensor data, then adverse health effects are reduced, but device complexity increases
Solution Approach 1:
The system integrates multiple functions into a unified platform: health data collection from various sources (wearables, healthcare providers), real-time sensor monitoring, automated A/V settings adjustment, and cross-device synchronization. This multi-functional approach manages complexity by consolidating diverse functions under a single system architecture.
Solution Approach 2:
The system introduces intermediary components including health data aggregation services, machine learning models for interpreting sensor data, and communication protocols that bridge wearables, healthcare provider systems, and A/V devices. These intermediaries manage complexity by providing standardized interfaces between different system components.
3Measurement precision
If health data is aggregated from multiple sources including healthcare providers, then measurement precision of user health status is improved, but loss of time for data aggregation increases
Solution Approach 1:
Health data from healthcare providers and baseline metrics from wearables are collected and processed in advance before media consumption sessions. This preliminary data aggregation reduces the time required during actual viewing, as the system already has user health profiles and can make rapid adjustments without waiting for real-time data collection.
Solution Approach 2:
The system implements continuous feedback loops where sensor data during media consumption is immediately processed and used to adjust settings. Health metrics are monitored in real-time, and the system provides rapid feedback adjustments to A/V parameters, minimizing the perceived time delay between data collection and action.
4Object-affected harmful factors
If A/V device settings are customized for each user based on health data, then user comfort is enhanced, but ease of operation decreases due to automatic adjustments
Solution Approach 1:
The system automatically monitors user health metrics and self-adjusts A/V settings without requiring manual user intervention. Users benefit from personalized comfort optimization while the system handles all adjustments autonomously based on real-time sensor data and individual health profiles.
Solution Approach 2:
The system provides dynamic, real-time adjustments to A/V settings based on changing user health conditions during media consumption. Rather than static pre-configured settings, the system continuously adapts brightness, volume, and other parameters to match the user's current physiological state, enhancing comfort while maintaining simplicity.
Data Source
AI summary
A process receives, with a receiver, health and wellness data of a user that is sensed by one or more sensors during consumption by the user of media content. Further, the process receives, with the receiver, health and wellness data of the user that is determined by a healthcare provider during an event that is distinct from the consumption of the media content. In addition, the process aggregates, with a processor, the health and wellness data of the user that is sensed and the health and wellness data of the user that is determined by the health care provider into an aggregated health and wellness data model. The process also determines, with the processor, one or more optimal audio/visual device settings based on the aggregated health and wellness data model.