Vision Change Detection Using Display Distance and Tilt Sensors
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Solution Overview
Problem
Gradual changes in human vision can be insidious and difficult to recognize, leading to delayed detection and intervention, especially in individuals with limited access to healthcare, which can result in increased damage and treatment costs.
Innovation Solution
A system that gathers and analyzes input data, including distance and tilt angle data between a user and a display device, to detect changes in vision over time, using sensors such as time-of-flight cameras and image sensors, and processes this data to determine visual acuity and dilation metrics, generating recommendation data for potential vision issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If regular health care access is maintained, then vision changes can be detected early, but this increases healthcare cost and accessibility requirements
Solution Approach 1:
The system enables self-monitoring of vision changes by automatically tracking distance data, tilt angle data, and other visual parameters using sensors already present in display devices. Users can monitor their own vision changes without requiring regular visits to healthcare providers, making the system accessible to anyone with a smartphone or tablet.
Solution Approach 2:
The system introduces a digital intermediary that bridges the gap between users and healthcare providers. By collecting and analyzing vision data automatically, the system can alert users and providers to potential vision changes before they become significant, reducing the need for frequent in-person visits while maintaining early detection capability.
2Loss of time
If vision monitoring is performed continuously, then early detection of vision changes is enabled, but this increases data processing complexity and energy consumption
Solution Approach 1:
The system performs vision monitoring at periodic intervals rather than continuously. It collects data at regular intervals during display device usage, processes the data to detect changes, and compares results against established thresholds. This periodic approach enables early detection while significantly reducing computational load and energy consumption compared to continuous monitoring.
Solution Approach 2:
The system pre-establishes baseline vision metrics and change thresholds during an initial calibration phase. By preparing reference data and detection criteria in advance, the system can quickly identify vision changes during subsequent monitoring without requiring complex real-time analysis, thereby reducing processing energy requirements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables early detection of vision changes, facilitating quicker interventions and improving user well-being by providing recommendations for healthcare consultations and mitigating the effects of vision degradation through adaptive display settings.
Implementation Method 1
sensors such as time-of-flight cameras
Implementation Method 2
image sensors
Data Source
AI summary
Information about changes in vision over time is useful to determine the health of a user. An electronic device has a display that presents visual information to a user. A sensor generates distance data that is used to determine a distance between the user and the display at particular times. Other data may also be acquired that is indicative of whether the user is wearing glasses, tilt of the user's head relative to the display, ambient light level, display brightness, what is being presented on the display such as video content or text content, font size, and so forth. The data is used to determine if the user's vision has changed beyond a threshold amount. If so, an action may be taken, such as providing a recommendation to the user. For example, the user may be advised to consult a health care provider.