Sensor-Detected Mobile UI Adaptation for Application Accessibility
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Solution Overview
Problem
Existing mobile device accessibility settings do not adequately address the unique accessibility needs of different applications, failing to provide sufficient assistance for users with impairments such as visual or manual dexterity issues.
Innovation Solution
A mobile device system that detects accessibility patterns through sensors like proximity, cameras, and accelerometers to modify the user interface of applications, tailoring adjustments such as text size, layout, and auditory feedback to enhance user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If default accessibility settings are provided by the mobile device, then general accessibility is improved, but application-specific accessibility needs are not addressed
Solution Approach 1:
The system segments accessibility assistance by application, creating separate accessibility patterns and modifications for each application rather than using a single global setting. This allows each application to have customized accessibility adjustments based on its specific interface and requirements.
Solution Approach 2:
The system applies local quality by making accessibility modifications specific to each application's user interface. Different applications receive different types of modifications (e.g., font size changes, button enlargement, layout adjustments) tailored to their specific needs and the user's detected impairments.
2Ease of operation
If the user interface is modified to aid accessibility, then ease of interaction is improved, but device complexity increases
Solution Approach 1:
The system employs self-service by automatically detecting accessibility patterns through sensor data and autonomously modifying the user interface without requiring manual configuration. The device monitors user interactions and sensor inputs to identify accessibility needs and applies appropriate modifications automatically.
Solution Approach 2:
The system uses feedback mechanisms by continuously monitoring sensor data and user interactions to detect accessibility patterns. The detected patterns trigger automatic interface modifications, and the system continues to monitor to ensure the modifications are effective and adjust if needed.
3Measurement precision
If sensor data is recorded to detect accessibility patterns, then accessibility detection accuracy is improved, but data processing requirements increase
Solution Approach 1:
The system applies partial action by recording and analyzing only the specific sensor data necessary for detecting accessibility patterns, rather than processing all possible sensor inputs. It focuses on relevant patterns such as holding duration, proximity, and interaction difficulty indicators.
Data Source
AI summary
Disclosed herein are various embodiments for detecting predefined accessibility patterns for modifying a user interface of a mobile device. An embodiment operates by determining a plurality of pre-defined accessibility patterns each of which correspond to one or more user interactions by a user with a mobile device. Sensor data indicating that a user is unable to hold the mobile device steady is received. A first pre-defined accessibility pattern that corresponds to the indication that the user is unable to hold the mobile device steady is identified. A modification to a user interface is determined, and the user interface is modified in accordance with the determined modification corresponding to the first pre-defined accessibility pattern.