AI Electric Wheelchair Control for Adaptive User Authentication
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Solution Overview
Problem
Existing electric wheelchairs do not adequately adapt to the impairment conditions and health status of users, particularly for those with hearing or visual impairments, and individuals with limited mobility, leading to difficulties in obstacle avoidance and control, especially in shared environments like medical institutions.
Innovation Solution
An artificial intelligence-based control system that adapts operation modes based on user impairment and health conditions, utilizing sensors for authentication and adaptive control, including voice, face, and gesture recognition, and autonomous driving, with customizable user authentication through machine learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional warning alarms are used in electric wheelchairs, then obstacle detection capability is improved, but accessibility is worsened for users with hearing or visual impairments
Solution Approach 1:
The patent implements multi-functional warning systems that can operate through multiple channels (audible alarms, visual displays, tactile vibrations, and wireless notifications to user devices) simultaneously. This ensures that users with different impairment types can receive obstacle warnings through their preferred sensory modality, making the system universally accessible while maintaining reliable obstacle detection.
Solution Approach 2:
The patent introduces an intermediary communication system that includes wireless transmission to user devices (smartphones, tablets) and adaptive interface elements. This intermediary layer translates obstacle detection information into multiple forms of communication that can be perceived by users with impairments, bridging the gap between detection capability and user accessibility.
2Ease of manufacture
If standard control mechanisms like joysticks are used in electric wheelchairs, then basic operation is maintained, but usability is worsened for users with limited mobility or quadriplegia
Solution Approach 1:
The patent replaces traditional mechanical control interfaces (joysticks, hand controls) with alternative interaction modalities including voice recognition, eye tracking, head movements, and wearable sensor inputs. This substitution maintains the essential control function while eliminating the need for manual dexterity, making the system usable for users with limited mobility or quadriplegia.
Solution Approach 2:
The patent implements a dynamic control system that can adapt the interface based on the user's capabilities and preferences. The system learns from user interactions and environmental context to automatically adjust control mechanisms, switching between different input methods as needed. This dynamic adaptation ensures ease of operation across diverse user abilities without requiring manual reconfiguration.
3Ease of operation
If electric wheelchairs are designed for individual use, then user comfort is optimized, but resource utilization is worsened in shared environments like medical institutions
Solution Approach 1:
The patent implements self-service features including automatic user authentication, personalized interface configuration, and autonomous obstacle detection and warning systems. When a user approaches the wheelchair, the system automatically identifies them through sensors, loads their preferred settings, and initiates appropriate control modes without manual intervention. This self-service capability ensures that each user receives personalized attention and comfort while enabling rapid transitions between users in shared environments.
Solution Approach 2:
The system performs preliminary actions by pre-configuring control parameters, authentication protocols, and interface settings based on stored user profiles before the actual usage begins. This preparation occurs automatically in the background, allowing users to simply sit down and begin using the wheelchair without manual setup, thereby optimizing both comfort and efficiency in shared settings.
4Measurement precision
If multiple sensors are combined for comprehensive obstacle detection, then detection accuracy is improved, but system complexity increases
Solution Approach 1:
The patent merges multiple sensor types (cameras, ultrasonic sensors, LIDAR, radar) into a unified detection system with centralized processing. The sensor fusion architecture combines data from different modalities to achieve comprehensive and accurate obstacle detection while managing complexity through integrated control. The system prioritizes sensor activation and data processing based on operational context, maintaining high detection accuracy without overwhelming complexity.
Data Source
AI summary
An artificial intelligence-based electric wheelchair control method includes performing a booting procedure according to power application to pair with a user device; obtaining user information from a server through the paired user device; determining an operation control mode of an electric wheelchair based on the user information; recognizing a predefined start command through a sensor corresponding to the determined operation control mode when an always-on display (AOD) screen is in an inactive status; activating the inactivated screen according to the start command, outputting a user interface screen for controlling the electric wheelchair on a display device and waiting for a user input signal; performing machine learning on a user input signal input through the sensor to perform user identification and authentication; and identifying a control command corresponding to the user input signal to control the operation of the electric wheelchair, based on the fact that the authentication is successful.