HMD Smartphone Motion Authentication via Sensor Fusion
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Solution Overview
Problem
Existing display systems for mobile terminal devices, such as smartphones, face challenges in efficiently performing personal authentication, particularly when the device is in a sleep state, requiring users to input authentication codes manually, which can be time-consuming.
Innovation Solution
A display system comprising a Head-Mounted Display (HMD) and a smartphone with integrated sensors like illuminance, acceleration, and geomagnetic sensors, which perform personal authentication based on user motion detection until a position input operation is initiated, allowing for alternative authentication via a code input if initial detection fails, and utilizing machine learning for improved identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If personal authentication is performed using traditional methods (e.g., authentication code input) when the smartphone is in sleep state, then authentication security is maintained, but authentication time increases
Solution Approach 1:
The system performs preliminary motion detection and user identification before the authentication process is formally initiated. By detecting user motion patterns (pickup, approach, grasping) in advance and pre-identifying the user, the system prepares authentication data beforehand, significantly reducing the actual authentication time when the user needs to access the device.
Solution Approach 2:
The system uses the user's own motion patterns and behavior characteristics as the authentication mechanism. Instead of requiring the user to manually input authentication codes, the device automatically detects and analyzes the user's natural motions (how they pick up, hold, and interact with the device) to perform authentication, making the process effortless and self-service oriented.
2Productivity
If motion-based automatic authentication is implemented, then authentication speed is improved, but system complexity increases due to additional sensors and processing
Solution Approach 1:
The patent leverages existing multi-functional sensors (acceleration sensor, gyro sensor, illuminance sensor) that serve multiple purposes: they detect device orientation, screen brightness requirements, and user motion patterns for authentication. By making these existing sensors serve the additional authentication function, the system avoids adding dedicated hardware while enabling motion-based authentication.
Solution Approach 2:
The system introduces a dedicated user identification unit that acts as an intermediary between sensor data collection and authentication decision-making. This unit synthesizes data from multiple sensors, compares detected motion patterns against stored user profiles, and determines authentication outcomes, thereby managing system complexity through modular architecture.
3Measurement precision
If multiple sensors are used for motion detection, then authentication accuracy is improved, but energy consumption increases
Solution Approach 1:
The system employs periodic sampling of sensor data rather than continuous monitoring. Sensors are activated at specific intervals or triggered by event-based conditions (e.g., detecting device pickup motion), allowing the system to collect sufficient authentication data while minimizing continuous energy consumption from constant sensor operation.
Solution Approach 2:
The system performs preliminary analysis of sensor data to determine whether authentication-level detail is needed. For example, initial acceleration data may indicate whether the device was picked up, triggering more detailed gyro and illuminance sensor measurements only when necessary, thereby reducing overall energy consumption while maintaining authentication accuracy.
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
This approach reduces the time and labor required for personal authentication, enhances security by regulating unauthorized access, and improves authentication accuracy through motion-based detection and machine learning profiling.
Implementation Method 1
the first sensor includes an illuminance sensor, and the first execution unit executes personal authentication of the user based on a detection result of the first sensor, from the time when the illuminance detected by the illuminance sensor reaches a threshold illuminance or greater until when the user starts the position input operation
Implementation Method 2
the first sensor may include at least one of an acceleration sensor, a gyro sensor, and a geomagnetic sensor, and the first sensor detects a movement of the information processor
Implementation Method 3
the first sensor may include at least one of an acceleration sensor, a gyro sensor, and a geomagnetic sensor
Implementation Method 4
the first sensor may include at least one of an acceleration sensor, a gyro sensor, and a geomagnetic sensor
Data Source
AI summary
The present disclosure provides a display system including a HMD mounted on a head of a user and a smartphone coupled to the HMD. The smartphone includes a touch sensor configured to accept a position input operation to detect coordinates of an operational position, a first sensor configured to detect a motion of the user with respect to the smartphone, and a first execution unit configured to execute personal authentication of the user based on a detection result of the first sensor until the user starts the position input operation.