HMD Motion Sensor Privacy via Active Noise Cancellation
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Solution Overview
Problem
Motion sensors on head-mounted displays can inadvertently capture and leak speech vibrations, potentially violating users' privacy even when the microphone is off or not present, as these sensors are highly sensitive to subtle vibrations.
Innovation Solution
Incorporating a processor that generates, subtracts, or filters signals from motion sensors to remove or obfuscate voice-generated components, using active noise cancellation algorithms and adding pseudo-random noise in the human voice frequency range to protect user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion sensors are mounted on HMD to track head pose for VR/AR applications, then motion tracking precision is improved, but speech privacy is compromised due to sensitivity to speech vibrations
Solution Approach 1:
The patent uses the harmful speech vibration signals detected by motion sensors and converts them into beneficial noise cancellation data. By treating the speech vibrations as noise to be cancelled rather than useful data, the system protects user privacy while maintaining motion tracking functionality through active noise cancellation techniques
Solution Approach 2:
The patent introduces audio signals from microphones as intermediary elements to cancel speech vibrations in motion sensor data. The microphone signals serve as mediators that, when processed through noise cancellation algorithms, remove speech-related vibrations from motion sensor readings, thereby protecting privacy without compromising motion tracking
2Object-affected harmful factors
If noise cancellation algorithms are applied to remove speech vibrations from motion sensor signals, then speech privacy is protected, but motion sensor signal quality deteriorates
Solution Approach 1:
The patent applies partial noise cancellation by selectively removing only speech-related frequency components from motion sensor signals rather than cancelling all vibrations. By targeting specific frequency ranges associated with speech (typically 85-255 Hz for fundamental frequency and harmonics), the system protects privacy while preserving motion tracking accuracy in non-speech frequency ranges
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
Effectively reduces the ability of malicious developers to eavesdrop on HMD users by ensuring that speech recognition and speaker recognition are not possible from motion sensor signals, maintaining user privacy even when the microphone is off.
Implementation Method 1
The processor is configured to execute one or more of (a) subtract signals from at least one microphone from the signals generated by the motion sensor to render a first signal
Implementation Method 2
add noise into the signals generated by the motion sensor to render a third signal. The processor is configured to transmit one or more of the first, second, or third signal to an application using motion sensor signals
Data Source
AI summary
To protect a user's privacy by reducing a malicious developer's ability to eavesdrop on unwitting HMD users by converting signals from a motion sensor in the HMD to speech or speaker recognition, a microphone can record ambient sound and voice which is subtracted from the motion sensor data before the sensor data is made available to the game developer. Additionally, ANC (active noise cancellation) techniques can be adapted to cancel noise from a motion sensor's data. In another technique, a band pass filter subtracts frequency in the sensor signals within the voice range. Still a third technique blends statistical noise into the motion sensor signal before passing to game developers to obfuscate the user's speech.