Pure-Tone Acoustic Motion Tracking on Smartphone Hardware
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Solution Overview
Problem
Conventional motion detection techniques, such as those using three-axis accelerometers and sound-based methods, require direct contact or specialized hardware, are inaccurate, uncomfortable, and inaccessible to most users, particularly for applications like sleep tracking and home security.
Innovation Solution
A method using pure tone acoustic signals transmitted and reflected by a target, analyzed through Discrete Fourier Transform (DFT) of the received signal, to estimate motion and direction relative to a microphone, employing inaudible frequencies and available smartphone hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If contactless motion detection using electromagnetic or ultrasonic waves is used, then motion detection accuracy is improved, but device complexity and accessibility deteriorate due to requiring specialised transmitters and receivers
Solution Approach 1:
The patent replaces electromagnetic and ultrasonic wave-based motion detection systems with an acoustic-based system using pure tones. This substitution uses standard smartphone speakers and microphones instead of specialised transmitters and receivers, thereby reducing device complexity while maintaining contactless motion detection capability.
Solution Approach 2:
The patent uses the existing acoustic hardware (speaker and microphone) in smartphones to perform motion detection, effectively copying the functionality of specialised radar or ultrasonic systems using readily available components. This allows standard smartphones to achieve motion tracking without requiring additional specialised hardware.
2Adaptability or versatility
If sound-based contactless motion detection using available smartphone hardware is used, then accessibility is improved, but measurement precision and sensitivity deteriorate
Solution Approach 1:
The patent changes the acoustic parameters by using pure tones at specific frequencies (including ultrasonic ranges above 20 kHz) instead of broadband sounds or lower frequency tones. This parameter change enables the standard smartphone hardware to achieve higher measurement precision and sensitivity for detecting slow motions below 10 cm/s, while maintaining accessibility through use of available devices.
3Measurement precision
If frequency-modulated sound signals (chirps) are used for motion detection, then measurement precision is improved, but harmful factors increase due to ear sensitivity to frequency changes
Solution Approach 1:
The patent uses periodic pure tone signals instead of frequency-modulated chirps. By transmitting continuous or periodically pulsed pure tones at fixed frequencies (including ultrasonic frequencies above human hearing range), the system maintains measurement precision while eliminating the harmful effect of audible frequency modulation that causes discomfort to users.
Solution Approach 2:
The patent changes the signal frequency parameter to use ultrasonic frequencies above 20 kHz, which are inaudible to humans. This parameter change eliminates the harmful effect of audible chirp sounds while maintaining the Doppler shift measurement capability for accurate motion detection.
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
Accurately tracks motion slower than 10 cm/s with high sensitivity and directionality, using inaudible tones, improving user comfort and accessibility while reducing energy consumption.
Implementation Method 1
reception of the signal reflected by a target ensonified by the transmitted signal
Implementation Method 2
GB2437619 discloses a Doppler measurement with a pure tone
Data Source
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AI summary
Apparatus is provided to detect motion of a target reflecting one or more pure tone signals, comprising transmission of one or more pure tone acoustic signals, reception of the signal reflected by a target ensonified by the transmitted signal, and motion detection of the ensonified target from analysis of the Discrete Fourier Transform (DFT) of the received signal, in particular values of the time-variance of energy within adjacent frequency bins in the signal DFT, where the emitted tone has a frequency at the boundary between the two adjacent frequency bins.