Wearable Acoustic Sensing for Low-Complexity Activity Detection

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Solution Overview

Problem

Conventional wearable devices for user activity detection and facial expression recognition often rely on complex and resource-intensive sensor arrangements, such as inertial measurement units (IMUs), which are costly and inefficient.

Innovation Solution

The use of wearable devices equipped with wireless transmitter-receiver pairs for acoustic sensing, allowing for the detection of user activities and facial expressions through the transmission and reception of acoustic signals, processed using machine learning systems.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional sensor arrangements such as inertial measurement units (IMUs) are used for user activity detection, then user activity detection capability is achieved, but device complexity and cost increase

Engineering Contradiction:

Improveuser activity detection capabilityVSAvoidsensor arrangement complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent replaces mechanical sensor systems (IMUs) with an acoustic sensing system using wireless transmitter-receiver pairs. The system transmits acoustic signals that reflect off the user's body and are received back, with machine learning algorithms processing these acoustic echoes to detect user activities, thereby eliminating complex mechanical sensors while maintaining detection capability

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces acoustic signals as an intermediary medium between the wearable device and the user's body. The transmitter sends acoustic signals that interact with the user's body movements, and the receiver captures the reflected signals, allowing indirect but effective detection of user activities without direct mechanical contact or complex sensor arrays

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If conventional sensor arrangements such as inertial measurement units (IMUs) are used for user activity detection, then user activity detection capability is achieved, but manufacturing cost increases

Engineering Contradiction:

Improveuser activity detection capabilityVSAvoidmanufacturing cost

Core Design Contradiction:

ReliabilityVSEase of manufacture

Solution Approach 1:

The patent employs inexpensive acoustic transmitters and receivers that can be mass-produced at low cost, replacing expensive IMU sensors. The acoustic signal generation and reception components are significantly cheaper to manufacture while achieving comparable or superior detection performance through software-based processing

Inventive Principle:

Principle #27Cheap short-living objects (Disposable)

Solution Approach 2:

The patent substitutes costly mechanical sensor systems with acoustic field-based sensing, where the primary costs are in software development and processing rather than hardware manufacturing, thereby reducing overall manufacturing expenses while maintaining detection reliability

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If conventional sensor arrangements are used for facial expression recognition, then facial expression detection is achieved, but resource consumption increases

Engineering Contradiction:

Improvefacial expression recognition capabilityVSAvoidprocessing and memory resources

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent replaces resource-intensive computer vision-based facial recognition with acoustic sensing. The transmitter-receiver pairs capture acoustic reflections from facial muscle movements, and machine learning models process these acoustic signals to recognize facial expressions, consuming significantly fewer computational and memory resources compared to image-based approaches

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

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 enables efficient and cost-effective user activity detection and facial expression recognition, reducing the need for complex sensor arrangements and minimizing resource usage.

Implementation Method 1

The transmitter of the wireless transmitter-receiver pair transmits an acoustic signal, and the receiver of the wireless transmitter-receiver pair receives the acoustic signal

Methodology Applied

Scientific EffectAcoustic signal transmission and reflection: Sound

Data Source

PatentUS20250060782A1Wearable devices with wireless transmitter-receiver pairs for acoustic sensing of user characteristics

Publication Date: 2025.02.20 CORNELL UNIVERSITY

AI summary

An apparatus in one embodiment comprises at least one wearable device, with the at least one wearable device comprising at least one of a transmitter and a receiver of a wireless transmitter-receiver pair. The transmitter of the wireless transmitter-receiver pair transmits an acoustic signal, and the receiver of the wireless transmitter-receiver pair receives the acoustic signal. The received acoustic signal is processed utilizing a machine learning system to detect at least one characteristic of a user of the at least one wearable device. In some embodiments, a given wearable device comprises at least first and second wireless transmitter-receiver pairs, with the transmitter of each of the first and second wireless transmitter-receiver pairs transmitting an acoustic signal having a different carrier frequency. In such embodiments, a multi-channel echo profile may be generated using the multiple acoustic signals and classified by the machine learning system to detect the at least one characteristic.