Saturday, May 17, 2025
News PouroverAI
Visit PourOver.AI
No Result
View All Result
  • Home
  • AI Tech
  • Business
  • Blockchain
  • Data Science & ML
  • Cloud & Programming
  • Automation
  • Front-Tech
  • Marketing
  • Home
  • AI Tech
  • Business
  • Blockchain
  • Data Science & ML
  • Cloud & Programming
  • Automation
  • Front-Tech
  • Marketing
News PouroverAI
No Result
View All Result

Audioplethysmography for cardiac monitoring with hearable devices – Google Research Blog

October 27, 2023
in AI Technology
Reading Time: 3 mins read
0 0
A A
0
Share on FacebookShare on Twitter



Posted by Xiaoran “Van” Fan, Experimental Scientist, and Trausti Thormundsson, Director, Google

The market for true wireless stereo (TWS) active noise canceling (ANC) hearables (headphones and earbuds) has been rapidly growing in recent years. In fact, by 2023, the global shipment volume of TWS ANC hearables is expected to nearly double that of smart wristbands and watches. This growth can be attributed to advancements in ANC, transparency mode, and artificial intelligence, which have significantly extended the on-head time for hearables.

Hearables are no longer just used for music listening; users now wear them for various purposes such as exercising, focusing, and mood adjustment. However, the health aspects of hearables are still relatively unexplored in the consumer market.

In our paper “APG: Audioplethysmography for Cardiac Monitoring in Hearables,” presented at MobiCom 2023, we introduce a new active in-ear health sensing modality. This modality, called Audioplethysmography (APG), allows ANC hearables to monitor a user’s physiological signals, such as heart rate and heart rate variability, without the need for additional sensors or compromising battery life.

APG has several advantages: it is highly resilient to motion artifacts, adheres to safety regulations, remains unaffected by seal conditions, and is inclusive of all skin tones. It works by transmitting a low intensity ultrasound wave through the ANC headphone’s speakers and collecting the receiving wave via the on-board feedback microphones. The APG signal is a pulse-like waveform that synchronizes with the heartbeat and provides rich cardiac information.

The ear canal is an ideal location for health sensing because it receives its blood supply from the deep ear artery, which forms a network of smaller vessels that permeate the auditory canal. Slight variations in blood vessel shape caused by the heartbeat can lead to changes in the volume and pressure of the ear canals, making it an ideal location for health monitoring.

Previous research has explored using hearables for health sensing by incorporating multiple sensors and a microcontroller. However, this approach adds cost, weight, power consumption, acoustic design complexity, and form factor challenges to hearables, making widespread adoption difficult.

ANC hearables already have feedback and feedforward microphones that can detect or record bio-signals inside and outside the ear canal. This passive sensing paradigm has prompted various mobile applications, but consumer-grade ANC headphones come with high-pass filters that limit the quality of the signals. It is challenging to embed health features that rely on low-frequency signals in commercial ANC headphones.

APG overcomes these challenges by using a low intensity ultrasound probing signal. This signal triggers echoes that are modulated by the tiny ear canal skin displacement and heartbeat vibrations. Coherent detection is used to retrieve the micro physiological modulation, resulting in an APG waveform that closely resembles a photoplethysmogram (PPG) waveform but provides more detailed cardiac information.

During our experiments, we found that APG works robustly even with poor earbud seals and music playing. However, it can be noisy and susceptible to body motion interference. To address this, we introduced channel diversity by transmitting multiple frequencies simultaneously. This allows us to capture both cardiac activities and head movements, and select the best frequency for high-quality pulse waveform measurement.

Our field studies with 153 participants showed that APG consistently achieved accurate heart rate and heart rate variability measurements across various activity scenarios. Unlike PPG, APG was resilient to variations in skin tone, seal conditions, and ear canal size.

Overall, APG presents a promising new modality for in-ear health sensing in ANC hearables. It eliminates the need for additional sensors, provides accurate measurements, and overcomes the limitations of existing passive sensing methods.



Source link

Tags: AudioplethysmographyBlogCardiacDevicesGooglehearablemonitoringResearch
Previous Post

Google paid $26 billion in 2021 to become a default search engine

Next Post

Meet Llemma: The Next-Gen Mathematical Open-Language Model Surpassing Current Benchmarks

Related Posts

How insurance companies can use synthetic data to fight bias
AI Technology

How insurance companies can use synthetic data to fight bias

June 10, 2024
From Low-Level to High-Level Tasks: Scaling Fine-Tuning with the ANDROIDCONTROL Dataset
AI Technology

From Low-Level to High-Level Tasks: Scaling Fine-Tuning with the ANDROIDCONTROL Dataset

June 10, 2024
Decoding Decoder-Only Transformers: Insights from Google DeepMind’s Paper
AI Technology

Decoding Decoder-Only Transformers: Insights from Google DeepMind’s Paper

June 9, 2024
How Game Theory Can Make AI More Reliable
AI Technology

How Game Theory Can Make AI More Reliable

June 9, 2024
Buffer of Thoughts (BoT): A Novel Thought-Augmented Reasoning AI Approach for Enhancing Accuracy, Efficiency, and Robustness of LLMs
AI Technology

Buffer of Thoughts (BoT): A Novel Thought-Augmented Reasoning AI Approach for Enhancing Accuracy, Efficiency, and Robustness of LLMs

June 9, 2024
Deciphering Doubt: Navigating Uncertainty in LLM Responses
AI Technology

Deciphering Doubt: Navigating Uncertainty in LLM Responses

June 9, 2024
Next Post
Meet Llemma: The Next-Gen Mathematical Open-Language Model Surpassing Current Benchmarks

Meet Llemma: The Next-Gen Mathematical Open-Language Model Surpassing Current Benchmarks

Red Hat Quarkus Java stack spruces up the dev UI

Red Hat Quarkus Java stack spruces up the dev UI

The Main Reasons To Install Motorised Blinds for Your Kiwi Home

The Main Reasons To Install Motorised Blinds for Your Kiwi Home

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

  • Trending
  • Comments
  • Latest
Is C.AI Down? Here Is What To Do Now

Is C.AI Down? Here Is What To Do Now

January 10, 2024
Porfo: Revolutionizing the Crypto Wallet Landscape

Porfo: Revolutionizing the Crypto Wallet Landscape

October 9, 2023
23 Plagiarism Facts and Statistics to Analyze Latest Trends

23 Plagiarism Facts and Statistics to Analyze Latest Trends

June 4, 2024
A Complete Guide to BERT with Code | by Bradney Smith | May, 2024

A Complete Guide to BERT with Code | by Bradney Smith | May, 2024

May 19, 2024
Part 1: ABAP RESTful Application Programming Model (RAP) – Introduction

Part 1: ABAP RESTful Application Programming Model (RAP) – Introduction

November 20, 2023
Saginaw HMI Enclosures and Suspension Arm Systems from AutomationDirect – Library.Automationdirect.com

Saginaw HMI Enclosures and Suspension Arm Systems from AutomationDirect – Library.Automationdirect.com

December 6, 2023
Can You Guess What Percentage Of Their Wealth The Rich Keep In Cash?

Can You Guess What Percentage Of Their Wealth The Rich Keep In Cash?

June 10, 2024
AI Compared: Which Assistant Is the Best?

AI Compared: Which Assistant Is the Best?

June 10, 2024
How insurance companies can use synthetic data to fight bias

How insurance companies can use synthetic data to fight bias

June 10, 2024
5 SLA metrics you should be monitoring

5 SLA metrics you should be monitoring

June 10, 2024
From Low-Level to High-Level Tasks: Scaling Fine-Tuning with the ANDROIDCONTROL Dataset

From Low-Level to High-Level Tasks: Scaling Fine-Tuning with the ANDROIDCONTROL Dataset

June 10, 2024
UGRO Capital: Targeting to hit milestone of Rs 20,000 cr loan book in 8-10 quarters: Shachindra Nath

UGRO Capital: Targeting to hit milestone of Rs 20,000 cr loan book in 8-10 quarters: Shachindra Nath

June 10, 2024
Facebook Twitter LinkedIn Pinterest RSS
News PouroverAI

The latest news and updates about the AI Technology and Latest Tech Updates around the world... PouroverAI keeps you in the loop.

CATEGORIES

  • AI Technology
  • Automation
  • Blockchain
  • Business
  • Cloud & Programming
  • Data Science & ML
  • Digital Marketing
  • Front-Tech
  • Uncategorized

SITEMAP

  • Disclaimer
  • Privacy Policy
  • DMCA
  • Cookie Privacy Policy
  • Terms and Conditions
  • Contact us

Copyright © 2023 PouroverAI News.
PouroverAI News

No Result
View All Result
  • Home
  • AI Tech
  • Business
  • Blockchain
  • Data Science & ML
  • Cloud & Programming
  • Automation
  • Front-Tech
  • Marketing

Copyright © 2023 PouroverAI News.
PouroverAI News

Welcome Back!

Login to your account below

Forgotten Password? Sign Up

Create New Account!

Fill the forms bellow to register

All fields are required. Log In

Retrieve your password

Please enter your username or email address to reset your password.

Log In