Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Neural Control of Respiration01:18

Neural Control of Respiration

2.7K
The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...
2.7K
Special considerations while measuring oxygen saturation01:19

Special considerations while measuring oxygen saturation

635
Assessing respiratory rate concurrently with pulse measurement is fundamental to patient care, providing valuable insights into the patient's respiratory function. The normal breathing rate for an adult usually falls within a normal range of 12 to 20 breaths per minute. Abnormal respiratory rates can signal underlying health conditions or the need for immediate intervention.
Ensuring accuracy in vital sign recordings while prioritizing patient comfort and minimizing anxiety is...
635
Pulse Oximetry01:24

Pulse Oximetry

374
Pulse oximetry, or SpO2, is a non-invasive method for continuously monitoring arterial oxygen saturation (SaO2). This procedure involves attaching a probe or sensor to the patient's fingertip, forehead, earlobe, or nose bridge. The sensor works by detecting changes in oxygen saturation levels through light signals generated by the oximeter and reflected by the pulsing blood under the probe.
Purpose
Average SpO2 values are greater than 95%. If the readings fall below 90%, it indicates that...
374
Oxygen Delivering System II: Venturi Mask and Transtracheal Oxygen01:16

Oxygen Delivering System II: Venturi Mask and Transtracheal Oxygen

797
Oxygen therapy is a pivotal aspect of medical care, particularly for patients with respiratory ailments. Two prominent oxygen-delivering systems include the Venturi mask and the transtracheal oxygen catheter.
Venturi Mask
The Venturi mask, named after the Venturi effect, is designed to deliver precise oxygen concentrations. It consists of a large tube with an oxygen inlet that narrows down, causing a pressure drop that pulls air in through adjustable side ports. The mask is a lightweight,...
797
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

88
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
88
Assessment of Respiration01:23

Assessment of Respiration

1.2K
The respiratory system's basic structures and primary functions lay the foundation for nurses' comprehensive respiratory assessments. This assessment includes subjective and objective data to gauge the patient's respiratory health.
Subjective Assessment: Nurses interview the patient to gather information directly during the subjective assessment. It includes questions about the individual's medical history, medications, and symptoms, focusing on past respiratory conditions like...
1.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Estimating intra- and inter-subject oxygen consumption in outdoor human gait using multiple neural network approaches.

PloS one·2024
Same author

Indirect Estimation of Vertical Ground Reaction Force from a Body-Mounted INS/GPS Using Machine Learning.

Sensors (Basel, Switzerland)·2021
Same author

A Comparison of Various Algorithms for Classification of Food Scents Measured with an Ion Mobility Spectrometry.

Sensors (Basel, Switzerland)·2021
Same author

Continuous Analysis of Running Mechanics by Means of an Integrated INS/GPS Device.

Sensors (Basel, Switzerland)·2019

Related Experiment Video

Updated: Aug 8, 2025

A Model to Simulate Clinically Relevant Hypoxia in Humans
09:54

A Model to Simulate Clinically Relevant Hypoxia in Humans

Published on: December 22, 2016

8.9K

Surrogate Modelling for Oxygen Uptake Prediction Using LSTM Neural Network.

Pavel Davidson1, Huy Trinh1, Sakari Vekki2

  • 1Faculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, Finland.

Sensors (Basel, Switzerland)
|February 28, 2023
PubMed
Summary

Estimating oxygen consumption (V˙O2) for consumers is challenging. This study shows that motion data from an INS/GPS device, analyzed with a LSTM neural network, can accurately predict V˙O2 during running and walking.

Keywords:
INS/GPSLSTM neural networkmachine learningoxygen uptakerunning metrics

More Related Videos

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
09:42

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

Published on: September 1, 2023

1.3K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.1K

Related Experiment Videos

Last Updated: Aug 8, 2025

A Model to Simulate Clinically Relevant Hypoxia in Humans
09:54

A Model to Simulate Clinically Relevant Hypoxia in Humans

Published on: December 22, 2016

8.9K
Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
09:42

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

Published on: September 1, 2023

1.3K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.1K

Area of Science:

  • Exercise physiology
  • Biomechanical engineering
  • Wearable sensor technology

Background:

  • Oxygen uptake (V˙O2) is a key metric for exercise assessment, typically measured by costly and cumbersome equipment.
  • Consumer-grade sensors are needed for accessible, continuous V˙O2 monitoring during activities like walking and running.
  • Current indirect estimation methods often rely on linear regression or neural networks, with varying accuracy.

Purpose of the Study:

  • To investigate the contribution of motion data to V˙O2 estimation accuracy during unconstrained locomotion.
  • To evaluate the performance of a Long Short-Term Memory (LSTM) neural network for indirect V˙O2 prediction using motion data.
  • To assess the added value of combining motion and heart rate data for improved V˙O2 estimation.

Main Methods:

  • Utilized an in-house developed Inertial Navigation System combined with Global Positioning System (INS/GPS) device worn on the torso.
  • Collected motion parameters including speed, speed change, cadence, and vertical oscillation during walking and running.
  • Employed a Long Short-Term Memory (LSTM) neural network to predict oxygen consumption (V˙O2) based on sensor data.

Main Results:

  • A LSTM neural network accurately predicted V˙O2 using only motion data (accuracy of 2.49 mL/min/kg, 95% limits of agreement).
  • Motion parameters like speed, speed change, cadence, and vertical oscillation were key predictors.
  • Combining motion data with heart rate data significantly reduced prediction errors by 1.7-1.9 times compared to using either data source alone.

Conclusions:

  • Motion data from wearable INS/GPS devices can reliably estimate V˙O2 during unconstrained walking and running.
  • LSTM neural networks offer a powerful tool for accurate indirect V˙O2 measurement using consumer-grade sensor data.
  • Integrating heart rate data with motion data provides the most accurate V˙O2 estimation, paving the way for advanced consumer fitness tracking.