ArticleMedical & biological engineering & computing2009
Transient and steady state estimation of human oxygen uptake based on noninvasive portable sensor measurements.
Article in Medical & biological engineering & computing, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Extracting aerobic system dynamics during unsupervised activities of daily living using wearable sensor machine learning models.Journal of applied physiology (Bethesda, Md. : 1985) · 2018Trial
- Prediction of oxygen uptake dynamics by machine learning analysis of wearable sensors during activities of daily living.Scientific reports · 2017Article
- Modelling the dynamics of expiratory airflow to describe chronic obstructive pulmonary disease.Medical & biological engineering & computing · 2014Article
- An equivalent circuit model for onset and offset exercise response.Biomedical engineering online · 2014Article
- Dynamic modelling of heart rate response under different exercise intensity.The open medical informatics journal · 2010Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The main motivation of this study is to establish an ambulatory cardio-respiratory analysis system for the monitoring and evaluation of exercise and regular daily physical activity. We explored the estimation of oxygen uptake by using noninvasive portable sensors. These sensors are easy to use but may suffer from malfunctions under free living environments. A promising solution is to combine sensors with different measuring mechanisms to improve both reliability and accuracy of the estimation results. For this purpose, we selected a wireless heart rate sensor and a tri-axial accelerometer to form a complementary sensor platform. We analyzed the relationship between oxygen uptake measured by gas analysis and data collected from the simple portable sensors using multivariable nonlinear modeling approaches. It was observed that the resulting nonlinear multivariable model could not only achieve a better estimate compared with single input single output models, but also had greater potential to improve reliability.
Indexed as
Identifiers
19798527What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.