Estimation of Instantaneous Oxygen Uptake During Exercise and Daily Activities Using a Wearable Cardio-Electromechanical and Environmental Sensor

Overview

Journal IEEE J Biomed Health Inform

Specialties Biomedical Engineering
Medical Informatics

Date 2020 Aug 6

PMID 32750964

Citations 8

Authors

Md Mobashir Hasan Shandhi

William H Bartlett

James Alex Heller

Mozziyar Etemadi

Aaron Young

Thomas Plotz

Omer T Inan

Affiliations

Soon will be listed here.

Abstract

Objective: To estimate instantaneous oxygen uptake VO with a small, low-cost wearable sensor during exercise and daily activities in order to enable monitoring of energy expenditure (EE) in uncontrolled settings. We aim to do so using a combination of seismocardiogram (SCG), electrocardiogram (ECG) and atmospheric pressure (AP) signals obtained from a minimally obtrusive wearable device.

Methods: In this study, subjects performed a treadmill protocol in a controlled environment and an outside walking protocol in an uncontrolled environment. During testing, the COSMED K5 metabolic system collected gold standard breath-by-breath (BxB) data and a custom-built wearable patch placed on the mid-sternum collected SCG, ECG and AP signals. We extracted features from these signals to estimate the BxB VO data obtained from the COSMED system.

Results: In estimating instantaneous VO, we achieved our best results on the treadmill protocol using a combination of SCG (frequency) and AP features (RMSE of 3.68 ± 0.98 ml/kg/min and R of 0.77). For the outside protocol, we achieved our best results using a combination of SCG (frequency), ECG and AP features (RMSE of 4.3 ± 1.47 ml/kg/min and R of 0.64). In estimating VO consumed over one minute intervals during the protocols, our median percentage error was 15.8[Formula: see text] for the treadmill protocol and 20.5[Formula: see text] for the outside protocol.

Conclusion: SCG, ECG and AP signals from a small wearable patch can enable accurate estimation of instantaneous VO in both controlled and uncontrolled settings. SCG signals capturing variation in cardio-mechanical processes, AP signals, and state of the art machine learning models contribute significantly to the accurate estimation of instantaneous VO.

Significance: Accurate estimation of VO with a low cost, minimally obtrusive wearable patch can enable the monitoring of VO and EE in everyday settings and make the many applications of these measurements more accessible to the general public.

Citing Articles

Use of Wearable Devices for Peak Oxygen Consumption Measurement in Clinical Cardiology: Case Report and Literature Review.

Bayshtok G, Tiosano S, Furer A Interact J Med Res. 2023; 12:e45504.

PMID: 37581915 PMC: 10466150. DOI: 10.2196/45504.

Wrist ballistocardiography and invasively recorded blood pressure in healthy volunteers during reclining bike exercise.

Steffensen T, Schjerven F, Flade H, Kirkeby-Garstad I, Ingestrom E, Solberg F Front Physiol. 2023; 14:1189732.

PMID: 37250120 PMC: 10213206. DOI: 10.3389/fphys.2023.1189732.

Towards Wearable Estimation of Tidal Volume via Electrocardiogram and Seismocardiogram Signals.

Soliman M, Ganti V, Inan O IEEE Sens J. 2023; 22(18):18093-18103.

PMID: 37091042 PMC: 10120872. DOI: 10.1109/jsen.2022.3196601.

Heart Rate Variability Based Estimation of Maximal Oxygen Uptake in Athletes Using Supervised Regression Models.

Balakarthikeyan V, Jais R, Vijayarangan S, Sreelatha Premkumar P, Sivaprakasam M Sensors (Basel). 2023; 23(6).

PMID: 36991963 PMC: 10054075. DOI: 10.3390/s23063251.

Enhancing instantaneous oxygen uptake estimation by non-linear model using cardio-pulmonary physiological and motion signals.

Wang Z, Zhang Q, Lan K, Yang Z, Gao X, Wu A Front Physiol. 2022; 13:897412.

PMID: 36105296 PMC: 9465676. DOI: 10.3389/fphys.2022.897412.

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