OBJECTIVE: To estimate instantaneous oxygen uptake VO2 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 VO2 data obtained from the COSMED system. RESULTS: In estimating instantaneous VO2, 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 R2 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 R2 of 0.64). In estimating VO2 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 VO2 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 VO2. SIGNIFICANCE: Accurate estimation of VO2 with a low cost, minimally obtrusive wearable patch can enable the monitoring of VO2 and EE in everyday settings and make the many applications of these measurements more accessible to the general public.
OBJECTIVE: To estimate instantaneous oxygen uptake VO2 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 VO2 data obtained from the COSMED system. RESULTS: In estimating instantaneous VO2, 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 R2 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 R2 of 0.64). In estimating VO2 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 VO2 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 VO2. SIGNIFICANCE: Accurate estimation of VO2 with a low cost, minimally obtrusive wearable patch can enable the monitoring of VO2 and EE in everyday settings and make the many applications of these measurements more accessible to the general public.
Authors: Arne De Brabandere; Tim Op De Beéck; Kurt H Schütte; Wannes Meert; Benedicte Vanwanseele; Jesse Davis Journal: PLoS One Date: 2018-06-29 Impact factor: 3.240
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Authors: Laura Guidetti; Marco Meucci; Francesco Bolletta; Gian Pietro Emerenziani; Maria Chiara Gallotta; Carlo Baldari Journal: PLoS One Date: 2018-12-31 Impact factor: 3.240