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Wearable Wireless Sensors for Measuring Calorie Consumption

BACKGROUND: The tracking devices could help measuring the heart rate and energy expenditure and recognizing the user's activity. The calorie measurement is a significant achievement for the fitness tracking and the continuous health monitoring. METHODS: In this paper, a combination of an accele...

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Autores principales: Fotouhi-Ghazvini, Faranak, Abbaspour, Saedeh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038742/
https://www.ncbi.nlm.nih.gov/pubmed/32166074
http://dx.doi.org/10.4103/jmss.JMSS_15_18
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author Fotouhi-Ghazvini, Faranak
Abbaspour, Saedeh
author_facet Fotouhi-Ghazvini, Faranak
Abbaspour, Saedeh
author_sort Fotouhi-Ghazvini, Faranak
collection PubMed
description BACKGROUND: The tracking devices could help measuring the heart rate and energy expenditure and recognizing the user's activity. The calorie measurement is a significant achievement for the fitness tracking and the continuous health monitoring. METHODS: In this paper, a combination of an accelerometer and a photoplethysmography (PPG) sensor is implemented to calculate the calories consumed. These sensors were mounted next to each other and then were placed on the ankle and finger by flat cable. The sensed data are transferred via Bluetooth to a smartphone in a serial and real-time manner. An Android App is designed to display the user's health data. The average amount of consumed energy is obtained from the combination of the accelerometer sensor based on the laws of motion and the PPG sensor based on the heart rate data. RESULTS: The designed system is tested on 10 nonathlete males and 10 nonathlete females randomly. By applying the wavelet, the value of the acceleration signal variance was reduced from 3.2 to 0.8. The correlation between PPG and pulse oximeter was 0.9. Moreover, the correlation of the accelerometer and treadmill was 0.9. The root mean square error (RMSE) and the P value of the calorie output from PPG and pulse oximeter are 0.53 and 0.008, respectively. The RMSE and the P value of the calories output from the accelerometer and the treadmill are 0.42 and 0.007, respectively. CONCLUSION: Our device validity and reliability were good by comparing it with a typical smart band, smart watch, and smartphone available in the market. The combined PPG and the accelerometer sensors were compared with the gold standard, the pulse oximeter, and the treadmill. According to the results, there is no significant difference in the values obtained. Therefore, a mobile system is augmented with the wireless accelerometer and PPG that are connected to a smartphone. The system could be carried out with the user at any time and any place.
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spelling pubmed-70387422020-03-12 Wearable Wireless Sensors for Measuring Calorie Consumption Fotouhi-Ghazvini, Faranak Abbaspour, Saedeh J Med Signals Sens Original Article BACKGROUND: The tracking devices could help measuring the heart rate and energy expenditure and recognizing the user's activity. The calorie measurement is a significant achievement for the fitness tracking and the continuous health monitoring. METHODS: In this paper, a combination of an accelerometer and a photoplethysmography (PPG) sensor is implemented to calculate the calories consumed. These sensors were mounted next to each other and then were placed on the ankle and finger by flat cable. The sensed data are transferred via Bluetooth to a smartphone in a serial and real-time manner. An Android App is designed to display the user's health data. The average amount of consumed energy is obtained from the combination of the accelerometer sensor based on the laws of motion and the PPG sensor based on the heart rate data. RESULTS: The designed system is tested on 10 nonathlete males and 10 nonathlete females randomly. By applying the wavelet, the value of the acceleration signal variance was reduced from 3.2 to 0.8. The correlation between PPG and pulse oximeter was 0.9. Moreover, the correlation of the accelerometer and treadmill was 0.9. The root mean square error (RMSE) and the P value of the calorie output from PPG and pulse oximeter are 0.53 and 0.008, respectively. The RMSE and the P value of the calories output from the accelerometer and the treadmill are 0.42 and 0.007, respectively. CONCLUSION: Our device validity and reliability were good by comparing it with a typical smart band, smart watch, and smartphone available in the market. The combined PPG and the accelerometer sensors were compared with the gold standard, the pulse oximeter, and the treadmill. According to the results, there is no significant difference in the values obtained. Therefore, a mobile system is augmented with the wireless accelerometer and PPG that are connected to a smartphone. The system could be carried out with the user at any time and any place. Wolters Kluwer - Medknow 2020-02-06 /pmc/articles/PMC7038742/ /pubmed/32166074 http://dx.doi.org/10.4103/jmss.JMSS_15_18 Text en Copyright: © 2020 Journal of Medical Signals & Sensors http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Fotouhi-Ghazvini, Faranak
Abbaspour, Saedeh
Wearable Wireless Sensors for Measuring Calorie Consumption
title Wearable Wireless Sensors for Measuring Calorie Consumption
title_full Wearable Wireless Sensors for Measuring Calorie Consumption
title_fullStr Wearable Wireless Sensors for Measuring Calorie Consumption
title_full_unstemmed Wearable Wireless Sensors for Measuring Calorie Consumption
title_short Wearable Wireless Sensors for Measuring Calorie Consumption
title_sort wearable wireless sensors for measuring calorie consumption
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038742/
https://www.ncbi.nlm.nih.gov/pubmed/32166074
http://dx.doi.org/10.4103/jmss.JMSS_15_18
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