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Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study

BACKGROUND: In the context of monitoring dogs, usually, accelerometers have been used to measure the dog’s movement activity. Here, we study another application of the accelerometers (and gyroscopes)—seismocardiography (SCG) and gyrocardiography (GCG)—to monitor the dog’s heart. Together, 3-axis SCG...

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Autores principales: Lahdenoja, Olli, Hurnanen, Tero, Kaisti, Matti, Koskinen, Juho, Tuominen, Jarno, Vähä-Heikkilä, Matti, Parikka, Laura, Wiberg, Maria, Koivisto, Tero, Pänkäälä, Mikko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6480821/
https://www.ncbi.nlm.nih.gov/pubmed/31014339
http://dx.doi.org/10.1186/s12938-019-0667-9
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author Lahdenoja, Olli
Hurnanen, Tero
Kaisti, Matti
Koskinen, Juho
Tuominen, Jarno
Vähä-Heikkilä, Matti
Parikka, Laura
Wiberg, Maria
Koivisto, Tero
Pänkäälä, Mikko
author_facet Lahdenoja, Olli
Hurnanen, Tero
Kaisti, Matti
Koskinen, Juho
Tuominen, Jarno
Vähä-Heikkilä, Matti
Parikka, Laura
Wiberg, Maria
Koivisto, Tero
Pänkäälä, Mikko
author_sort Lahdenoja, Olli
collection PubMed
description BACKGROUND: In the context of monitoring dogs, usually, accelerometers have been used to measure the dog’s movement activity. Here, we study another application of the accelerometers (and gyroscopes)—seismocardiography (SCG) and gyrocardiography (GCG)—to monitor the dog’s heart. Together, 3-axis SCG and 3-axis GCG constitute of 6-axis mechanocardiography (MCG), which is inbuilt to most modern smartphones. Thus, the objective of this study is to assess the feasibility of using a smartphone-only solution to studying dog’s heart. METHODS: A clinical trial (CT) was conducted at the University Small Animal Hospital, University of Helsinki, Finland. 14 dogs (3 breeds) including 18 measurements (about one half of all) where the dog’s status was such that it was still and not panting were further selected for the heart rate (HR) analysis (each signal with a duration of 1 min). The measurement device in the CT was a custom Holter monitor including synchronized 6-axis MCG and ECG. In addition, 16 dogs (9 breeds, one mixed-breed) were measured at home settings by the dog owners themselves using Sony Xperia Android smartphone sensor to further validate the applicability of the method. RESULTS: The developed algorithm was able to select 10 good-quality signals from the 18 CT measurements, and for 7 of these, the automated algorithm was able to detect HR with deviation below or equal to 5 bpm (compared to ECG). Further visual analysis verified that, for approximately half of the dogs, the signal quality at home environment was sufficient for HR extraction at least in some signal locations, while the motion artifacts due to dog’s movements are the main challenges of the method. CONCLUSION: With improved data analysis techniques for managing noisy measurements, the proposed approach could be useful in home use. The advantage of the method is that it can operate as a stand-alone application without requiring any extra equipment (such as smart collar or ECG patch).
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spelling pubmed-64808212019-05-01 Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study Lahdenoja, Olli Hurnanen, Tero Kaisti, Matti Koskinen, Juho Tuominen, Jarno Vähä-Heikkilä, Matti Parikka, Laura Wiberg, Maria Koivisto, Tero Pänkäälä, Mikko Biomed Eng Online Research BACKGROUND: In the context of monitoring dogs, usually, accelerometers have been used to measure the dog’s movement activity. Here, we study another application of the accelerometers (and gyroscopes)—seismocardiography (SCG) and gyrocardiography (GCG)—to monitor the dog’s heart. Together, 3-axis SCG and 3-axis GCG constitute of 6-axis mechanocardiography (MCG), which is inbuilt to most modern smartphones. Thus, the objective of this study is to assess the feasibility of using a smartphone-only solution to studying dog’s heart. METHODS: A clinical trial (CT) was conducted at the University Small Animal Hospital, University of Helsinki, Finland. 14 dogs (3 breeds) including 18 measurements (about one half of all) where the dog’s status was such that it was still and not panting were further selected for the heart rate (HR) analysis (each signal with a duration of 1 min). The measurement device in the CT was a custom Holter monitor including synchronized 6-axis MCG and ECG. In addition, 16 dogs (9 breeds, one mixed-breed) were measured at home settings by the dog owners themselves using Sony Xperia Android smartphone sensor to further validate the applicability of the method. RESULTS: The developed algorithm was able to select 10 good-quality signals from the 18 CT measurements, and for 7 of these, the automated algorithm was able to detect HR with deviation below or equal to 5 bpm (compared to ECG). Further visual analysis verified that, for approximately half of the dogs, the signal quality at home environment was sufficient for HR extraction at least in some signal locations, while the motion artifacts due to dog’s movements are the main challenges of the method. CONCLUSION: With improved data analysis techniques for managing noisy measurements, the proposed approach could be useful in home use. The advantage of the method is that it can operate as a stand-alone application without requiring any extra equipment (such as smart collar or ECG patch). BioMed Central 2019-04-23 /pmc/articles/PMC6480821/ /pubmed/31014339 http://dx.doi.org/10.1186/s12938-019-0667-9 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Lahdenoja, Olli
Hurnanen, Tero
Kaisti, Matti
Koskinen, Juho
Tuominen, Jarno
Vähä-Heikkilä, Matti
Parikka, Laura
Wiberg, Maria
Koivisto, Tero
Pänkäälä, Mikko
Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study
title Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study
title_full Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study
title_fullStr Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study
title_full_unstemmed Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study
title_short Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study
title_sort cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6480821/
https://www.ncbi.nlm.nih.gov/pubmed/31014339
http://dx.doi.org/10.1186/s12938-019-0667-9
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