A database of physical therapy exercises with variability of execution collected by wearable sensors

This document introduces the PHYTMO database, which contains data from physical therapies recorded with inertial sensors, including information from an optical reference system. PHYTMO includes the recording of 30 volunteers, aged between 20 and 70 years old. A total amount of 6 exercises and 3 gait...

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Published inScientific data Vol. 9; no. 1; pp. 266 - 13
Main Authors García-de-Villa, Sara, Jiménez-Martín, Ana, García-Domínguez, Juan Jesús
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 03.06.2022
Nature Publishing Group
Nature Portfolio
Subjects
692/700/228/491
692/700/784
Adult
Aged
Algorithms
Data Descriptor
Exercise
Gait
Humanities and Social Sciences
Humans
Middle Aged
multidisciplinary
Physical therapy
Physical Therapy Modalities
Science
Science (multidisciplinary)
Sensors
Wearable Electronic Devices
Young Adult
Online AccessGet full text
ISSN2052-4463
2052-4463
DOI10.1038/s41597-022-01387-2

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Abstract This document introduces the PHYTMO database, which contains data from physical therapies recorded with inertial sensors, including information from an optical reference system. PHYTMO includes the recording of 30 volunteers, aged between 20 and 70 years old. A total amount of 6 exercises and 3 gait variations were recorded. The volunteers performed two series with a minimum of 8 repetitions in each one. PHYTMO includes magneto-inertial data, together with a highly accurate location and orientation in the 3D space provided by the optical system. The files were stored in CSV format to ensure its usability. The aim of this dataset is the availability of data for two main purposes: the analysis of techniques for the identification and evaluation of exercises using inertial sensors and the validation of inertial sensor-based algorithms for human motion monitoring. Furthermore, the database stores enough data to apply Machine Learning-based algorithms. The participants’ age range is large enough to establish age-based metrics for the exercises evaluation or the study of differences in motions between different groups. Measurement(s) Turn rate • Specific force • Magnetic field • Locations • Orientations Technology Type(s) Inertial measurement unit • Stereophotogrammetric system Factor Type(s) Time Sample Characteristic - Organism Humans
AbstractList This document introduces the PHYTMO database, which contains data from physical therapies recorded with inertial sensors, including information from an optical reference system. PHYTMO includes the recording of 30 volunteers, aged between 20 and 70 years old. A total amount of 6 exercises and 3 gait variations were recorded. The volunteers performed two series with a minimum of 8 repetitions in each one. PHYTMO includes magneto-inertial data, together with a highly accurate location and orientation in the 3D space provided by the optical system. The files were stored in CSV format to ensure its usability. The aim of this dataset is the availability of data for two main purposes: the analysis of techniques for the identification and evaluation of exercises using inertial sensors and the validation of inertial sensor-based algorithms for human motion monitoring. Furthermore, the database stores enough data to apply Machine Learning-based algorithms. The participants’ age range is large enough to establish age-based metrics for the exercises evaluation or the study of differences in motions between different groups.
This document introduces the PHYTMO database, which contains data from physical therapies recorded with inertial sensors, including information from an optical reference system. PHYTMO includes the recording of 30 volunteers, aged between 20 and 70 years old. A total amount of 6 exercises and 3 gait variations were recorded. The volunteers performed two series with a minimum of 8 repetitions in each one. PHYTMO includes magneto-inertial data, together with a highly accurate location and orientation in the 3D space provided by the optical system. The files were stored in CSV format to ensure its usability. The aim of this dataset is the availability of data for two main purposes: the analysis of techniques for the identification and evaluation of exercises using inertial sensors and the validation of inertial sensor-based algorithms for human motion monitoring. Furthermore, the database stores enough data to apply Machine Learning-based algorithms. The participants’ age range is large enough to establish age-based metrics for the exercises evaluation or the study of differences in motions between different groups. Measurement(s)Turn rate • Specific force • Magnetic field • Locations • OrientationsTechnology Type(s)Inertial measurement unit • Stereophotogrammetric systemFactor Type(s)TimeSample Characteristic - OrganismHumans
This document introduces the PHYTMO database, which contains data from physical therapies recorded with inertial sensors, including information from an optical reference system. PHYTMO includes the recording of 30 volunteers, aged between 20 and 70 years old. A total amount of 6 exercises and 3 gait variations were recorded. The volunteers performed two series with a minimum of 8 repetitions in each one. PHYTMO includes magneto-inertial data, together with a highly accurate location and orientation in the 3D space provided by the optical system. The files were stored in CSV format to ensure its usability. The aim of this dataset is the availability of data for two main purposes: the analysis of techniques for the identification and evaluation of exercises using inertial sensors and the validation of inertial sensor-based algorithms for human motion monitoring. Furthermore, the database stores enough data to apply Machine Learning-based algorithms. The participants’ age range is large enough to establish age-based metrics for the exercises evaluation or the study of differences in motions between different groups.Measurement(s)Turn rate • Specific force • Magnetic field • Locations • OrientationsTechnology Type(s)Inertial measurement unit • Stereophotogrammetric systemFactor Type(s)TimeSample Characteristic - OrganismHumans
Measurement(s) Turn rate • Specific force • Magnetic field • Locations • Orientations Technology Type(s) Inertial measurement unit • Stereophotogrammetric system Factor Type(s) Time Sample Characteristic - Organism Humans
This document introduces the PHYTMO database, which contains data from physical therapies recorded with inertial sensors, including information from an optical reference system. PHYTMO includes the recording of 30 volunteers, aged between 20 and 70 years old. A total amount of 6 exercises and 3 gait variations were recorded. The volunteers performed two series with a minimum of 8 repetitions in each one. PHYTMO includes magneto-inertial data, together with a highly accurate location and orientation in the 3D space provided by the optical system. The files were stored in CSV format to ensure its usability. The aim of this dataset is the availability of data for two main purposes: the analysis of techniques for the identification and evaluation of exercises using inertial sensors and the validation of inertial sensor-based algorithms for human motion monitoring. Furthermore, the database stores enough data to apply Machine Learning-based algorithms. The participants’ age range is large enough to establish age-based metrics for the exercises evaluation or the study of differences in motions between different groups. Measurement(s) Turn rate • Specific force • Magnetic field • Locations • Orientations Technology Type(s) Inertial measurement unit • Stereophotogrammetric system Factor Type(s) Time Sample Characteristic - Organism Humans
This document introduces the PHYTMO database, which contains data from physical therapies recorded with inertial sensors, including information from an optical reference system. PHYTMO includes the recording of 30 volunteers, aged between 20 and 70 years old. A total amount of 6 exercises and 3 gait variations were recorded. The volunteers performed two series with a minimum of 8 repetitions in each one. PHYTMO includes magneto-inertial data, together with a highly accurate location and orientation in the 3D space provided by the optical system. The files were stored in CSV format to ensure its usability. The aim of this dataset is the availability of data for two main purposes: the analysis of techniques for the identification and evaluation of exercises using inertial sensors and the validation of inertial sensor-based algorithms for human motion monitoring. Furthermore, the database stores enough data to apply Machine Learning-based algorithms. The participants' age range is large enough to establish age-based metrics for the exercises evaluation or the study of differences in motions between different groups.This document introduces the PHYTMO database, which contains data from physical therapies recorded with inertial sensors, including information from an optical reference system. PHYTMO includes the recording of 30 volunteers, aged between 20 and 70 years old. A total amount of 6 exercises and 3 gait variations were recorded. The volunteers performed two series with a minimum of 8 repetitions in each one. PHYTMO includes magneto-inertial data, together with a highly accurate location and orientation in the 3D space provided by the optical system. The files were stored in CSV format to ensure its usability. The aim of this dataset is the availability of data for two main purposes: the analysis of techniques for the identification and evaluation of exercises using inertial sensors and the validation of inertial sensor-based algorithms for human motion monitoring. Furthermore, the database stores enough data to apply Machine Learning-based algorithms. The participants' age range is large enough to establish age-based metrics for the exercises evaluation or the study of differences in motions between different groups.
ArticleNumber 266
Author Jiménez-Martín, Ana
García-de-Villa, Sara
García-Domínguez, Juan Jesús
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Snippet This document introduces the PHYTMO database, which contains data from physical therapies recorded with inertial sensors, including information from an optical...
Measurement(s) Turn rate • Specific force • Magnetic field • Locations • Orientations Technology Type(s) Inertial measurement unit • Stereophotogrammetric...
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StartPage 266
SubjectTerms 692/700/228/491
692/700/784
Adult
Aged
Algorithms
Data Descriptor
Exercise
Gait
Humanities and Social Sciences
Humans
Middle Aged
multidisciplinary
Physical therapy
Physical Therapy Modalities
Science
Science (multidisciplinary)
Sensors
Wearable Electronic Devices
Young Adult
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Title A database of physical therapy exercises with variability of execution collected by wearable sensors
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