A database of physical therapy exercises with variability of execution collected by wearable sensors.
Sara García-de-VillaAna Jiménez-MartínJuan Jesús García DomínguezPublished in: Scientific data (2022)
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.
Keyphrases
- machine learning
- electronic health record
- big data
- high resolution
- resistance training
- adverse drug
- deep learning
- artificial intelligence
- physical activity
- high speed
- low cost
- endothelial cells
- mental health
- health information
- emergency department
- data analysis
- high intensity
- social media
- ionic liquid
- induced pluripotent stem cells
- heart rate