Mobile Data Gathering and Preliminary Analysis for the Functional Reach Test

The functional reach test (FRT) is a clinical tool used to evaluate dynamic balance and fall risk in older adults and those with certain neurological diseases. It provides crucial information for developing rehabilitation programs to improve balance and reduce fall risk. This paper aims to describe...

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Published inSensors (Basel, Switzerland) Vol. 24; no. 4; p. 1301
Main Authors Francisco, Luís, Duarte, João, Albuquerque, Carlos, Albuquerque, Daniel, Pires, Ivan Miguel, Coelho, Paulo Jorge
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 01.02.2024
MDPI
Subjects
Aged
Algorithms
Balance
Data entry
Exercise
Falls
functional reach test
Humans
inertial sensors
Medical personnel
Mobile Applications
Mobile devices
monitoring apps
Nervous System Diseases
Older people
Physical fitness
R&D
Reproducibility of Results
Research & development
Sensors
smart wearables
Smartphone
Smartphones
Wearable computers
Portugal
inertial sensors
smart wearables
monitoring apps
functional reach test
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Summary:The functional reach test (FRT) is a clinical tool used to evaluate dynamic balance and fall risk in older adults and those with certain neurological diseases. It provides crucial information for developing rehabilitation programs to improve balance and reduce fall risk. This paper aims to describe a new tool to gather and analyze the data from inertial sensors to allow automation and increased reliability in the future by removing practitioner bias and facilitating the FRT procedure. A new tool for gathering and analyzing data from inertial sensors has been developed to remove practitioner bias and streamline the FRT procedure. The study involved 54 senior citizens using smartphones with sensors to execute FRT. The methods included using a mobile app to gather data, using sensor-fusion algorithms like the Madgwick algorithm to estimate orientation, and attempting to estimate location by twice integrating accelerometer data. However, accurate position estimation was difficult, highlighting the need for more research and development. The study highlights the benefits and drawbacks of automated balance assessment testing with mobile device sensors, highlighting the potential of technology to enhance conventional health evaluations.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s24041301