The Timed Up and Go (TUG) test is a widely used clinical assessment for mobility, balance, and fall risk. Traditional TUG tests rely on manual timing, which can introduce unwanted subjectivity and variability. Smartphones, with their embedded inertial sensors, offer a promising alternative for automated, objective, and remote TUG assessment. This paper presents a novel algorithm for computing TUG test duration from inertial data collected using smartphones, which makes use of the acceleration and the orientation signals produced by smartphones. The algorithm was assessed using data from a study involving 33 participants. Our results demonstrate high agreement between the computed TUG times and those measured by a reference device (maximum absolute LoA=2.9s). This has relevance for conditions such as Parkinson’s disease, frailty, and cardiac patient monitoring.

Reliable and repeatable smartphone based Timed Up and Go Test using inertial sensors

Palumbo F.
2025

Abstract

The Timed Up and Go (TUG) test is a widely used clinical assessment for mobility, balance, and fall risk. Traditional TUG tests rely on manual timing, which can introduce unwanted subjectivity and variability. Smartphones, with their embedded inertial sensors, offer a promising alternative for automated, objective, and remote TUG assessment. This paper presents a novel algorithm for computing TUG test duration from inertial data collected using smartphones, which makes use of the acceleration and the orientation signals produced by smartphones. The algorithm was assessed using data from a study involving 33 participants. Our results demonstrate high agreement between the computed TUG times and those measured by a reference device (maximum absolute LoA=2.9s). This has relevance for conditions such as Parkinson’s disease, frailty, and cardiac patient monitoring.
2025
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
979-8-3315-1522-5
Inertial measurement unit; Disease patients; Test duration; Timed Up And Go; Inertial data; Minimal differences; End time; Magnetometer; Community centers; Physical tests; Limits of agreement; End of the test; Physical capacity; Gyroscope; Combination of algorithms; Output of algorithm; Manual measurements; Start of the test; Acceleration data; Acceleration signal; Naive algorithm
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/563061
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