Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults

article

Ponciano, Vasco
Pires, Ivan Miguel
Ribeiro, Fernando Reinaldo
Villasana, María Vanessa
Crisóstomo, Rute
Canavarro Teixeira, Maria
Zdravevski, Eftim

MDPI

PONCIANO, Vasco [et al.] (2020) - Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults. Sensors. ISSN 1424-8220. Vol. 20, nº 12, p. 3481. DOI https://www.mdpi.com/1424-8220/20/12/3481

1424-8220

10.3390/s20123481

Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults

Timed-up and go test
Sensors
Mobile devices
Accelerometer
Magnetometer
Pressure sensor
Feature detection
Diseases
Older adults

UIDB/EEA/50008/2020

2020-07-07T09:25:20Z
2020-07-07T09:25:20Z
2020

Due to the increasing age of the European population, there is a growing interest in performing research that will aid in the timely and unobtrusive detection of emerging diseases. For such tasks, mobile devices have several sensors, facilitating the acquisition of diverse data. This study focuses on the analysis of the data collected from the mobile devices sensors and a pressure sensor connected to a Bitalino device for the measurement of the Timed-Up and Go test. The data acquisition was performed within different environments from multiple individuals with distinct types of diseases. Then this data was analyzed to estimate the various parameters of the Timed-Up and Go test. Firstly, the pressure sensor is used to extract the reaction and total test time. Secondly, the magnetometer sensors are used to identify the total test time and different parameters related to turning around. Finally, the accelerometer sensor is used to extract the reaction time, total test time, duration of turning around, going time, return time, and many other derived metrics. Our experiments showed that these parameters could be automatically and reliably detected with a mobile device. Moreover, we identified that the time to perform the Timed-Up and Go test increases with age and the presence of diseases related to locomotion.
info:eu-repo/semantics/publishedVersion

openAccess
http://creativecommons.org/licenses/by/4.0/

eng