Title :
iTUG, a Sensitive and Reliable Measure of Mobility
Author :
Salarian, Arash ; Horak, Fay B. ; Zampieri, Cris ; Carlson-Kuhta, Patricia ; Nutt, John G. ; Aminian, Kamiar
Author_Institution :
Lab. of Movement Anal. & Meas. (LMAM), Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne, Switzerland
fDate :
6/1/2010 12:00:00 AM
Abstract :
Timed Up and Go (TUG) test is a widely used clinical paradigm to evaluate balance and mobility. Although TUG includes several complex subcomponents, namely: sit-to-stand, gait, 180° turn, and turn-to-sit; the only outcome is the total time to perform the task. We have proposed an instrumented TUG, called iTUG, using portable inertial sensors to improve TUG in several ways: automatic detection and separation of subcomponents, detailed analysis of each one of them and a higher sensitivity than TUG. Twelve subjects in early stages of Parkinson´s disease (PD) and 12 age matched control subjects were enrolled. Stopwatch measurements did not show a significant difference between the two groups. The iTUG, however, showed a significant difference in cadence between early PD and control subjects (111.1 ± 6.2 versus 120.4 ± 7.6 step/min, p <; 0.006) as well as in angular velocity of arm-swing (123 ± 32.0 versus 174.0 ± 50.4°/s, p <; 0.005), turning duration (2.18 ± 0.43 versus 1.79 ± 0.27 s, p <; 0.023), and time to perform turn-to-sits (2.96 ± 0.68 versus 2.40 ± 0.33 s, p <; 0.023). By repeating the tests for a second time, the test-retest reliability of iTUG was also evaluated. Among the subcomponents of iTUG, gait, turning, and turn-to-sit were the most reliable and sit-to-stand was the least reliable.
Keywords :
biomechanics; biomedical equipment; biomedical measurement; diseases; patient diagnosis; 180° turn; Parkinson´s disease; arm-swing velocity; balance; gait; iTUG; instrumented Timed Up and Go test; mobility; portable inertial sensors; sit-to-stand; stopwatch measurements; test-retest reliability; turn-to-sit; turning duration; Balance; gait; mobility; objective assessment; wearable sensors; Biomechanics; Data Interpretation, Statistical; Female; Gait; Humans; Male; Middle Aged; Movement; Parkinson Disease; Postural Balance;
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
DOI :
10.1109/TNSRE.2010.2047606