TABLE IV.

Summary of instrumenting the TUG test with wearable sensors in chronological order. M = male, D = dimensional.

Article	Population and Sample Size	Description of TUG Technology	Study Findings
Narayanan et al. (2007) [67]	N/A	1 3D accelerometer mounted at the waist.	At home, self-administered TUG. Data automatically uploaded and accessible via a web interface.
Higashi et al. (2008) [45]	10 healthy. 20 hemiplegic.	1 IMU at L2 vertebra and 1 IMU on 1 upper thigh. A video camera records the tests.	Using acceleration signal metrics, hemiplegic subjects with different gait levels could be differentiated.
Gillain et al. (2009) [73]	14 healthy (mean age 73.53 years years). 14 MCI (mean age 72.85 years). 6 Alzheimer’s (mean age 73.66 years).	1 3D accelerometer at L3 vertebra.	Several gait parameters in the single and dual task TUG tests were different amongst the 3 population groups.
Marschollek et al. (2009) [111], [112]	110 geriatric (29M).	1 3D accelerometer located at the trunk.	Able to classify fallers and non-fallers by utilizing gait parameters extracted from the acceleration signals.
Greene et al. (2010) [70]	142 non-fallers and 207 fallers. (103M, 72.4 ± 7.4 years)	1 IMU mounted on the front of each shank at the midpoint level. A video camera records the tests.	Large set of TUG component and gait parameters. Retrospectively estimated falls risk with 76.8% accuracy.
King et al. (2010) [78]	12 healthy (24-35 years). 16 fallers (9M, 79.2 ± 9.24 years)	1 3D accelerometer (e-AR) worn on the ear.	Metrics computed could differentiate between fallers and non-fallers.
Salarian et al. (2010) [41]	12 early-to-moderate stage PD (7M, 60.4 ± 8.5 years). 12 age- matched healthy (3M, 60.2 ± 8.2 years).	7 inertial sensors attached on the forearms (2D gyroscope), shanks (1D gyroscope), thighs (1D gyroscope) and sternum (3D accelerometer and 2D gyroscope). Small data-logger in a waist-worn pack.	Each TUG component is automatically detected. Gait, turns, and turn-to sit sections of the iTUG demonstrated significant differences between the 2 populations.
Weiss et al. (2010) [18]	17 PD (15M, 66.8 ± 5.9 years). 15 age- matched healthy (5M, 67.6 ± 9.6 years).	1 3D accelerometer worn on the lower back between the L3 and L5 vertebrae.	Analysis of sit-to-stand and stand-to-sit movements with parameters such as range, jerk, duration, and median standard deviation.
Chiari (2011) [113]	20 early-to-mid PD. 20 healthy.	1 accelerometer mounted at the L5 vertebra.	92.5% classification accuracy for discriminating the PD and the non-PD populations.
Jallon et al. (2011) [114]	19 subjects.	1 3D accelerometer and magnetometer on the chest.	Graph-based Bayesian classifier distinguished TUG phases with near 85% accuracy.
Al-jawad and colleagues (2012) [115], [116]	10 healthy (4M, 63.2 ± 10.1 years). 10 early stage PD (8M, 58.8 ± 9.5 years). 10 advanced stage PD (7M, 66.2 ± 4.8 years).	1 IMU placed on the lower back.	Able to detect different TUG subtasks with small mean absolute errors.
Cuesta-Vargas et al. (2013) [108]	10 healthy (5M, 22 ± 3.1 years).	7 EMG sensors on the right side of the body.	Different maximum voluntary isometric contractions on land versus water TUG.
Mariani et al. (2013) [14]	10 mild-to-moderate PD (64 ± 7 years). 10 age-matched healthy (66 ± 7 years).	1 3D IMU mounted to the upper shoe.	Parameters computed are able to distinguish between the control subjects and the PD subjects.
Najafi et al. (2013) [76]	8 peripheral neuropathy (2M, 77 ± 7 years).	1 accelerometer integrated into a shirt at the chest level.	Falls risk group took significantly longer to perform stand-to-sit task. A 0.40 second (0.85%) systematic error for TUG duration was achieved.
Strohrmann et al. (2013) [77]	3 children with cerebral palsy or stroke.	10 IMUs attached to the waist, torso, and limbs.	Computed gait parameters are predictors of a motor assessment score.
Tmaura et al. (2013)[117]	40 elderly (age ≥ 65 years).	3D accelerometer and 3 1D gyroscopes were attached near L2 vertebra and to both thighs.	The high falls risk subjects took significantly longer (15.77 ± 1.41 seconds) compared to the lower falls risk subjects (10.09 ± 1.86 seconds).
Caldara et al. (2014) [75]	13 PD (64.6 ± 9 years). 4 healthy (64.3 ± 4 years).	3D accelerometers, gyroscopes, and magnetometers were placed on the spine, each forearm, and each lower leg.	Several features were computed.
SankarPandi et al. (2014) [72]	321 elderly (122M, mean age 88 years).	1 accelerometer mounted on the right wrist.	Forty features were used to classify disability levels with a mean accuracy of 62.16%.