Table 2.

Summary of articles included for review

Authors	Participant characteristics	Sensor type	Location of sensor	Gait metrics measures	Sampling frequency	Environment	Gait speed	Gait distance/time	Quality assessment score
Nagai et al., 2014 [13]	N = 11 (3 female, 8 male) Mean age = 72.8 yrs	Wearable device with triaxial accelerometer (WAA-066, ATR Promotions Co., Japan)	Lumbar spine and cervical spine; 2 sensors)	Postural sway Walking capacity Gait cycle	1 occasion	Indoor horizontal walkway	Self-selected	50 m repetitions until tired (maximum 548 m)	0.54
Lee et al., 2017 [22]	N = 15 (11 female, 4 male) Mean age = 58.5 yrs	Smart-shoes (UCLA Wireless Health Institute) with pressure sensors (FSR400, Interlink Electronics, USA)	Insole of shoe (heel, lateral plantar, toe); 5 sensors	Plantar pressure distribution Gait symmetry	1 occasion (preoperative)	Indoor hospital ward	Self-selected	40 m	0.46
Sun et al., 2018 [3, 21]	N = 20 (sex not specified) Mean age = 58 yrs	Wearable device with accelerometers, gyroscopes (Intelligent Device for Energy Expenditure and Activity 3; MiniSun, LLC, Fresno, CA, USA)	Chest, thigh ankles and plantar surface of foot; 7 sensors	Gait cycle Cadence Step length Gait velocity	1 occasion	Indoor, well-lit environment	Self-selected	16 m	0.71
Loske et al., 2018 [23]	N = 20 (sex not specified)	Inertial sensors with accelerometer, gyroscope and magnetometer (RehaGait System, Hasomed GmbH, Magdeburg, Germany)	Lateral shoe, lower and upper legs, pelvis; 7 sensors	Gait cycle Gait symmetry Step length Gait velocity Cadence	3 occasions (preoperatively, 10 weeks postop, 12 months postop)	Indoors (clinic)	Self selected	6 min	0.67