NCT04867148

The Prediction and Prevention of Disease by Using Big Data in Motion Analysis

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 2,000 (actual)
• Sponsor: Pusan National University Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

Variable patterns of gait disturbance can be found in patients with spine disease including the problems of gait initiation, freezing of gait, reduced balance and postural control, reduced step lengths, increased step times, and slow walking speed.

Conditions

• Ankylosing Spondylitis
• Adolescent Idiopathic Scoliosis
• Gait Analysis

Interventions

Type	Name	Description
DEVICE	Inertial measurement unit sensor-based gait analysis system	Gait analysis was performed on 20-m long corridor to collect gait data on more than 23 strides. The gait protocol was performed with an IMU sensor-based gait analysis system (DynaStab™, JEIOS, South Korea) consisting of a shoe-type data logger (Smart Balance1 SB-1, JEIOS, South Korea) and a data acquisition system (DynaStab-Spotfire1, Tibco Spotfire 7.10). The shoe-type data logger included an IMU sensor (IMU-3000™, InvenSense, USA) that measured tri-axial acceleration (up to ± 6 g) and tri-axial angular 136 velocity (up to ± 500˚ s-1) along three orthogonal axes.12,16 The IMU sensors were installed in both shoe outsoles, and the data were transmitted wirelessly to a data acquisition system via Bluetooth®. Shoe sizes were adapted to each participant, with available sizes ranging from 225 mm to 280 mm. The local coordinate system for the IMU sensors included the 140 anteroposterior, mediolateral, and vertical directions.

Timeline

• Start date: 2019-09-01
• Primary completion: 2020-02-20
• Completion: 2022-12-31
• First posted: 2021-04-30
• Last updated: 2021-04-30

Locations

1 site across 1 country: South Korea