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

NCT ID: NCT04867148

Last Updated: 2021-04-30

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

2000 participants

Study Classification

INTERVENTIONAL

Study Start Date

2019-09-01

Study Completion Date

2022-12-31

Brief Summary

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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.

Detailed Description

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Conditions

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Ankylosing Spondylitis Adolescent Idiopathic Scoliosis Gait Analysis

Keywords

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Gait analysis Spine

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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Gait analysis

Gait analysis of patients with ankylosing spondylitis, patients with adoldescent idiopathic scoliosis and control group.

Group Type EXPERIMENTAL

Inertial measurement unit sensor-based gait analysis system

Intervention Type DEVICE

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.

Interventions

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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.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Pusan National University Hospital orthopedics, otorhinolaryngology, neurology outpatient or inpatient who agreed to the study.
* For adult men and women 18 years of age or older.

Exclusion Criteria

* Patients unable to walk independently.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Pusan National University Hospital

OTHER

Sponsor Role lead

Responsible Party

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Lee Jung Sub

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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jungsub Lee, M.D., Ph.D.

Role: STUDY_CHAIR

Pusan National University Hospital

Locations

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Pusan National University Hospital

Busan, Seo-gu, South Korea

Site Status

Countries

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South Korea

Other Identifiers

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PNUH orthopaedics

Identifier Type: -

Identifier Source: org_study_id