Validating Wireless Gait Sensor for Elderly Fall Risk Classification
A Study on Validation of Gait Analysis Wireless Small Inertial Sensor and Diagnostic Machine Learning Model for Classification of Elderly Fall Risk Group
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Hyun Jin Lee
- Phone Number: +82-10-9615-0011
- Email: spring75517@gmail.com
Study Locations
-
-
-
Yangsan, Korea, Republic of
- Sungchul Huh, MD
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- a person over the age of 55
- Persons who can walk independently for at least one minute
- Those who do not take drugs that affect their ability to maintain balance
- A person who does not have an orthopedic problem such as a fracture of the lower extremities within six months
Exclusion Criteria:
- Those who have difficulty understanding the gait analysis program or difficulty expressing symptoms
- A person deemed unfit for this study by a rehabilitation specialist due to other conditions
- A person who is unable to apply this walking analysis program due to serious cardiovascular diseases
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Other
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Experimental: Gait group
|
Participant gait analysis with the inertial sensor
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Falls Risk Assessment Scale
Time Frame: Patient gait data is collected continuously throughout the study period, enabling the ongoing measurement of falls risk.
|
A falls risk assessment scale measured through the analysis of patients' gait using wireless inertial sensors and a diagnostic machine learning model.
|
Patient gait data is collected continuously throughout the study period, enabling the ongoing measurement of falls risk.
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Sungchul Huh, PhD, Pusan National University Yangsan Hospital
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- 11-2023-001
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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