Lie Detector At the Gait: Artificial Intelligence Model

NCT06057272 | Completed

• 1 other identifier: GO21/749
• Study Type: observational
• Target: 60
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this clinical trial is to obtain more consistent results with the use of repetitive neural networks in gait models and classification approaches in individuals applying forensic sciences. It was aimed to develop a decision support system for determining the walking imitations of individuals with explainable machine learning approaches on disability compensation in the field of Forensic Medicine. Participants will be assessed regarding kinematic and temporospatial gait parameters, pain severity, and fatigue level. Comparison group: Researchers will compare the patients applying to the forensic medicine department to those applying to the orthopedic department, and their healthy counterparts.

Conditions

Gait, Stumbling; Fracture Lower Leg; Imitates Movements

Keywords

gait; kinematic; forensic medicine; artificial intelligence; imitation

Outcome Measures

Primary Outcomes (2)

• Kinematic Gait analysis

  During walking, angular values of the lower and upper limbs and trunk will be measured simultaneously with the measurement of time distance characteristics.

  Day 1

• Temporospatial gait analysis

  Individuals' gait will be assessed using the GAITRite® computerized walking path (CIR System INC. Clifton, NJ 07012). Data from the system, which has 18,432 sensors, is obtained by pressure-activated sensors at a rate of 60-120 Hz. In order to eliminate the learning effect, the subjects will be asked to walk at the pace they choose after three attempts are made. Rest breaks will be given between assessments and the average of three repetitions of the walk will be recorded.

  Day 1

Secondary Outcomes (3)

• Pain assessment

  Day 1

• Fatigue assessment

  Day 1

• Mental State Assessment

  Day 1

Study Arms (3)

Forensic Medicine

Individuals with unilateral lower extremity fractures who apply to the Department of Forensic Medicine for disability rate determination and reporting

Orthopedic

In individuals with unilateral lower extremity fractures who apply to the Department of Orthopedics and Traumatology

Healthy

The healthy counterparts of the patients in the forensic medicine and orthopedic population group.

Eligibility Criteria

• Age: 18 Years - 40 Years
• Gender Eligibility Details: The male participants will be included in the study.
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

The participants will be included via invitation.

You may qualify if:

• Applying to the Department of Forensic Medicine to determine the disability rate,
• Antalgic gait evaluation performed within the scope of traffic accident or disability reporting,
• Having a history of unilateral lower extremity fracture,
• Not having any orthopedic or neurological problems that may affect walking, other than fractures,
• At least 6 months after surgical treatment,
• Scoring 24 or more from the Standardized Mini Mental Test
• Male individuals between the ages of 18-40
• Having a history of unilateral lower extremity fracture,
• Not in a position of disability or compensation after the fracture,
• Treated in the Orthopedics and Traumatology Department
• Similar to the participants in the Group Forensic Medicine in terms of demographic characteristics,
• No orthopedic or neurological problems other than fractures that would affect walking,
• At least 6 months after surgical treatment,
• Scoring 24 or above from the Standardized Mini Mental Test,
• Male individuals between the ages of 18-40

You may not qualify if:

• Having any problems or pain in the upper extremities and/or trunk,
• Having problems in both lower extremities,
• Treatment is ongoing,
• Patients who do not have the ability to walk independently,
• Having a Body Mass Index of 30 kg/m² and above.

Sponsors & Collaborators

• Hacettepe University: lead

Study Sites (1)

Hacettepe University Physical Therapy and Rehabilitation Faculty

Ankara, Samanpazarı, 06100, Turkey (Türkiye)

Location

MeSH Terms

Conditions

Gait Disorders, Neurologic

Condition Hierarchy (Ancestors)

Neurologic Manifestations; Nervous System Diseases; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Officials

• Semra Topuz, Prof

  Hacettepe University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Target Duration: 1 Day
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Clinical Professor

Study Record Dates

• First Submitted: September 14, 2023
• First Posted: September 28, 2023
• Study Start: October 30, 2023
• Primary Completion: June 30, 2024
• Study Completion: December 30, 2024
• Last Updated: March 19, 2025

Record last verified: 2024-07

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)