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Role of Artificial Intelligence in Predicting Muscle Fatigue Using Virtual Reality Training

NCT05813613 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 90

Last updated 2023-06-09

No results posted yet for this study

Summary

The goal of this observational predicted study is to predict muscle fatigue using a specific AI algorithm in healthy vs post Covid-19 infected individuals. The main question it aims to answer is:

Can Artificial Intelligence be used as a reliable source of predicting localized muscle fatigue in healthy vs post Covid-19 infected individuals?

Participants will be divided into two groups: A healthy group and a post Covid-19 group.

* Each group will undergo a familiarization process before the start of the exercises.
* Then, each group will perform squatting exercises guided by the kynpasis virtual reality apparatus.
* sEMG for the vastus lateralis and rectus femories, chest expansion, and goniometric measurements of the knee will be taken during different reported fatigue levels using the Biopac system.
* Groups will continue squatting while recording their subjective fatigue levels using the Borg scale.
* Data will then be run through machine learning processes to produce an AI algorithm capable of predicting isolated muscle fatigue.

Conditions

Interventions

OTHER

Squatting with the aid of Kynapsis Virtual Training apparatus.

Squatting exercise was performed using a virtual reality (VR) machine (kynapsis) for guidance in both groups. Squats were performed while the hands were kept in front of the bodies and the knees flexed to 90 degrees following a rhythm of two seconds for descent, two second ascent mimicking the movement done on the VR machine.

Sponsors & Collaborators

  • Beirut Arab University

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
49 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-04-15
Primary Completion
2023-06-01
Completion
2023-06-07

Countries

  • Lebanon

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05813613 on ClinicalTrials.gov