Role of Artificial Intelligence in Predicting Muscle Fatigue Using Virtual Reality Training
Condition: Fatigue
MeSH terms: Fatigue
Study type: Observational

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.
    

Detailed description: 
      Participants were divided into two groups, one consisting of healthy individuals and another
      consisting of Covid-19 subjects. Both groups received a familiarization training for the
      exercise to be performed with 15 minutes of rest afterwards, before the start of the data
      collection.

      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.

      Additional variables were considered, including chest expansion, and the range of motion
      using an electric goniometer, all being measured and recorded using the Biopac (BIOPAC
      Systems, Inc., Santa Barbara, CA) that, according to evidence, possess a high-pass frequency
      filter and bipolar electrode system.

      The muscles tested are the 3 heads of the QF muscle RF, VM, and VL. Their areas were cleaned
      using alcohol and shaved to reduce resistance of electrodes. Three disposable sEMG surface
      electrodes were placed, two of them on the muscle belly with 2.5cm distance between them, and
      one control electrode placed on the agonist side, the participant was asked to extend their
      knee and flex it against resistance to locate the lateral and medial vasti. sEMG electrodes
      were placed on the subdivisions of the QF muscle during the exercise. The extracted data is
      then run through an AI algorithm that will analyze and predict muscle fatigue.

      The Borg (C-10) scale was explained to the participants and was present in front of them
      while performing the exercise as an outcome measure to assess the subjective muscle fatigue
      that once reached will end the exercise.
    

Intervention name(s): Squatting with the aid of Kynapsis Virtual Training apparatus.
Intervention type(s): Other
Intervention description(s): 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.
Observational model: Other
Time perspective: Cross-Sectional
Sampling method: Probability Sample
Study population: 
        The study population consisted of two groups.

          -  Non-athletic healthy individuals that did not perform any intense activities for the
             past 3 days and had not contacted Covid-19 previously.

          -  Non-athletic healthy individuals that did not perform any intense activities for the
             past 3 days but have a confirmed positive PCR test done within a 1 year interval.
      
Keywords: Electromyography; Fatigue; Squats; Borg scale; Musculoskeletal disorders