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CompletedNCT04624594Updated Aug 16, 2021

AI Mobile Application Versus HCP for Bodyweight Squats

An interventional study of Artificial Intelligence Feedback and Physical Therapist Feedback in Squat Form, sponsored by Columbia University. Completed at 1 site in United States. Open to participants aged 20 Years to 35 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2021-08-16.

Sponsored by Columbia University · Not applicable, Interventional, and Other

From the registry’s dates

  • Registered 1 year after the study started (first participant enrolled Oct 2019, registered Nov 2020).
Phase
Not applicable
Study type
Interventional
Enrollment
30
Allocation
Randomized
Ages
20 Years to 35 Years
Sex
All
01

Study summary

To assess if an artificial intelligence (AI) mobile application can identify and improve bodyweight squat form in adult participants when compared to a Physical Therapist (PT).

Read the detailed description

Artificial intelligence (AI) is changing the way people can address their health needs. One such way related to physical exercise is AI-enabled exercise mobile application (digital coach), which uses motion tracking technology to monitor and provide real-time audio feedback on a person's exercise form. However, this AI technology has yet to be independently tested against an in-person evaluator (human coach) for its ability to improve exercise form. This study is a blinded randomized controlled trial comparing the ability of the digital coach (n=15) and a Physical Therapist (PT) human coach (n=15) to improve bodyweight squat form in 30 able-bodied volunteers age 20 - 35. Each volunteer performs 10 unassisted control squats, then 10 squats with assistive vocal feedback from either coach after each repetition, and finally 10 more unassisted test squats, all squats video-recorded. Three independent video evaluators count the number of correct squat repetitions completed by volunteers before and after intervention by the different coaches. This project is important to validate the digital coach compared to a PT human coach in a small population using a bodyweight squat for its wide applicability to daily movement patterns.

02

Conditions studied

  • Squat Form

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Keywords

  • Exercise
  • Squat
  • Physical therapist
  • Artificial Intelligence (AI)
03

In context

Body Weight

1,223 studies on the registry are indexed under Body Weight; 131 are open to participants now.

This study's enrollment of 30 is below the median of 64 across 947 interventional studies indexed under Body Weight.

Browse Body Weight studies →

Lead sponsor

Columbia University is the lead sponsor of 1,103 studies on the registry; 193 are open to participants now.

Of its 172 completed or terminated interventional studies of FDA-regulated products, 142 (83%) have results posted.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
20 Years to 35 Years
Sexes eligible
All
Accepts healthy volunteers
Yes

Inclusion criteria

  • Columbia University affiliate
  • Aged 20 to 35 years
  • Able to perform moderate bodyweight exercise for 10 minutes

Exclusion criteria

Exclusion Criteria:

  • Unable to provide consent
05

Study design

Phase
Not applicable
Primary purpose
Other
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Single (Outcomes assessor)
Enrollment
30 participants (actual)

Study arms

  • Experimental
    Artificial Intelligence (AI) Group

    To determine baseline ability and serve as their own control, participants in both groups performed 10 bodyweight squat "control" repetitions without feedback followed by one minute of rest. Those in the AI group then performed 10 more "practice" repetitions with real-time audiovisual feedback from the app followed by one minute of rest. The AI's design provided one piece of feedback, if necessary, with a vocal statement and on-screen video per repetition (e.g. when a participant performed a squat repetition with their neck flexed downward, AI suggested keeping their head up with on-screen instruction). Participants in both groups then performed 10 "test" repetitions without feedback followed by one minute of rest.

    Other: Artificial Intelligence Feedback

  • Active comparator
    Physical Therapist Group

    To determine baseline ability and serve as their own control, participants in both groups performed 10 bodyweight squat "control" repetitions without feedback followed by one minute of rest. Those in the PT group (n=15) also performed 10 "practice" repetitions with one piece of feedback per repetition, if necessary, from the PT followed by one minute of rest. Participants in both groups then performed 10 "test" repetitions without feedback followed by one minute of rest.

    Other: Physical Therapist Feedback

Interventions

  • OtherArtificial Intelligence Feedback

    AI mobile application provides feedback to participants randomized to artificial intelligence group.

  • OtherPhysical Therapist Feedback

    PT provides feedback to participants randomized to physical therapist group.

06

What researchers measure

Primary outcomes

  1. Number of correct squats

    Post-intervention improvement in squats will be determined by the number of correct squats in the third set as compared to the first set of squats.

    Time frame: Up to 15 minutes or completion of third set of squats

Secondary outcomes

  1. Number of squats that are identified correctly by AI

    AI identification of correct and incorrect squats will be determined by the number of squats that are identified correctly by AI as compared with independent evaluators.

    Time frame: Up to 15 minutes or completion of third set of squats

07

Study locations

1 site
  • Columbia University Medical Center
    New York, New York 10032, United States
08

References and documents

Publications

  • Luna A, Casertano L, Timmerberg J, O'Neil M, Machowsky J, Leu CS, Lin J, Fang Z, Douglas W, Agrawal S. Artificial intelligence application versus physical therapist for squat evaluation: a randomized controlled trial. Sci Rep. 2021 Sep 13;11(1):18109. doi: 10.1038/s41598-021-97343-y. PubMed 34518568 ↗

Individual participant data

Plan to share: No — Individual participant data is not shared with other researchers

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Aug 16, 2021, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT04624594
Lead sponsor
Columbia University
Collaborators
National Medical Fellowships
Responsible party
Sponsor
First posted
Nov 12, 2020
Start date
Oct 15, 2019
Primary completion
Dec 30, 2019
Completion
Dec 30, 2019
Last update
Aug 16, 2021

Study contacts

Sunil K. Agrawal, PhD
principal investigator · Columbia University

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in Aug 2021. You cannot join it, but the record below documents what was studied.

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