Squat FormNCT04624594
AI Mobile Application Versus HCP for Bodyweight Squats
A study testing Artificial Intelligence Feedback and Physical Therapist Feedback in people with Squat Form, run by Columbia University at 1 site in United States.
Trial 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 more about this study
- Who is it for?
- Ages 20 to 35 yearsHealthy volunteers can take part
- Conditions the study is for
- Squat Form
- What is being tested?
- Artificial Intelligence Feedback and Physical Therapist Feedback
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 30 participants
- Where
- 1 siteUnited States
- Study dates
- 15 Oct 2019to 30 Dec 2019
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 to 35 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- Columbia University affiliate
- Aged 20 to 35 years
- Able to perform moderate bodyweight exercise for 10 minutes
Who cannot join
- Unable to provide consent
Trial locations and contacts
1 site in 1 country.
United States1 site
Columbia University Medical Center
New York, New York, 10032
About this study
Official title: Artificial Intelligence (AI) Mobile Application Versus Health Care Provider (HCP) for Bodyweight Squats: A Randomized, Blinded, Controlled Clinical Trial
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.
- Conditions
- Squat Form
- Being tested
- Artificial Intelligence Feedback, Physical Therapist Feedback
- Keywords
- Exercise, Squat, Physical therapist, Artificial Intelligence (AI)
- Medical subject headings
- Motor Activity
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence FeedbackOther
AI mobile application provides feedback to participants randomized to artificial intelligence group.
Physical Therapist FeedbackOther
PT provides feedback to participants randomized to physical therapist group.
| Study group | Role | What they receive |
|---|---|---|
| Artificial Intelligence (AI) Group | Experimental | 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. Receives: Other: Artificial Intelligence Feedback |
| Physical Therapist Group | Active comparator | 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. Receives: Other: Physical Therapist Feedback |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: Up to 15 minutes or completion of third set of squats
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Nov 2020
- Study start15 Oct 2019
- Primary completion30 Dec 2019
- Study completion30 Dec 2019
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Squat FormStudies of the same condition, open and under way.
- More trials run by Columbia UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 30 participants (actual)
Sponsor and investigators
- Lead sponsor
- Columbia University
- Sponsor type
- University, hospital or other
- Collaborators
- National Medical Fellowships
- Responsible party
- Sponsor
- Investigators
- Sunil K. Agrawal, PhD, Principal investigator, Columbia University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04624594
- Sponsor's protocol ID
- AAAS7301
- Status last verified
- Aug 2021
- First submitted
- 5 Nov 2020
- Last updated
- 16 Aug 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data is not shared with other researchers
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
Study at a glance
From the registry record, last updated by the sponsor on 16 Aug 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence (AI) Mobile Application Versus Health Care Provider (HCP) for Bodyweight Squats: A Randomized, Blinded, Controlled Clinical Trial
- ClinicalTrials.gov ID
- NCT04624594
- Acronym / sponsor ID
- AAAS7301
- Conditions
- Squat Form
- Keywords
- Exercise, Squat, Physical therapist, Artificial Intelligence (AI)
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 30 participants (actual)
- Lead sponsor
- Columbia UniversityUniversity, hospital or other
- Collaborators
- National Medical Fellowships
- Study start
- 15 Oct 2019 (actual)
- Primary completion
- 30 Dec 2019 (actual)
- Study completion
- 30 Dec 2019 (actual)
- First posted
- 12 Nov 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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).
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.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Artificial Intelligence (AI) Group | Experimental | Other: Artificial Intelligence FeedbackTo 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. |
| Physical Therapist Group | Active comparator | Other: Physical Therapist FeedbackTo 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. |
Who may qualify
- Ages
- 20 to 35 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (3 listed)
- Columbia University affiliate
- Aged 20 to 35 years
- Able to perform moderate bodyweight exercise for 10 minutes
Key exclusion criteria (1 listed)
- Unable to provide consent
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence FeedbackAI mobile application provides feedback to participants randomized to artificial intelligence group. | Other | Artificial Intelligence (AI) Group |
| Physical Therapist FeedbackPT provides feedback to participants randomized to physical therapist group. | Other | Physical Therapist Group |
Primary outcome
Number of correct squats
Time frame: Up to 15 minutes or completion of third set of 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.
1 secondary outcome
Number of squats that are identified correctly by AI
Time frame: Up to 15 minutes or completion of third set of squats
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 16 Aug 2021.
- Derived from this study: PubMed 34518568Luna 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.
- Individual participant dataSharing planned: No. Individual participant data is not shared with other researchers
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Sunil K. Agrawal, PhD principal investigator
Columbia University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial Intelligence Feedback and Physical Therapist Feedback in people with Squat Form, run by Columbia University at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 16 Aug 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of correct squats (time frame: Up to 15 minutes or completion of third set of squats). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04624594, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 16 Aug 2021.