Osteoarthritis, KneeNCT07580222
Mobile Technology to Measure Knee Health in Osteoarthritis
An observational study of Osteoarthritis, Knee, run by VA Office of Research and Development at 1 site in United States.
Trial summary
Veterans face a high prevalence of knee osteoarthritis (OA), but current diagnostic methods often miss early stages when interventions are more effective. This project will evaluate smartphone-based motion capture via OpenCap to measure joint mechanics in knee OA patients during functional activities, comparing its… Read more about this study
- Who is it for?
- Ages 30 years and older
- Conditions the study is for
- Osteoarthritis, Knee
- How many people
- 47 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Apr 2026to 31 Mar 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 30 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Individuals who were diagnosed with early knee osteoarthritis and had a history of being elected to receive injection treatment
Who may be able to join
- Veteran and non-Veterans
- males and females
- diagnosed with early knee osteoarthritis
- qualified for and participated in the Precision Assessment of Platelet Rich Plasma for Joint Preservation study (ClinicalTrials.gov ID: NCT03460236)
- able and willing to provide informed consent for follow-up study
Who cannot join
- symptomatic OA in joints other than the knee in the lower body
- joint replacement
- rheumatic disease
- BMI > 35 kg/m^2
- severe systematic disease defined as American Society of Anesthesiologists (ASA) 3 or above
- pregnant or intending to become pregnant during the study
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
VA Palo Alto Health Care System, Palo Alto, CA
Palo Alto, California, 94304-1207
Jade He, PhD, 650-493-5000 ext. 64431, Jade.He@va.gov
Jade He, PhD
About this study
Official title: Using Mobile Technology to Extract Mechanical Markers of Joint Health and Function in Early Knee Osteoarthritis
Veterans face a high prevalence of knee osteoarthritis (OA), but current diagnostic methods often miss early stages when interventions are more effective. This project will evaluate smartphone-based motion capture via OpenCap to measure joint mechanics in knee OA patients during functional activities, comparing its performance to a conventional motion capture system, patient-reported symptoms, and knee joint structure. The findings will have the potential to enable clinicians to trial OpenCap in its current form, provide insights into tracking joint health, and guide refinements to advance toward earlier diagnosis of knee OA by complementing symptom assessments with measures of joint mechanics.
Read the detailed description
Significance to VA: Veterans, particularly the younger age group, have a higher prevalence of osteoarthritis (OA) than the general population. Among Veterans, OA most commonly affects the knee, a joint with a high injury rate in the US Military. Current diagnostic criteria for knee OA, which often rely on radiographic evidence, do not consistently identify younger patients or those in the early stages of OA, when interventions may be most effective. At the onset of OA symptoms, there is a critical window to quantify mechanical markers that could predict disease progression and provide insights beyond pain. While mechanical markers are predictive and capable of tracking OA progression, their clinical utility has been limited by conventional marker-based motion capture (Mocap), which requires specialized equipment, trained experts, and dedicated resources, making it inaccessible in many clinical settings.
Innovation and Impact: A novel mobile technology, OpenCap, uses smartphone video-based motion capture to estimate movement mechanics, offering a low-cost and highly accessible alternative to traditional Mocap. OpenCap requires at a minimum of two smartphones and applies machine learning and musculoskeletal modeling to quantify mechanical markers. This technology has the potential to overcome significant barriers to implementing mechanical markers in clinical care. However, OpenCap has not yet been evaluated in knee OA patients, and its validity for quantifying mechanical markers during activities relevant to knee OA management remains underexplored.
Therefore, this mentored career development award application has an objective to evaluate the utility of mobile technology OpenCap in quantifying mechanical markers that may provide insights into joint health in patients with early knee OA and to extract these markers from functional activities commonly used in knee OA management.
Specific Aims: Aim 1 will evaluate the current potential use of the mobile technology OpenCap in patients with knee OA by testing the hypotheses that (1a) mechanical markers estimated by the mobile technology significantly differ but are associated with those measured using conventional Mocap and (1b) the mobile technology detects within-person, within-visit mechanical differences introduced by functional activity variations. Aim 2 will explore the broader use of the mobile technology OpenCap in patients with knee OA by (2a) associating mechanical markers estimated by the mobile technology with patient-reported outcomes (PROs), performance-based measures, and structural metrics and (2b) determining the test-retest reliability of the mechanical markers.
Anticipated Research Outcomes: The project findings will have the potential to enable clinicians to trial the technology in its current form, leveraging its potential to quantify and document movement mechanics in patients at risk of or with knee OA. At the same time, the project's results will explore more advanced applications, such as tracking functional changes over time during OA treatment and contributing critical data to refine and further develop the technology. On the other hand, recalling an existing research cohort offers an invaluable opportunity for longitudinal follow-up.
Anticipated Training Outcomes: This award will provide the applicant with training in musculoskeletal modeling, data science, and clinical and translational science, enabling the applicant to validate and refine mobile motion capture technologies. This training will prepare the applicant to integrate mobile technologies into clinical practice and support applicant's advancement to independence through next-level CDA award.
Path to Translation/Implementation: This study will provide clinicians with practical insights on using OpenCap in its current form to quantify and document joint health. Findings will inform future refinements and support subsequent efforts to evaluate the feasibility of video-based motion capture via OpenCap in OA care. This project aligns with VA priorities by improving early diagnosis and management of knee OA to enhance care for Veterans.
- Conditions
- Osteoarthritis, Knee
- Medical subject headings
- Osteoarthritis, Knee
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Knee OA | Adults who were previously diagnosed with early knee osteoarthritis, enrolled in Precision Assessment of Platelet Rich Plasma for Joint Preservation study (NCT03460236), and able and willing to participate in the follow-up assessment. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Knee flexion angle
Knee flexion angle extracted from functional activities (e.g., walking, chair-to-stand)
Measured: Baseline and Week 1
Secondary outcomes (1)
Knee flexion moment
Knee flexion moment estimated from functional activities (e.g., walking, chair-to-stand)
Measured: Baseline and Week 1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 May 2026
- Study start1 Apr 2026
- Primary completion30 Sep 2027 (estimated)
- Study completion31 Mar 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Osteoarthritis, KneeStudies of the same condition, open and under way.
- More trials run by VA Office of Research and DevelopmentThe 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 47 participants (estimated)
Sponsor and investigators
- Lead sponsor
- VA Office of Research and Development
- Sponsor type
- US federal agency
- Responsible party
- Sponsor
- Investigators
- Jade He, PhD, Principal investigator, VA Palo Alto Health Care System, Palo Alto, CA
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07580222
- Sponsor's protocol ID
- RRD8-005-24W
- Other IDs
- 66791, IK1RD000707
- Status last verified
- May 2026
- First submitted
- 8 Apr 2026
- Last updated
- 12 May 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 12 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using Mobile Technology to Extract Mechanical Markers of Joint Health and Function in Early Knee Osteoarthritis
- ClinicalTrials.gov ID
- NCT07580222
- Acronym / sponsor ID
- RRD8-005-24W
- Conditions
- Osteoarthritis, Knee
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 47 participants (estimated)
- Lead sponsor
- VA Office of Research and DevelopmentUS federal agency
- Study start
- 1 Apr 2026 (actual)
- Primary completion
- 30 Sep 2027 (estimated)
- Study completion
- 31 Mar 2028 (estimated)
- First posted
- 12 May 2026 (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.
Veterans face a high prevalence of knee osteoarthritis (OA), but current diagnostic methods often miss early stages when interventions are more effective. This project will evaluate smartphone-based motion capture via OpenCap to measure joint mechanics in knee OA patients during functional activities, comparing its performance to a conventional motion capture system, patient-reported symptoms, and knee joint structure. The findings will have the potential to enable clinicians to trial OpenCap in its current form, provide insights into tracking joint health, and guide refinements to advance toward earlier diagnosis of knee OA by complementing symptom assessments with measures of joint mechanics.
Detailed description
Significance to VA: Veterans, particularly the younger age group, have a higher prevalence of osteoarthritis (OA) than the general population. Among Veterans, OA most commonly affects the knee, a joint with a high injury rate in the US Military. Current diagnostic criteria for knee OA, which often rely on radiographic evidence, do not consistently identify younger patients or those in the early stages of OA, when interventions may be most effective. At the onset of OA symptoms, there is a critical window to quantify mechanical markers that could predict disease progression and provide insights beyond pain. While mechanical markers are predictive and capable of tracking OA progression, their clinical utility has been limited by conventional marker-based motion capture (Mocap), which requires specialized equipment, trained experts, and dedicated resources, making it inaccessible in many clinical settings.
Innovation and Impact: A novel mobile technology, OpenCap, uses smartphone video-based motion capture to estimate movement mechanics, offering a low-cost and highly accessible alternative to traditional Mocap. OpenCap requires at a minimum of two smartphones and applies machine learning and musculoskeletal modeling to quantify mechanical markers. This technology has the potential to overcome significant barriers to implementing mechanical markers in clinical care. However, OpenCap has not yet been evaluated in knee OA patients, and its validity for quantifying mechanical markers during activities relevant to knee OA management remains underexplored.
Therefore, this mentored career development award application has an objective to evaluate the utility of mobile technology OpenCap in quantifying mechanical markers that may provide insights into joint health in patients with early knee OA and to extract these markers from functional activities commonly used in knee OA management.
Specific Aims: Aim 1 will evaluate the current potential use of the mobile technology OpenCap in patients with knee OA by testing the hypotheses that (1a) mechanical markers estimated by the mobile technology significantly differ but are associated with those measured using conventional Mocap and (1b) the mobile technology detects within-person, within-visit mechanical differences introduced by functional activity variations. Aim 2 will explore the broader use of the mobile technology OpenCap in patients with knee OA by (2a) associating mechanical markers estimated by the mobile technology with patient-reported outcomes (PROs), performance-based measures, and structural metrics and (2b) determining the test-retest reliability of the mechanical markers.
Anticipated Research Outcomes: The project findings will have the potential to enable clinicians to trial the technology in its current form, leveraging its potential to quantify and document movement mechanics in patients at risk of or with knee OA. At the same time, the project's results will explore more advanced applications, such as tracking functional changes over time during OA treatment and contributing critical data to refine and further develop the technology. On the other hand, recalling an existing research cohort offers an invaluable opportunity for longitudinal follow-up.
Anticipated Training Outcomes: This award will provide the applicant with training in musculoskeletal modeling, data science, and clinical and translational science, enabling the applicant to validate and refine mobile motion capture technologies. This training will prepare the applicant to integrate mobile technologies into clinical practice and support applicant's advancement to independence through next-level CDA award.
Path to Translation/Implementation: This study will provide clinicians with practical insights on using OpenCap in its current form to quantify and document joint health. Findings will inform future refinements and support subsequent efforts to evaluate the feasibility of video-based motion capture via OpenCap in OA care. This project aligns with VA priorities by improving early diagnosis and management of knee OA to enhance care for Veterans.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Knee OA | – | –Adults who were previously diagnosed with early knee osteoarthritis, enrolled in Precision Assessment of Platelet Rich Plasma for Joint Preservation study (NCT03460236), and able and willing to participate in the follow-up assessment. |
Who may qualify
- Ages
- 30 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Individuals who were diagnosed with early knee osteoarthritis and had a history of being elected to receive injection treatment
Key inclusion criteria (5 listed)
- Veteran and non-Veterans
- males and females
- diagnosed with early knee osteoarthritis
- qualified for and participated in the Precision Assessment of Platelet Rich Plasma for Joint Preservation study (ClinicalTrials.gov ID: NCT03460236)
- able and willing to provide informed consent for follow-up study
Key exclusion criteria (6 listed)
- symptomatic OA in joints other than the knee in the lower body
- joint replacement
- rheumatic disease
- BMI > 35 kg/m^2
- severe systematic disease defined as American Society of Anesthesiologists (ASA) 3 or above
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Knee flexion angle
Time frame: Baseline and Week 1
Knee flexion angle extracted from functional activities (e.g., walking, chair-to-stand)
1 secondary outcome
Knee flexion moment
Time frame: Baseline and Week 1
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 May 2026.
- Individual participant dataSharing planned: No
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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.
Jade He, PhD principal investigator
VA Palo Alto Health Care System, Palo Alto, CA
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Osteoarthritis, Knee, run by VA Office of Research and Development 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 5 inclusion and 6 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: looking for participants now, as of the sponsor's last update on 12 May 2026. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Jade He, PhD ((650) 493-5000 ext. 64431, Jade.He@va.gov), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Knee flexion angle (time frame: Baseline and Week 1). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 12 May 2026.