Mobile Technology to Measure Knee Health in Osteoarthritis

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.

Study Overview

• Status: Recruiting
• Conditions: Osteoarthritis, Knee

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 Type: Observational
• Enrollment (Estimated): 47

Contacts and Locations

• Study Contact: Name: Jade He, PhD; Phone Number: 64431 (650) 493-5000; Email: Jade.He@va.gov

Study Locations

• United States
  • California
    • Palo Alto, California, United States, 94304-1207
      • Recruiting
      • VA Palo Alto Health Care System, Palo Alto, CA
      • Contact: Jade He, PhD; Phone Number: 64431 650-493-5000; Email: Jade.He@va.gov
      • Principal Investigator: Jade He, PhD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Individuals who were diagnosed with early knee osteoarthritis and had a history of being elected to receive injection treatment

Description

Inclusion Criteria:

• 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

Exclusion Criteria:

• 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

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
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 the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Knee flexion angle	Knee flexion angle extracted from functional activities (e.g., walking, chair-to-stand)	Baseline and Week 1

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Knee flexion moment	Knee flexion moment estimated from functional activities (e.g., walking, chair-to-stand)	Baseline and Week 1

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Western Ontario and McMaster Universities Osteoarthritis Index (Transformed)	Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores will be calculated from answers to the Knee Injury and Osteoarthritis Outcome Score questionnaire, including domains of Pain, Stiffness, and Function. WOMAC scores will be transformed to a scale of 0-100, with higher scores indicating fewer symptoms.	Baseline and Week 1
Duration of 40-meter fast walk test	Duration in seconds to complete 40-meter fast walk test	Baseline or Week 1
Repetitions for 30-second chair-to-stand test	The number of repetitions of chair-to-stand performed during 30-second	Baseline or Week 1

Collaborators and Investigators

• Sponsor: VA Office of Research and Development
• Investigators: Principal Investigator: Jade He, PhD, VA Palo Alto Health Care System, Palo Alto, CA

Study record dates

Study Major Dates

• Study Start (Actual): April 1, 2026
• Primary Completion (Estimated): September 30, 2027
• Study Completion (Estimated): March 31, 2028

Study Registration Dates

• First Submitted: April 8, 2026
• First Submitted That Met QC Criteria: May 5, 2026
• First Posted (Actual): May 12, 2026

Study Record Updates

• Last Update Posted (Actual): May 12, 2026
• Last Update Submitted That Met QC Criteria: May 5, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Musculoskeletal Diseases; Arthritis; Joint Diseases; Rheumatic Diseases; Osteoarthritis; Osteoarthritis, Knee
• Other Study ID Numbers: RRD8-005-24W; 66791 (Other Identifier: Stanford IRB); IK1RD000707 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No