Posture Analysis Through Machine Learning (PathML)

This study will include video-recorded data from 20 adults (age 18-85yrs) residing in San Luis Obispo, CA. Participants will also have their height and weight measured, complete demographic questionnaires, and one 3hour session with video recordings in a combination of naturalistic condition and semi-structured environments. The video data will be used to train machine learning models to automatically classify physical behavior as compared to ground-truth measures of manual annotation.

Study Overview

• Status: Active, not recruiting
• Conditions: Health Behavior

Detailed Description

This is a cross-sectional, single observation study. Individuals will be drawn from local surrounding clinics and the general community. All recruitment will include both men and women. Selection criteria include individuals between the ages of 18-85 years, no major chronic illness that impair mobility and able to complete activities of daily living without assistance. Participants will complete one three hour session where there will be one video camera set up within the home (i.e., static cameras). For approximately 30 minutes of the session they will complete a semi-scripted routine that will include sit to stand transitions, a timed up and go test, and scripted activities of daily living.

Researchers will use a video camera to record participant behavior within their daily life. For two of the three hours, researchers will be video recordings the participants normal (unscripted) activities. • For one hour of the session we will use two cameras, one that will be held by a researcher and one that will be set up on a tripod. During this hour we will ask participants to follow a semi-structured protocol:

• 10 minutes recording the empty space
• 10 minutes that include a timed up a go test (sit up from a chair and walk 10 feet), repeat the test 3 times.
• 6 minute walk test (walk continuously for 6 minutes)
• Four stage balance test
• The remainder of the time, participants will complete standard activities of daily living like household chores, eating or drinking.

Data will be annotated using an established behavioral observation software by training research assistants (ground-truth). The image data from videos will be used to train machine learning models to classify physical activities (e.g. ,'walking', 'sitting' or 'standing up"), information about behavior (e.g., location and purpose of the activity), and performance (e.g., walking speed and sit to stand transition times).

• Study Type: Observational
• Enrollment (Actual): 20

Contacts and Locations

Study Locations

• United States
  • California
    • San Luis Obispo, California, United States, 93407
      • CalPoly

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 85 years (Adult, Older Adult)
• Accepts Healthy Volunteers: N/A
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Generally health adult population recruited from local community

Description

Inclusion Criteria:

1. Age 18-85 years
2. No major chronic illness that impair mobility
3. Able to complete activities of daily living without assistance.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
Recordings; Selection criteria include individuals between the ages of 18-85 years, no major chronic illness that impair mobility and able to complete activities of daily living without assistance. We will recruit approximately equal number of men and women and 30% of the sample will be racial or ethnic minorities.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Postural Status	Sitting versus standing versus moving	Upon enrollment (one timepoint)
Activity type	Indoor vs outdoor vs driving	Upon enrollment (one timepoint)
Sit to stand transition time	Time it takes to go from sitting to standing	Upon enrollment (one timepoint)

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Activity intensity	Sedentary, light, moderate and vigorous intensity	Upon enrollment (one timepoint)
Activity type	lying, sitting, driving, standing, housework or office work, walking, running, sports, other	Upon enrollment (one timepoint)

Collaborators and Investigators

• Sponsor: SentiMetrix, Inc
• Collaborators: California Polytechnic State University-San Luis Obispo
• Investigators: Principal Investigator: Sarah Keadle, Cal Poly

Study record dates

Study Major Dates

• Study Start (Actual): November 1, 2021
• Primary Completion (Anticipated): June 30, 2022
• Study Completion (Anticipated): June 30, 2022

Study Registration Dates

• First Submitted: August 27, 2021
• First Submitted That Met QC Criteria: August 27, 2021
• First Posted (Actual): September 5, 2021

Study Record Updates

• Last Update Posted (Actual): May 10, 2022
• Last Update Submitted That Met QC Criteria: May 4, 2022
• Last Verified: May 1, 2022

More Information

Terms related to this study

• Keywords: adult; behavioral observation; computer vision; methodology
• Other Study ID Numbers: PathML2021

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