Clinical Trial Details
— Status: Active, not recruiting
Administrative data
NCT number |
NCT05034302 |
Other study ID # |
PathML2021 |
Secondary ID |
|
Status |
Active, not recruiting |
Phase |
|
First received |
|
Last updated |
|
Start date |
November 1, 2021 |
Est. completion date |
June 30, 2022 |
Study information
Verified date |
May 2022 |
Source |
SentiMetrix, Inc |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
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.
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).