Machine Learning to Analyze Facial Imaging, Voice and Spoken Language for the Capture and Classif… (NCT04442425) | Clinical Trial Compass
CompletedNot Applicable
Machine Learning to Analyze Facial Imaging, Voice and Spoken Language for the Capture and Classification of Cancer/Tumor Pain
United States83 participantsStarted 2020-10-27
Plain-language summary
Background:
Cancer pain can have a very negative effect on people s daily lives. Researchers want to use machine learning to detect facial expressions and voice signals. They want to help people with cancer by creating a model to measure pain. They want the model to reflect diverse faces and facial expressions.
Objective:
To find out whether facial recognition technology can be used to classify pain in a diverse set of people with cancer. Also, to find out whether voice recognition technology can be used to assess pain.
Eligibility:
People ages 12 and older who are undergoing treatment for cancer
Design:
Participants will be screened with:
Cancer history
Information about their sex and skin type
Information about their access to a smart phone and wireless internet
Questions about their cancer pain
Participants will have check-ins at the clinic and at home. These will occur over about 3 months. They will have 2-4 check-ins at the clinic. They will check in at home about 3 times per week.
During check-ins, participants will answer questions and talk about their cancer pain. They will use a mobile phone or a computer with a camera and microphone to complete a questionnaire. They will record a video of themselves reading a 15-second passage of text and responding to a question.
During the clinic check-ins, professional lighting, video equipment, and cameras will be used for the recordings.
During remote check-ins, participants will be asked to complete the questionnaire and recordings alone. They should be in a quiet and bright room. The room should have a white wall or background.
Who can participate
Age range12 Years – 120 Years
SexALL
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Inclusion criteria
✓. Ability of subject to understand and willingness to sign a written informed consent document.
✓. Adults and children (including NIH staff) aged \>= 12 years.
✓. Participants with diagnosis of a cancer or tumor
✓. Participant must be receiving either standard of care or investigational cancer/tumor treatment either at NIH or with a community physician.
✓. Must have access to a smart phone (iPhone or Android) with either a data plan and/or access to wireless internet (wifi) or a computer with a camera and microphone and access to internet and must willing to use their device and assume any associated charges from
Exclusion criteria
✕. Participants with progressive brain tumors or metastasis. Participants with treated brain metastasis or primary brain tumor are eligible if there is no evidence of progression for at least 4 weeks after CNS directed treatment and there is no impact on voice or facial muscle movements.
✕. Participants with Parkinson s disease.
✕
What they're measuring
1
Feasibility of using facial recognition technology to classify pain