Machine Learning to Analyze Facial Imaging, Voice and Spoken Language for the Capture and Classification of Cancer/Tumor Pain

NCT04442425 | Completed

• 2 other identifiers: 20013020-C-0130
• Study Type: observational
• Target: 83
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Cancer; Neoplasms; Solid Tumors

Keywords

Telehealth; Self-Reported Pain; Facial Recognition Technology; Pain Score; Natural History

Outcome Measures

Primary Outcomes (1)

• Feasibility of using facial recognition technology to classify pain

  The primary objective of this study is to determine the feasibility of using facial recognition technology to classify pain in a demographically diverse set of patients with cancer/tumor who are participating on a clinical trial.

  3 months

Secondary Outcomes (4)

• To determine the feasibility of using voice recognition technology

  3 months

• To transcribe patient video responses to assess pain using free-text

  3 months

• To determine the feasibility of combining RGB and thermal images with voice recognition transcribed verbal responses

  3 months

• To use natural language processing algorithms to assess pain

  3 months

Study Arms (16)

1DF/NoPain_IV-VI_Female

Worst pain in past month = 0; Skin Type IV-VI, Female

1DM/NoPain_IV-VI_Male

Worst pain in past month = 0; Skin Type IV-VI, Male

1LF/NoPain_I-III_Female

Worst pain in past month = 0; Skin Type I-III, Female

1LM/NoPain_I-III_Male

Worst pain in past month = 0; Skin Type I-III, Male

2DF/MildPain_IV-VI_Female

Worst pain in past month = 1-3; Skin Type IV-VI, Female

2DM/MildPain_IV-VI_Male

Worst pain in past month = 1-3; Skin Type IV-VI, Male

2LF/MildPain_I-III_Female

Worst pain in past month = 1-3; Skin Type I-III, Female

2LM/MildPain_I-III_Male

Worst pain in past month = 1-3; Skin Type I-III, Male

3DF/ModPain_IV-VI_Female

Worst pain in past month = 4-6; Skin Type IV-VI, Female

3DM/ModPain_IV-VI_Male

Worst pain in past month = 4-6; Skin Type IV-VI, Male

3LF/ModPain_I-III_Female

Worst pain in past month = 4-6; Skin Type I-III, Female

3LM/ModPain_I-III_Male

Worst pain in past month = 4-6; Skin Type I-III, Male

4DF/SeverePain_IV-VI_Female

Worst pain in past month = 7-10; Skin Type IV-VI, Female

4DM/SeverePain_IV-VI_Male

Worst pain in past month = 7-10; Skin Type IV-VI, Male

4LF/SeverePain_I-III_Female

Worst pain in past month = 7-10; Skin Type I-III, Female

4LM/SeverePain_I-III_Male

Worst pain in past month = 7-10; Skin Type I-III, Male

Eligibility Criteria

• Age: 12 Years - 120 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with histologically or cytologically proven cancer or tumor

You may qualify if:

• 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
• service providers.

You may not qualify if:

• 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.
• Known current alcohol or drug abuse.
• Any psychiatric condition that would prohibit the understanding or rendering of informed consent.
• Non-English speaking subjects.

Sponsors & Collaborators

• National Cancer Institute (NCI): lead

Study Sites (1)

National Institutes of Health Clinical Center

Bethesda, Maryland, 20892, United States

Location

Related Links

• NIH Clinical Center Detailed Web Page

MeSH Terms

Conditions

Neoplasms

Study Officials

• James L Gulley, M.D.

  National Cancer Institute (NCI)

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: NIH
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: June 19, 2020
• First Posted: June 22, 2020
• Study Start: October 27, 2020
• Primary Completion: March 27, 2024
• Study Completion: March 27, 2024
• Last Updated: July 16, 2026

Record last verified: 2026-04-29

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF
• Time Frame: Clinical data available during the study and indefinitely.
• Access Criteria: Clinical data will be made available via subscription to BTRIS and with the permission of the study PI.

Locations

US (1)