High-quality Image (NIR and RGB) Dataset Synchronized With Contact Vital Sings Recordings and Clinical Data of Stratified Healthy Population. Algorithms and AI Models to Obtain a Set of Vital Signs Image-based.

NCT05947721 | Completed

• 1 other identifier: Frejya/IBV-Dataset
• Study Type: observational
• Target: 60
• Locations: 1 country
• Sites: 1

Brief Summary

The objective of this study is to collect an image dataset of healthy and pathological population with a characterization of the potential factors that may influence the methodologies used to obtain vital signs. To this end, an observational study of qualitative and quantitative data collection through cameras, contact recording technologies (gold standards) and questionnaires has been proposed. Based on these data, the specific objectives of this study are as follows:

• To determine the differences according to the factors analysed.
• Develop/fine-tune algorithms/AI models to obtain quality rPPG/rBCG signals.
• Fine-tune models to obtain the main vital signs as HR, RR, SpO2 and BP from image-based-data. The dataset (namely Freyja/IBV-Dataset) is composed of 73 subjects (35 females and 38 males) with ages ranging from 18 to 85, representation in the 6 skin phototypes according to the Fitzpatrick scale (1), and BMI ranging from 15 to 40. In order to determine the sample size, specific ranges have been defined for each of the intrinsic subject factors and all possible combinations have been covered. The number of subjects defined for each combination was based on the percentage it represents in the Spanish population according to the INE (Instituto Nacional de Estadística). The subjects will be recruited through the own databases of participants in previous trials of the Institute of Biomechanics of Valencia, who have given written consent to be contacted in order to request their participation in any other study where their profile may fit. The surveys will be included in an online platform specialized in the realization of questionnaires. This data will be exported for further storage, management and analysis. All information will be anonymized for processing and analysis, and may be used under the terms and conditions dictated by the current legal framework. To participate in the study, participants must accept the terms and conditions included in the first page of the survey embedded in the online platform, where the aspects related to the study methodology and the use of them data are exposed.

Conditions

Healthy Population (HP)

Keywords

Dataset; Physiological signals; Remote Photopletismography

Outcome Measures

Primary Outcomes (4)

• Heart Rate (HR)

  Frequency of the heartbeat measured by the number of contractions of the heart per minute (beats per minute).

  Cross-sectional: Observations or measurements made at a single point in time, usually at subject enrollment. Each of the registers have a duration of 60s.

• Respiration Rate (RR)

  The respiratory rate is the rate at wich breathing occurs and is measured in breaths per minute.

  Cross-sectional: Observations or measurements made at a single point in time, usually at subject enrollment. Each of the registers have a duration of 60s.

• Oxigen saturation (SpO2)

  SpO2 is the fraction of oxygen-saturated haemoglobin relative to total haemoglobin (unsaturated + saturated) in the blood.

  Cross-sectional: Observations or measurements made at a single point in time, usually at subject enrollment.

• General information questionnaire

  Custom-made questionnaire designed to collect relevant sociodemografic and clinical information os each subject, including: age, gender, height, weight, date of birth, Fitzpatrick Phototype and risk factors (hypertension, diabetes, tabacquismo, diet, apnea, physical activity, alcohol consumption and metabolic syndrome).

  Cross-sectional: Observations or measurements made at a single point in time, usually at subject enrollment.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Community sample. Contacted by the collaborators or by IBV itself.

You may qualify if:

• Men and women older tan 18 years old with no chronic or acute conditions declared.
• Having the ability to understand the information of the questionnaires to be completed.

You may not qualify if:

• Non-acceptance of the terms and conditions of the study.
• Electronic implants (pacemakers, insulin pumps, cochlear implants).
• Epilepsy.
• Allergies or cutaneous hypersensitivity to the different components of the contact equipment, such as gels/adhesives.
• Presence of tattoos or other serious skin alterations (large burns, keloids...) in the face area.
• Infectious diseases of the skin, atopic dermatitis, erythroderma, rosacea...

Sponsors & Collaborators

• Instituto de Biomecanica de Valencia: lead

Study Sites (1)

Instituto de Biomecánica de Valencia. Universitat Politècnica de Valéncia

Valencia, 46021, Spain

Location

Related Publications (5)

• Sachdeva S. Fitzpatrick skin typing: applications in dermatology. Indian J Dermatol Venereol Leprol. 2009 Jan-Feb;75(1):93-6. doi: 10.4103/0378-6323.45238. No abstract available.

  PMID: 19172048 BACKGROUND

• Khanam FTZ, Al-Naji A, Chahl J. Remote Monitoring of Vital Signs in Diverse Non-Clinical and Clinical Scenarios Using Computer Vision Systems: A Review. Applied Sciences. enero de 2019;9(20):4474.

  BACKGROUND

• Liu X, Yin J, Liu Y, Zhang S, Guo S, Wang K. Vital Signs Monitoring with RFID: Opportunities and Challenges. IEEE Network. julio de 2019;33(4):126-32.

  BACKGROUND

• Pham C, Poorzargar K, Nagappa M, Saripella A, Parotto M, Englesakis M, Lee K, Chung F. Effectiveness of consumer-grade contactless vital signs monitors: a systematic review and meta-analysis. J Clin Monit Comput. 2022 Feb;36(1):41-54. doi: 10.1007/s10877-021-00734-9. Epub 2021 Jul 9.

  PMID: 34240262 BACKGROUND

• Al-Naji A, Gibson K, Lee SH, Chahl J. Monitoring of Cardiorespiratory Signal: Principles of Remote Measurements and Review of Methods. IEEE Access. 2017;5:15776-90.

  BACKGROUND

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 7, 2023
• First Posted: July 17, 2023
• Study Start: June 1, 2022
• Primary Completion: December 1, 2022
• Study Completion: December 1, 2022
• Last Updated: July 17, 2023

Record last verified: 2023-07

Data Sharing

• IPD Sharing: Will not share

Locations

ES (1)