Current methods for contactless optical patient diagnosis: a systematic review

Area of Science:

• Medical Technology
• Artificial Intelligence in Healthcare
• Patient Monitoring

Background:

• Healthcare systems globally face personnel shortages, leading to increased workload and burnout.
• Manual vital sign measurement is time-consuming and contributes significantly to healthcare professionals' burden.
• Contactless monitoring technologies present an opportunity to alleviate this workload.

Purpose of the Study:

• To systematically review the state-of-the-art in contactless optical patient diagnosis.
• To identify studies integrating contactless vital sign measurement with automated patient condition assessment.
• To analyze the current research landscape and identify gaps in automated contactless diagnosis.

Main Methods:

• Systematic literature review conducted by two independent reviewers.
• Screening of studies focusing on contactless vital sign monitoring and automated diagnosis.
• Analysis of eligible studies for their methodologies and diagnostic applications.

Main Results:

• Five eligible studies were identified.
• Three studies focused on infectious disease risk assessment.
• One study addressed cardiovascular disease risk, and another focused on obstructive sleep apnea diagnosis.
• Significant heterogeneity was observed across study parameters.

Conclusions:

• Contactless optical patient diagnosis, incorporating automated reasoning, shows potential for clinical application.
• A notable research gap exists, indicated by the low number of eligible studies.
• Further research is crucial to advance automated contactless diagnosis and its integration into clinical practice.