Photogrammetry-based smartphone applications for spinal posture assessment: a systematic review and meta-analysis

Area of Science:

• Biomedical Engineering
• Health Informatics
• Kinesiology

Background:

• Smartphones are increasingly integrated into healthcare for various diagnostic and monitoring purposes.
• Accurate human posture assessment is crucial for diagnosing musculoskeletal conditions and guiding rehabilitation.

Purpose of the Study:

• To systematically review and evaluate mobile applications that use photogrammetry for assessing body alignment.
• To determine the reliability and validity of smartphone-based posture analysis tools.

Main Methods:

• Systematic review following PRISMA 2020 guidelines, registered in PROSPERO.
• Searches across major scientific databases (PubMed, Scopus, Web of Science, etc.).
• Inclusion of studies on smartphone app development, testing, or validation for posture analysis; exclusion of wearable or radiographic methods.

Main Results:

• 29 studies with 1,910 participants were included.
• Pooled intraclass correlation coefficients (ICCs) indicated excellent test-retest (0.904) and inter-rater (0.889) reliability for craniovertebral angle.
• Moderate to excellent reliability was observed for hip tilt, head tilt, and acromion alignment measurements.

Conclusions:

• Smartphone applications utilizing photogrammetry demonstrate high reliability for posture assessment.
• These findings support the clinical utility and integration of mobile health tools in musculoskeletal evaluation.
• Further research should address study heterogeneity and reporting inconsistencies to enhance evidence quality.