Smartphone Positioning Affects Pose Estimation Accuracy
This cross-sectional within-subject study of 44 university students evaluated how smartphone camera angle (front, side, diagonal) and distance (90, 180, 200, 360 cm) affect AI-based pose-estimation detection and repetition counting for push-ups and squats. Across ~1,320 repetitions per exercise, mean detection rates were ≈61% with MAEs ≈1.1 repetitions; diagonal and frontal mid-range views (180–200 cm) produced the highest accuracy. Findings offer actionable guidance for mHealth developers and clinicians.
Key Points
- 1Reports mean detection rates of ~61% and mean absolute errors around 1.1 repetitions per exercise.
- 2Shows diagonal and frontal mid-range views (180–200 cm) markedly increase detection and counting precision.
- 3Guides developers and clinicians to recommend diagonal or front mid-range positioning for reliable exercise-tracking.
Scoring Rationale
Strong experimental design and actionable results, limited generalizability due to small, young university participant sample.
Sources
Public references used for this report.
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