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Visual Computing for Industry, Biomedicine, and Art
Fig. 7 | Visual Computing for Industry, Biomedicine, and Art

Fig. 7

From: Automated analysis of pectoralis major thickness in pec-fly exercises: evolving from manual measurement to deep learning techniques

Fig. 7

Distribution of the measurement locations of the PMaj maximum thickness change for different experimental conditions (n = 25). (a) represents the 50% of 1-RM without RUSI biofeedback; (b) represents the 50% of 1-RM with RUSI biofeedback; (c) represents the 80% of 1-RM without RUSI biofeedback; (d) represents the 80% of 1-RM with RUSI biofeedback. We found that the PMaj maximum thickness occurrences had the highest ratio within the rightmost interval of the graph

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