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Visual Computing for Industry, Biomedicine, and Art
Fig. 4 | Visual Computing for Industry, Biomedicine, and Art

Fig. 4

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

Fig. 4

Method outline: Participants were instructed to remain still for approximately 30 s to establish a baseline assessment. This was followed by four experimental conditions of PMaj resistance training. The training session consisted of two assigned load training intensities (50% of 1-RM and 80% of 1-RM), with the conditions without RUSI biofeedback continuously being performed before the condition with RUSI biofeedback. One set of three repetitions was performed in each experimental condition. Our methodology employs a comprehensive automated approach for calculating PMaj thickness across the entire probe detection region (scanning depth is 55 mm and each small segment is 5 mm), in contrast to manual measurement methods [9]

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