sEMG as a Method for Characterizing Mammogram Discomfort (Preprint)

BACKGROUND Mammograms are the most readily used procedures for early breast cancer detection but are notorious for the discomfort they induce in patients. This physiological strain has been validated by many questionnaire-based investigations, some of which indicate it may discourage and/or deter women from potentially lifesaving healthcare. While informative, these subjective measures are highly variable and do not provide an objective perspective regarding the coordinated physiological and ergonomic response required for the procedure. OBJECTIVE A multi-muscle surface electromyography (sEMG) methodology is proposed to better understand the machine-patient dynamics and potentially develop objective measures of mammogram related pain and stress. METHODS Seven different muscle pairs on the neck, shoulders, and torso were identified as being critical in postural positioning during the industry-standard mammogram procedure. sEMG was recorded during eight compressions across two mammograms simulations for 25 women wearing wireless devices. An illustrative map of muscle activity was created based on a comprehensive 10-metric sEMG analysis that compared baseline recordings to activated states during each compression. RESULTS The deltoid demonstrated the highest muscular activation across trials with an increase in meanRMS activity of up to 436%, while the trapezius upper fibers, infraspinatus, and teres major also showed significant increases in muscle activation averaging 89-155% when compared to rest states. Across metrics, muscle activations were ipsilaterally correlated, with significant differences observed only when the breast was compressed on the same side as the muscle being measured. The serratus anterior and external oblique muscles showed minimal activation for any compression or positioning. No significant differences were found between curved and flat paddle designs. After the breast, patient-reported discomfort localized primarily to the shoulder and neck regions, corroborating the physiological measurements. CONCLUSIONS The juxtaposition of muscle-specific activity against inactive muscles, along with reported discomfort values, demonstrates that the sEMG methodology accurately captures the patient-machine interaction dynamics with objective, quantifiable precision that complements subjective feedback. By providing real-time physiological data on muscular patterns and biomechanical responses throughout the procedure, this sEMG-based approach offers measurable metrics for evaluating proposed improvements to mammogram equipment design and protocols. CLINICALTRIAL N/A