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Published on: August 25, 2022
Surface Electromyography as a Method for Characterizing Mammogram Discomfort: Cross-Sectional Questionnaire Study of
Krystyna Gielo-Perczak1, Riley McNaboe1, Hugo Posada-Quintero1
1Department of Biomedical Engineering, College of Engineering, University of Connecticut, Arthur B Bronwell Bldg, 260 Glenbrook Road, Storrs, CT, 06269, United States, 1 860-486-0370, 1 860-486-2500.
Surface electromyography (sEMG) objectively measured muscle activity during mammograms, revealing significant deltoid and trapezius activation. This technology offers quantifiable insights into patient discomfort and machine-patient dynamics.
Area of Science:
- Biomedical Engineering
- Medical Imaging Physics
Background:
- Mammograms are crucial for early breast cancer detection but often cause patient discomfort, potentially deterring women from screenings.
- Subjective pain reports are variable and lack objective physiological data on patient response during mammography.
Purpose of the Study:
- To introduce a multimuscle surface electromyography (sEMG) methodology for objective assessment of mammogram-related pain and stress.
- To analyze machine-patient dynamics and develop objective measures of physiological strain during mammography.
Main Methods:
- sEMG recorded activity from seven muscle pairs in the neck, shoulders, and torso during mammogram simulations.
- 25 women participated, undergoing 8 compressions with wireless sEMG devices.
- A 10-metric analysis compared muscle activation during compressions to baseline recordings.
Main Results:
- The deltoid muscle showed the highest activation (up to 436% increase), with significant increases also observed in the trapezius, infraspinatus, and teres major (89-155%).
- Muscle activation correlated ipsilaterally with breast compression.
- Patient-reported discomfort in the shoulder and neck aligned with physiological measurements.
Conclusions:
- sEMG methodology provides objective, quantifiable data on patient-machine interaction during mammograms, complementing subjective feedback.
- This approach offers measurable metrics for evaluating mammogram equipment design and protocol improvements.
- Real-time physiological data can enhance understanding of biomechanical responses and patient comfort.

