Pascal Gaggero

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About

Pascal Gaggero’s research centers on advancing **electrical impedance tomography (EIT)** for clinical use, with a focus on non-invasive monitoring of pulmonary and cardiovascular functions. His major contributions lie in improving the **reliability and robustness** of EIT systems, addressing critical barriers that have hindered their transition from laboratory settings to everyday use in intensive care units (ICUs). In his most-cited work, “Automated robust test framework for electrical impedance tomography” (2015, 11 citations), Gaggero developed a systematic, automated testing procedure using a saline phantom and industrial robot to calculate reliable, repeatable performance metrics—a foundational step for standardizing EIT device validation. His earlier study, “Compensating Electrode Errors Due to Electrode Detachment in Electrical Impedance Tomography” (2013, 3 citations), tackled a common clinical challenge by proposing compensation methods for measurement errors caused by electrode detachment, directly enhancing data accuracy in real-world patient monitoring. Through these efforts, Gaggero has strengthened the **practical viability of EIT**, making strides toward its adoption as a bedside tool for continuous respiratory and cardiac assessment. His work is particularly notable for bridging engineering rigor with clinical needs, offering solutions that improve both **testability and error resilience** in medical imaging.