Esophageal pressure is currently seen as the gold standard to quantify the respiratory effort during assisted spontaneous ventilation. Yet, the assessment of waveforms at the bedside is often complicated due to heavy interference by cardiac artifacts and due to the unknown dependency on the lung volume. We propose an algorithm that automatically removes artifacts and gives an estimate for the respiratory effort of a patient. The estimator is based on fitting a respiratory system model to the Campbell diagram and, thus, also gives insight into important patient parameters like the chest wall elastance. The feasibility of our approach is demonstrated using clinical datasets of patients on pressure support ventilation. The algorithm facilitates the interpretation of ventilatory waveforms and may support the overall assessment of patients.