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您的检索式：作者名="Steffen Leonhardt"
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| 1 | Mobile noncontact monitoring of heart and lung activity显示文摘 | Steffen M Alek sandrowicz A Leonhardt S | 2007 | IEEE Trans Circ Syst2007，1，4： | 1 |
| 2 | Non-Contact Monitoring of Heart and Lung Activity by Magnetic Induction Measurement显示文摘 | Steffen M Leonhardt S | 2008 | Acta Polytechnica2008，48，3： | 1 |
| 3 | Artificial intelligence for closed-loop ventilation therapy with hemodynamic control using the open lung concept显示文摘Purpose–The purpose of this paper is to develop an automatic control system for mechanical ventilation therapy based on the open lung concept(OLC)using artificial intelligence.In addition,mean arterial blood pressure(MAP)is stabilized by means of a decoupling controller with automated noradrenaline(NA)dosage to ensure adequate systemic perfusion during ventilation therapy for patients with acute respiratory distress syndrome(ARDS).Design/methodology/approach–The aim is to develop an automatic control system for mechanical ventilation therapy based on the OLC using artificial intelligence.In addition,MAP is stabilized by means of a decoupling controller with automated NA dosage to ensure adequate systemic perfusion during ventilation therapy for patients with ARDS.Findings–Thisinnovativeclosed-loop mechanicalventilation system leadsto a significant improvement in oxygenation,regulates end-tidal carbon dioxide for appropriate gas exchange and stabilizes MAP to guarantee proper systemic perfusion during the ventilation therapy.Research limitations/implications–Currently,this automatic ventilation system based on the OLC can only be applied in animal trials;for clinical use,such a system generally requires a mechanical ventilator and sensors with medical approval for humans.Practical implications–For implementation of a closed-loop ventilation system,reliable signals from the sensors are a prerequisite for successful application.Originality/value–Theexperiment with porcine dynamics demonstrates thefeasibility and usefulness of this automatic closed-loop ventilation therapy,with hemodynamic control for severe ARDS.Moreover,this pilot study validated a new algorithm for implementation of the OLC,whereby all control objectives are fulfilled during the ventilation therapy with adequate hemodynamic control of patients with ARDS. | Anake Pomprapa Danita Muanghong Marcus Köny Steffen Leonhardt Philipp Pickerodt Onno Tjarks David Schwaiberger Burkhard Lachmann | 2015 | International Journal of Intelligent Computing and Cybernetics2015，8，1： | 0 |
| 4 | Model-based optimization of adaptive external counterpulsation therapy显示文摘External counterpulsation therapy(ECP)is a non-invasive method to assist the circulatory system.The main principle of ECP is to initiate a diastolic pulse wave in the arterial system by squeezing the inner leg vessels.Superficial and low veins are compressed due to muscle contractions,which are triggered by functional electrical stimulation(FES).In this work,a new trigger method for the stimulation is proposed.Blood flow is determined by measuring the pulsatile change of conductivity in the observed segment by impedance plethysmography.The proposed“adaptive stimulation”allows the automatic adjustment of the start and duration of the stimulation to improve transport of venous blood.For this purpose,a mathematical circulation model was developed for optimization of the adaptive functional electrical stimulation.The model takes into account the effects of gravity,muscle pump with or without FES,and venous regurgitation.The model was shown to have a behavior similar to that of clinical measurements.The simulation showed a flow enhancement of up to 14%and,furthermore,that the start of the stimulation is less important than the duration of each stimulation phase.Therefore,an adaptation of the heart rate seems necessary,as the expulsion and refill times must remain relatively constant for an optimal pumping result.For a practical approach,it is reasonable to adapt the duration of stimulation to 56%of the cardiac cycle in order to reach a maximum flow. | Soren Weyer Hannes Weber Christian Kleeberg Steffen Leonhardt Daniel Teichmann | 2016 | International Journal of Modeling, Simulation, and Scientific Computing2016，7，2： | 0 |
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