Delayed intracardial shunting and hypoxemia after massive pulmonary embolism in a patient with a biventricular assist device

We describe the interdisciplinary management of a 34-year-old woman with dilated cardiomyopathy three months postpartum on a cardiac biventricular assist device (BVAD) as bridge to heart transplantation with delayed onset of intracardial shunting and subsequent hypoxemia due to massive pulmonary embolism. After emergency surgical embolectomy pulmonary function was highly compromised (PaO2/FiO2 54) requiring bifemoral veno-venous extracorporeal membrane oxygenation. Transesophageal echocardiography detected atrial level hypoxemic right-to-left shunting through a patent foramen ovale (PFO). Percutaneous closure of the PFO was achieved with a PFO occluder device. After placing the PFO occluder device oxygenation increased significantly (Δ paO2 119 Torr). The patient received heart transplantation 20 weeks after BVAD implantation and was discharged from ICU 3 weeks after transplantation

A physicsbased model for predicting user intent in shared-control pedestrian mobility aids

Abstract — This paper presents a physics-based model approach to infer navigational intent of the user of a walker, based on measuring forces and moments applied to the walker’s handles. Our experiments use two 6-DOF force/moment sensors on the walker’s handles, a 2-D kinematic-dynamic model of the walker and a digital motion capture system to trace the path of the walker. The motion capture system records the path the walker follows while the 6 DOF sensors record the handle forces used to guide the walker along that path. A dynamic model of the walker that determines user navigational intent from force/moment data was developed and validated against the motion capture data streams. This paper describes the development and validation of the model as well as plans for using the model as a path predictor. The inferred user intent will be incorporated into a passive shared steering control system for the walker

Shared Navigational Control and User Intent Detection in an Intelligent Walker

This paper describes the navigational control scheme used in the CO-Operative Locomotion Aide (COOL Aide), an intelligent walker designed to assist the elderly or the disabled with normal, and routine walking tasks. Navigation is achieved through a shared control architecture that recognizes the goals of both the human user and the walker. The control system is based on a synthesis of heuristic logic that exploits a dynamic model of walker system that can detect sliding and loss of walker stability. The model is used to predict the user’s intended path, based on the history of information collected from the walker’s sensors. Sensor information consists primarily of the forces and moments the user exerts on the walker’s handles during the natural assisted walking process, as well as the user’s local environment. Based on the model’s prediction, the walker’s state, and the walker’s environment, the control system can confirm or overturn the hypotheses of user’s intent it put forward and can influence the walker’s heading if the system believes the user will not reach the perceived intended goal unassisted. This paper discusses the model’s use in the shared control scheme and the mechanism for detecting/handling errors in the model’s predictions

User Intent in a Shared Control Framework for Pedestrian Mobility Aids

This paper presents a novel approach to infer navigational intent of the user of a walker, based on measuring forces and moments applied to the walker’s handles. While there are many types of “intent ” that could be inferred for a given user action, the experiments conducted here focused on the determining user’s navigational intent, i.e. their desired heading. Our experiments used two 6-DOF force/ moment sensors on the walker’s handles and a digital motion capture system to correlate applied force with actual motion. Preliminary results revealed that the intent to turn, represented by changes in the heading angle, highly correlates with the overall turning moment around the vertical axis as well as the side forces applied by the user. Other force/moment components reveal additional information, such as support needs. The inferred user intent will be incorporated into a passive shared steering control system for the walker. 1