ABSTRACT
OBJECTIVES: We have previously shown in experimental settings that a leaflet foldoplasty device reduces redundant leaflet area to re-establish mitral valve (MV) coaptation. The current study investigates the in vivo device retention and functional durability following foldoplasty. METHODS: The prototype is of superelastic nitinol formed into a 3-dimensional shape. It is unfolded to engage a specified area of leaflet tissue and then folded to exclude this tissue from the coaptation surface. Design modifications were made and tested in benchtop studies to determine the optimal design for durable retention within the leaflet. To evaluate in vivo performance, posterior leaflet chordae were severed in Yorkshire pigs to produce complete posterior leaflet prolapse and severe mitral regurgitation. Design modifications were then used for MV repair. Five animals that underwent repair using the optimal design were observed for 2 weeks postoperative to evaluate the functional result and implant retention. RESULTS: Device position and orientation were maintained at 2 weeks while preserving the functional MV repair in all 5 animals. Coaptation height was 5.5 ± 1.5 mm, which was not significantly different from a baseline of 4.9 ± 0.8 mm. The degree of leaflet excursion was 41.0 ± 16.0 compared to a baseline of 58.7 ± 27.5. CONCLUSIONS: Device foldoplasty is a new concept for MV repair based on the reduction of redundant leaflet tissue area. This study demonstrates the feasibility of safe maintenance of this repair without early dislodgement or embolization.
Subject(s)
Cardiac Surgical Procedures , Mitral Valve Insufficiency , Mitral Valve Prolapse , Animals , Cardiac Surgical Procedures/methods , Feasibility Studies , Mitral Valve/diagnostic imaging , Mitral Valve/surgery , Mitral Valve Insufficiency/diagnostic imaging , Mitral Valve Insufficiency/surgery , Mitral Valve Prolapse/surgery , SwineABSTRACT
PURPOSE: In clinical practice, many patients with right heart failure (RHF) have elevated pulmonary artery pressures and increased afterload on the right ventricle (RV). In this study, we evaluated the feasibility of RV augmentation using a soft robotic right ventricular assist device (SRVAD), in cases of increased RV afterload. METHODS: In nine Yorkshire swine of 65-80 kg, a pulmonary artery band was placed to cause RHF and maintained in place to simulate an ongoing elevated afterload on the RV. The SRVAD was actuated in synchrony with the ventricle to augment native RV output for up to one hour. Hemodynamic parameters during SRVAD actuation were compared to baseline and RHF levels. RESULTS: Median RV cardiac index (CI) was 1.43 (IQR, 1.37-1.80) L/min/m2 and 1.26 (IQR 1.05-1.57) L/min/m2 at first and second baseline. Upon PA banding RV CI fell to a median of 0.79 (IQR 0.63-1.04) L/min/m2. Device actuation improved RV CI to a median of 0.87 (IQR 0.78-1.01), 0.85 (IQR 0.64-1.59) and 1.11 (IQR 0.67-1.48) L/min/m2 at 5 min (p = 0.114), 30 min (p = 0.013) and 60 (p = 0.033) minutes respectively. Statistical GEE analysis showed that lower grade of tricuspid regurgitation at time of RHF (p = 0.046), a lower diastolic pressure at RHF (p = 0.019) and lower mean arterial pressure at RHF (p = 0.024) were significantly associated with higher SRVAD effectiveness. CONCLUSIONS: Short-term augmentation of RV function using SRVAD is feasible even in cases of elevated RV afterload. Moderate or severe tricuspid regurgitation were associated with reduced device effectiveness.
Subject(s)
Heart Failure , Robotics , Tricuspid Valve Insufficiency , Animals , Heart Failure/therapy , Heart Ventricles/surgery , Humans , Pulmonary Artery/surgery , Swine , Tricuspid Valve/diagnostic imaging , Tricuspid Valve/surgery , Tricuspid Valve Insufficiency/diagnostic imaging , Tricuspid Valve Insufficiency/surgeryABSTRACT
The increasingly ageing population and the tendency to live alone have led science and engineering researchers to search for health care solutions. In the COVID 19 pandemic, the elderly have been seriously affected in addition to suffering from isolation and its associated and psychological consequences. This paper provides an overview of the RobWell (Robotic-based Well-Being Monitoring and Coaching System for the Elderly in their Daily Activities) system. It is a system focused on the field of artificial intelligence for mood prediction and coaching. This paper presents a general overview of the initially proposed system as well as the preliminary results related to the home automation subsystem, autonomous robot navigation and mood estimation through machine learning prior to the final system integration, which will be discussed in future works. The main goal is to improve their mental well-being during their daily household activities. The system is composed of ambient intelligence with intelligent sensors, actuators and a robotic platform that interacts with the user. A test smart home system was set up in which the sensors, actuators and robotic platform were integrated and tested. For artificial intelligence applied to mood prediction, we used machine learning to classify several physiological signals into different moods. In robotics, it was concluded that the ROS autonomous navigation stack and its autodocking algorithm were not reliable enough for this task, while the robot's autonomy was sufficient. Semantic navigation, artificial intelligence and computer vision alternatives are being sought.
Subject(s)
COVID-19 , Mentoring , Robotics , Aged , Artificial Intelligence , Humans , SARS-CoV-2ABSTRACT
Left ventricular failure is strongly associated with secondary mitral valve regurgitation. Implantable soft robotic devices are an emerging technology that enables augmentation of a native function of a target tissue. We demonstrate the ability of a novel soft robotic ventricular assist device to dynamically augment left ventricular contraction, provide native pulsatile flow, simultaneously reshape the mitral valve apparatus, and eliminate the associated regurgitation in an Short-term large animal model of acute left ventricular systolic dysfunction.
ABSTRACT
PURPOSE: Ocular surgery, ear, nose and throat surgery and neurosurgery are typical types of microsurgery. A versatile training platform can assist microsurgical skills development and accelerate the uptake of robot-assisted microsurgery (RAMS). However, the currently available platforms are mainly designed for macro-scale minimally invasive surgery. There is a need to develop a dedicated microsurgical robot research platform for both research and clinical training. METHODS: A microsurgical robot research platform (MRRP) is introduced in this paper. The hardware system includes a slave robot with bimanual manipulators, two master controllers and a vision system. It is flexible to support multiple microsurgical tools. The software architecture is developed based on the robot operating system, which is extensible at high-level control. The selection of master-slave mapping strategy was explored, while comparisons were made between different interfaces. RESULTS: Experimental verification was conducted based on two microsurgical tasks for training evaluation, i.e. trajectory following and targeting. User study results indicated that the proposed hybrid interface is more effective than the traditional approach in terms of frequency of clutching, task completion time and ease of control. CONCLUSION: Results indicated that the MRRP can be utilized for microsurgical skills training, since motion kinematic data and vision data can provide objective means of verification and scoring. The proposed system can further be used for verifying high-level control algorithms and task automation for RAMS research.
Subject(s)
Algorithms , Biomedical Research , Education, Medical, Graduate/methods , Microsurgery/education , Robotics/education , Surgery, Computer-Assisted/education , Equipment Design , Humans , SoftwareABSTRACT
We present an intelligent wearable system to monitor and predict mood states of elderly people during their daily life activities. Our system is composed of a wristband to record different physiological activities together with a mobile app for ecological momentary assessment (EMA). Machine learning is used to train a classifier to automatically predict different mood states based on the smart band only. Our approach shows promising results on mood accuracy and provides results comparable with the state of the art in the specific detection of happiness and activeness.
Subject(s)
Affect , Mobile Applications , Data Collection , Ecological Momentary AssessmentABSTRACT
Soft robotic devices have significant potential for medical device applications that warrant safe synergistic interaction with humans. This article describes the optimization of an implantable soft robotic system for heart failure whereby soft actuators wrapped around the ventricles are programmed to contract and relax in synchrony with the beating heart. Elastic elements integrated into the soft actuators provide recoiling function so as to aid refilling during the diastolic phase of the cardiac cycle. Improved synchronization with the biological system is achieved by incorporating the native ventricular pressure into the control system to trigger assistance and synchronize the device with the heart. A three-state electro-pneumatic valve configuration allows the actuators to contract at different rates to vary contraction patterns. An in vivo study was performed to test three hypotheses relating to mechanical coupling and temporal synchronization of the actuators and heart. First, that adhesion of the actuators to the ventricles improves cardiac output. Second, that there is a contraction-relaxation ratio of the actuators which generates optimal cardiac output. Third, that the rate of actuator contraction is a factor in cardiac output.
Subject(s)
Heart Failure/therapy , Heart-Assist Devices , Heart/physiology , Robotics/instrumentation , Animals , Biomechanical Phenomena , Biomedical Engineering , Cardiac Output , Disease Models, Animal , Heart Failure/physiopathology , Humans , Myocardial Contraction , SwineABSTRACT
Previous soft robotic ventricular assist devices have generally targeted biventricular heart failure and have not engaged the interventricular septum that plays a critical role in blood ejection from the ventricle. We propose implantable soft robotic devices to augment cardiac function in isolated left or right heart failure by applying rhythmic loading to either ventricle. Our devices anchor to the interventricular septum and apply forces to the free wall of the ventricle to cause approximation of the septum and free wall in systole and assist with recoil in diastole. Physiological sensing of the native hemodynamics enables organ-in-the-loop control of these robotic implants for fully autonomous augmentation of heart function. The devices are implanted on the beating heart under echocardiography guidance. We demonstrate the concept on both the right and the left ventricles through in vivo studies in a porcine model. Different heart failure models were used to demonstrate device function across a spectrum of hemodynamic conditions associated with right and left heart failure. These acute in vivo studies demonstrate recovery of blood flow and pressure from the baseline heart failure conditions. Significant reductions in diastolic ventricle pressure were also observed, demonstrating improved filling of the ventricles during diastole, which enables sustainable cardiac output.