Implantable brain stimulation devices continue to be developed to treat and monitor brain conditions. As the complexity of these devices grows to include adaptive neuromodulation therapy, validating the operation and verifying the correctness of these systems becomes more complicated. The new complexities lie in the functioning of the device being dependent on the interaction with the patient and environmental factors such as noise and artifacts. Here, we present a hardware-in-the-loop (HIL) testing framework that employs computational models of pathological neural dynamics to test adaptive deep brain stimulation (DBS) devices prior to animal or human testing. A brain stimulation and recording electrode array is placed in the saline tank and connected to an adaptive neuromodulation system that measures and processes the synthetic signals and delivers stimulation back into the saline tank. A data acquisition system is used to detect the stimulation and provide feedback to the computational model in order to simulate the effects of stimulation on the neural dynamics. In this study, we used real-time computational models to emulate the dynamics of epileptic seizures observed in the anterior nucleus of the thalamus (ANT) in epilepsy patients and beta band (11-35 Hz) oscillations observed in the subthalamic nucleus (STN) of Parkinson's disease (PD) patients. These models simulated neuronal responses to electrical stimulation pulses and the saline tank tested hardware interactions between the detection algorithms and stimulation interference. We tested and validated the operation of adaptive DBS algorithms for seizure and beta band power suppression embedded in an implantable DBS system (Medtronic Summit RC+S). This study highlights the utility of the proposed hardware-in-the-loop framework to systematically test the adaptive DBS systems in the presence of system aggressors such as environmental noise and stimulation-induced electrical artifacts. This testing procedure can help ensure correctness and robustness of adaptive DBS devices prior to animal and human testing.
A pilot clinical study was conducted that compared the peripheral oxygen saturation (SpO2) targeting performance of an automatic oxygen control system with manual oxygen control, which is the standard of care for preterm and low birth weight infants on high-flow nasal cannula (HFNC). The new oxygen control device studied was used to automatically adjust the fraction of inspired oxygen (FiO2) according to a desired SpO2 target setpoint and measured feedback signals including the SpO2 and other signals. A crossover study was designed with several endpoints including the comparison of the percentage of time that the SpO2 was within the target range with the automatic oxygen control device versus manual oxygen control. Other metrics were also compared to assess the performance of the system including the number of bradycardia events. The pilot study included six patients that fit the inclusion criteria. The results showed that there were improvements in all of the measured outcomes considered including statistically significant improvements in the number of bradycardia events during the period when the automatic oxygen control device was used.
Annuloplasty ring choice and design are critical to the long-term efficacy of mitral valve (MV) repair. DynaRing is a selectively compliant annuloplasty ring composed of varying stiffness elastomer segments, a shape-set nitinol core, and a cross diameter filament. The ring provides sufficient stiffness to stabilize a diseased annulus while allowing physiological annular dynamics. Moreover, adjusting elastomer properties provides a mechanism for effectively tuning key MV metrics to specific patients. We evaluate the ring embedded in porcine valves with an ex-vivo left heart simulator and perform a 150 million cycle fatigue test via a custom oscillatory system. We present a patient-specific design approach for determining ring parameters using a finite element model optimization and patient MRI data. Ex-vivo experiment results demonstrate that motion of DynaRing closely matches literature values for healthy annuli. Findings from the patient-specific optimization establish DynaRing's ability to adjust the anterior-posterior and intercommissural diameters and saddle height by up to 8.8%, 5.6%, 19.8%, respectively, and match a wide range of patient data.