Swallowing is a physiologically complex, kinematic process that requires highly coordinated activity of numerous nerves and muscles to execute efficient transport of a bolus from the oral cavity to the stomach. Dysphagia, or a difficulty with swallowing, is a concern following lung transplantation due to the high risk of recurrent laryngeal nerve damage, required levels of life-long immunosuppression, and upper airway trauma secondary to prolonged endotracheal intubation (Pomfret, 2016). Post-operatively, repetitive aspiration events can lead to the development of Bronchiolitis Obliterans Syndrome (BOS), a major contributing factor in acute allograft rejection and long-term failure of lung allograft function. The goal of this descriptive, retrospective study is to describe the characteristics of double lung transplant (DLT) swallows through analysis of kinematic swallow durations, airway protection, and physiologic swallow impairments. These results are compared to single lung transplant (SLT) swallow characteristics and two previously published, historical normal cohorts. By explicitly describing the swallow physiology of DLT and SLT recipients, clinically significant risk factors have been identified to assist clinicians and researchers in the development and implementation of better treatment options and safer swallowing strategies post-operatively. These efforts can improve the functional lifespan of the newly transplanted organ and increase patient quality of life.

Wirelessly powered implantable medical devices require efficient power transfer through biological tissue within safety constraints on energy absorption, often in the presence of environmental variability. Accurate modeling of the tissue medium is essential to evaluate the performance and sensitivity of transcutaneous powering systems. Here, we investigate loop and dipole antenna topologies in proximity to simulated tissue models and experimental phantoms, with emphasis on representing heterogeneous tissue with functionally equivalent simplified models, and modeling variability in tissue properties for sensitivity analyses. We first present a modified phantom formulation that provides greater control over frequency-dependent properties. We then show that homogeneous phantoms have limited use at representing input impedance and energy absorption at ultrahigh operating frequency by analyzing each antenna topology in proximity to layered or homogeneous tissue across frequency. We compare loop and dipole antenna topologies in terms of specific absorption rate and impedance, and show that frequency-dependent tissue behavior must be considered even at fixed operating frequencies. Finally, we discuss the dual utility of a transmitting antenna as a resonator to detect changes in tissue properties in addition to powering an implanted device.

A vertex-varying spectral content on graphs challenges the assumption of vertex invariance and requires vertex-frequency representations for an adequate analysis. In this letter, we introduce a class of vertex-frequency energy distributions inspired by traditional time-frequency energy distributions. These newly introduced distributions do not use localization windows. Their efficiency in energy concentration is illustrated through examples.

More than five million adults in U.S. are affected by the peripheral artery disease. Current wireless stent monitors are unsuitable to use in the thigh. In this paper, wireless powering and communication with implanted stents were investigated. Specifically, we investigated the effects of thigh tissue morphology and tissue thickness variations on wireless power gain and electromagnetic safety when using skin-contact touch probe antennas. Thigh simulation models were derived from anthropometric data for the diseased population. Power gain and specific absorption rate were determined for each variation. To corroborate human model simulation results, a power-to-frequency converter was designed, benchmarked, and implanted within ex vivo porcine tissue. The experiments showed the most realistic simulations reported so far that have the best agreement with measured results. This paper indicates that touch probe powered stent systems can safely deliver significant power to an implant. This research enables frequent at-home monitoring to replace costly in-hospital quarterly check-ups.

Here we present the results of experiments involving cynomolgus macaques, in which a model of traumatic spinal cord injury (TSCI) was created by using a balloon catheter inserted into the epidural space. Prior to the creation of the lesion, we inserted an EMG recording device to facilitate measurement of tail movement and muscle activity before and after TSCI. This model is unique in that the impairment is limited to the tail: the subjects do not experience limb weakness, bladder impairment, or bowel dysfunction. In addition, 4 of the 6 subjects received a combination treatment comprising thyrotropin releasing hormone, selenium, and vitamin E after induction of experimental TSCI. The subjects tolerated the implantation of the recording device and did not experience adverse effects due the medications administered. The EMG data were transformed into a metric of volitional tail moment, which appeared to be valid measure of initial impairment and subsequent natural or treatment-related recovery. The histopathologic assessment demonstrated widespread axon loss at the site of injury and areas cephalad and caudad. Histopathology revealed evidence of continuing inflammation, with macrophage activation. The EMG data did not demonstrate evidence of a statistically significant treatment effect.

Recent developments in personal and mobile healthcare have shown promising results in term of patients' quality of life and quality of care improvements. This can be achieved through continuous monitoring of patients' physiological functions using wearable non-invasive biomedical sensors. The remote collection and processing of such data can then be used to provide rapid medical response if a problem is detected or to offer preventive measures. However, the integration of wearable sensors into wider-scale framework is still a major challenge, as real-time data collection and remote configuration capabilities must be integrated to strongly constrained devices. Here, we show how such requirements can be integrated into a multiparameter, cardiorespiratory wearable sensor and how this sensor can be integrated into wide-scale Internet-based frameworks. We thus manufactured a biomedical-grade heart rate, instantaneous heart-rate variability and respiratory sensor. The sensor was tested in real life ambulatory condition, and we showed an Internet-based proof of concept exhibiting the integration of our sensor into wide-scale healthcare frameworks. Finally, we anticipate that wearable healthcare will greatly improve patients' quality-of-life by using IoT-based wearable devices similar to the sensor developed in this paper.

Recent developments in personal and mobile healthcare have shown promising results in term of patients' quality of life and quality of care improvements. This can be achieved through continuous monitoring of patients' physiological functions using wearable non-invasive biomedical sensors. The remote collection and processing of such data can then be used to provide rapid medical response if a problem is detected or to offer preventive measures. However, the integration of wearable sensors into wider-scale framework is still a major challenge, as real-time data collection and remote configuration capabilities must be integrated to strongly constrained devices. Here, we show how such requirements can be integrated into a multiparameter, cardiorespiratory wearable sensor and how this sensor can be integrated into wide-scale Internet-based frameworks. We thus manufactured a biomedical-grade heart rate, instantaneous heart-rate variability and respiratory sensor. The sensor was tested in real life ambulatory condition, and we showed an Internet-based proof of concept exhibiting the integration of our sensor into wide-scale healthcare frameworks. Finally, we anticipate that wearable healthcare will greatly improve patients' quality-of-life by using IoT-based wearable devices similar to the sensor developed in this paper.

Objective: Up to 10% of free flap cases are compromised, and without prompt intervention, amputation and even death can occur. Hourly monitoring improves salvage rates, but the gold standard for monitoring requires experienced personnel to operate and suffers from high false-positive rates as high as 31% that result in costly and unnecessary surgeries. In this paper, we investigate free flap patency monitoring using automatic hardware-only classification systems that eliminate the need for experienced personnel. The expected flow ranges of the antegrade and retrograde veins for breast reconstruction are studied using a syringe pump to create the laminar flow seen in veins. Methods: Feature data extracted from the Doppler blood flow signals are analyzed for sensitivity, specificity, and false-positive rates. Hardware is built to perform the classification automatically in real-time and output a decision at the end of the observation period. Results: Experimental results using the hardware-only classifier for a 50 ms window size show high sensitivity (96.75%), specificity (90.20%), and low false-positive rate (9.803%). The experimental and theoretical classification results show close agreement. Conclusion: This work indicates that automatic hardware-only classifiers can eliminate the need for experienced personnel to monitor free flap patency. Significance: The hardware-only classification is amenable to a monolithic implementation and future studies should study a totally implantable wirelessly-powered blood flow classifier. The high classifier performance in a short window period indicates that duty-cycled powering can be used to extend the safe operational depth of an implant. This is particularly relevant for the difficult buried free flap applications.

Free flap surgeries require hourly monitoring to detect vascular compromise. If not caught promptly, the flap can be lost. Monitoring free flaps using the gold standard requires experienced operators to interpret blood flow signatures, which are often difficult to distinguish from background noise. Previously reported hardware-only automatic patency classification showed a high sensitivity, specificity, and a low false-positive rate, but it was demonstrated using bulky discrete electronics and a syringe pump to generate the expected flow rates. In this paper, we investigate automatic hardware-only patency classification on blood flow data collected from the bilateral femoral veins during flow and occluded states using SPICE simulations in an IBM 130-nm CMOS process with a 1-V supply voltage and a 200-ms window length. Experimental results show a very high sensitivity (99.45%), specificity (99.93%), and very low false-positive rate (0.07275%) at just 8.715 $\mu \text{A}$ . This paper shows that automatic hardware-only patency classification is effective for monitoring patency on real pig blood flow data. The demonstrated classifier’s performance makes it suitable for integration as part of a wirelessly-powered biomedical patency monitor.