Background. Functional electrical stimulation (FES) has been used to improve function in individuals with hemiparesis following stroke. An ideal functional electrical stimulation (FES) system needs an accurate mathematical model capable of designing subject and task-specific stimulation patterns. Such a model was previously developed in our laboratory and shown to predict the isometric forces produced by the quadriceps femoris muscles of able-bodied individuals and individuals with spinal cord injury in response to a wide range of clinically relevant stimulation frequencies and patterns. The aim of this study was to test our isometric muscle force model on the quadriceps femoris, ankle dorsiflexor, and ankle plantar-flexor muscles of individuals with post-stroke hemiparesis. Methods. Subjects were seated on a force dynamometer and isometric forces were measured in response to a range of stimulation frequencies (10 to 80-Hz) and 3 different patterns. Subject-specific model parameter values were obtained by fitting the measured force responses from 2 stimulation trains. The model parameters thus obtained were then used to obtain predicted forces for a range of frequencies and patterns. Predicted and measured forces were compared using intra-class correlation coefficients, r2 values, and model error relative to the physiological error (variability of measured forces). Results. Results showed excellent agreement between measured and predicted force-time responses (r2 >0.80), peak forces (ICCs>0.84), and force-time integrals (ICCs>0.82) for the quadriceps, dorsiflexor, and plantar-fexor muscles. The model error was within or below the +95% confidence interval of the physiological error for >88% comparisons between measured and predicted forces. Conclusion. Our results show that the model has potential to be incorporated as a feed-forward controller for predicting subject-specific stimulation patterns during FES.
Burkholderia cenocepacia and Burkholderia multivorans are opportunistic drug-resistant pathogens that account for the majority of Burkholderia cepacia complex infections in cystic fibrosis patients and also infect other immunocompromised individuals. While they share similar genetic compositions, B. cenocepacia and B. multivorans exhibit important differences in pathogenesis. We have developed reconciled genome-scale metabolic network reconstructions of B. cenocepacia J2315 and B. multivorans ATCC 17616 in parallel (designated iPY1537 and iJB1411, respectively) to compare metabolic abilities and contextualize genetic differences between species. The reconstructions capture the metabolic functions of the two species and give insight into similarities and differences in their virulence and growth capabilities. The two reconstructions have 1,437 reactions in common, and iPY1537 and iJB1411 have 67 and 36 metabolic reactions unique to each, respectively. After curating the extensive reservoir of metabolic genes in Burkholderia, we identified 6 genes essential to growth that are unique to iPY1513 and 13 genes uniquely essential to iJB1411. The reconstructions were refined and validated by comparing in silico growth predictions to in vitro growth capabilities of B. cenocepacia J2315, B. cenocepacia K56-2, and B. multivorans ATCC 17616 on 104 carbon sources. Overall, we identified functional pathways that indicate B. cenocepacia can produce a wider a rray of virulence factors compared to B. multivorans, which supports the clinical observation that B. cenocepacia is more virulent than B. multivorans. The reconciled reconstructions provide a framework for generating and testing hypotheses on the metabolic and virulence capabilities of these two related emerging pathogens.
Objectives: Gait training interventions that target paretic propulsion induce improvements in walking speed and function in individuals post-stroke. Previously, we demonstrated that able-bodied individuals increase propulsion unilaterally when provided real-time biofeedback targeting anterior ground reaction forces (AGRF). The purpose of this study was to, for the first time, investigate short-term effects of real-time AGRF gait biofeedback training on post-stroke gait. Methods: Nine individuals with post-stroke hemiparesis (6 females, age = 54 ± 12.4 years 39.2 ± 24.4 months post-stroke) completed three 6-minute training bouts on an instrumented treadmill. During training, visual and auditory biofeedback were provided to increase paretic AGRF during terminal stance. Gait biomechanics were evaluated before training, and during retention tests conducted 2, 15, and 30 minutes post-training. Primary dependent variables were paretic and non-paretic peak AGRF; secondary variables included paretic and non-paretic peak trailing limb angle, plantarflexor moment, and step length. In addition to evaluating the effects of biofeedback training on these dependent variables, we compared effects of a 6-minute biofeedback training bout to a non-biofeedback control condition. Results: Compared to pre-training, significantly greater paretic peak AGRFs were generated during the 2, 15, and 30-minute retention tests conducted after the 18-minute biofeedback training session. Biofeedback training induced no significant effects on the non-paretic leg. Comparison of a 6-minute biofeedback training bout with a speed-matched control bout without biofeedback demonstrated a main effect for training type, with greater peak AGRF generation during biofeedback. Discussion: Our results suggest that AGRF biofeedback may be a feasible and promising gait training strategy to target propulsive deficits in individuals post-stroke.
The ultimate goal of Fontan surgical planning is to provide additional insights into the clinical decision-making process. In its current state, surgical planning offers an accurate hemodynamic assessment of the pre-operative condition, provides anatomical constraints for potential surgical options, and produces decent post-operative predictions if boundary conditions are similar enough between the pre-operative and post-operative states. Moving forward, validation with post-operative data is a necessary step in order to assess the accuracy of surgical planning and determine which methodological improvements are needed. Future efforts to automate the surgical planning process will reduce the individual expertise needed and encourage use in the clinic by clinicians. As post-operative physiologic predictions improve, Fontan surgical planning will become an more effective tool to accurately model patient-specific hemodynamics.
Purpose: To apply cross-correlation delay (XCD) analysis to myocardial phase contrast magnetic resonance (PCMR) tissue velocity data and to compare XCD to three established "time-to-peak" dyssynchrony parameters. Materials and Methods: Myocardial tissue velocity was acquired using PCMR in 10 healthy volunteers (negative controls) and 10 heart failure patients who met criteria for cardiac resynchronization therapy (positive controls). All dyssynchrony parameters were computed from PCMR velocity curves. Sensitivity, specificity, and receiver operator curve (ROC) analysis for separating positive and negative controls were computed for each dyssynchrony parameter. Results: XCD had higher sensitivity (90%) and specificity (100%) for discriminating between normal and patient groups than any of the time-to-peak dyssynchrony parameters. ROC analysis showed that XCD was the best parameter for separating the positive and negative control groups. Conclusion:XCD is superior to time-to-peak dyssynchrony parameters for discriminating between subjects with and without dyssynchrony and may aid in the selection of patients for cardiac resynchronization therapy.
Complete atrioventricular block (CAVB) is a life-threatening arrhythmia. A small animal model of chronic CAVB that properly reflects clinical indices of bradycardia would accelerate the understanding of disease progression and pathophysiology, and the development of therapeutic strategies. We sought to develop a surgical model of CAVB in adult rats, which could recapitulate structural remodeling and arrhythmogenicity expected in chronic CAVB. Upon right thoracotomy, we delivered electrosurgical energy subepicardially via a thin needle into the atrioventricular node (AVN) region of adult rats to create complete AV block. The chronic CAVB animals developed dilated and hypertrophied ventricles with preserved systolic functions due to compensatory hemodynamic remodeling. Ventricular tachyarrhythmias, which are difficult to induce in the healthy rodent heart, could be induced upon programmed electrical stimulation in chronic CAVB rats and worsened when combined with β-adrenergic stimulation. Focal somatic gene transfer of TBX18 to the left ventricular apex in the CAVB rats resulted in ectopic ventricular beats within days, achieving a de novo ventricular rate faster than the slow atrioventricular (AV) junctional escape rhythm observed in control CAVB animals. The model offers new opportunities to test therapeutic approaches to treat chronic and severe CAVB which have previously only been testable in large animal models.
Physiological, behavioral, and psychological changes associated with neuropsychiatric illness are reflected in several related signals, including actigraphy, location, word sentiment, voice tone, social activity, heart rate, and responses to standardized questionnaires. These signals can be passively monitored using sensors in smartphones, wearable accelerometers, Holter monitors, and multimodal sensing approaches that fuse multiple data types. Connection of these devices to the internet has made large scale studies feasible and is enabling a revolution in neuropsychiatric monitoring. Currently, evaluation and diagnosis of neuropsychiatric disorders relies on clinical visits, which are infrequent and out of the context of a patient's home environment. Moreover, the demand for clinical care far exceeds the supply of providers. The growing prevalence of context-aware and physiologically relevant digital sensors in consumer technology could help address these challenges, enable objective indexing of patient severity, and inform rapid adjustment of treatment in real-time. Here we review recent studies utilizing such sensors in the context of neuropsychiatric illnesses including stress and depression, bipolar disorder, schizophrenia, post traumatic stress disorder, Alzheimer's disease, and Parkinson's disease.
Cardiovascular simulations have great potential as a clinical tool for planning and evaluating patient-specific treatment strategies for those suffering from congenital heart diseases, specifically Fontan patients. However, several bottlenecks have delayed wider deployment of the simulations for clinical use; the main obstacle is simulation cost. Currently, time-averaged clinical flow measurements are utilized as numerical boundary conditions (BCs) in order to reduce the computational power and time needed to offer surgical planning within a clinical time frame. Nevertheless, pulsatile blood flow is observed in vivo, and its significant impact on numerical simulations has been demonstrated. Therefore, it is imperative to carry out a comprehensive study analyzing the sensitivity of using time-averaged BCs. In this study, sensitivity is evaluated based on the discrepancies between hemodynamic metrics calculated using time-averaged and pulsatile BCs; smaller discrepancies indicate less sensitivity. The current study incorporates a comparison between 3D patient-specific CFD simulations using both the time-averaged and pulsatile BCs for 101 Fontan patients. The sensitivity analysis involves two clinically important hemodynamic metrics: hepatic flow distribution (HFD) and indexed power loss (iPL). Paired demographic group comparisons revealed that HFD sensitivity is significantly different between single and bilateral superior vena cava cohorts but no other demographic discrepancies were observed for HFD or iPL. Multivariate regression analyses show that the best predictors for sensitivity involve flow pulsatilities, time-averaged flow rates, and geometric characteristics of the Fontan connection. These predictors provide patient-specific guidelines to determine the effectiveness of analyzing patient-specific surgical options with time-averaged BCs within a clinical time frame.
by
Xiaoya Guo;
Jian Zhu;
Akiko Maehara;
David Monoly;
Habib Samady;
Liang Wang;
Kristen L. Billiar;
Jie Zheng;
Chun Yang;
Don P Giddens;
Gary S. Mintz;
Dalin Tang
Computational models have been used to calculate plaque stress and strain for plaque progression and rupture investigations. An intravascular ultrasound (IVUS)-based modeling approach is proposed to quantify in vivo vessel material properties for more accurate stress/strain calculations. In vivo Cine IVUS and VH-IVUS coronary plaque data were acquired from one patient with informed consent obtained. Cine IVUS data and 3D thin-slice models with axial stretch were used to determine patient-specific vessel material properties. Twenty full 3D fluid–structure interaction models with ex vivo and in vivo material properties and various axial and circumferential shrink combinations were constructed to investigate the material stiffness impact on stress/strain calculations. The approximate circumferential Young’s modulus over stretch ratio interval [1.0, 1.1] for an ex vivo human plaque sample and two slices (S6 and S18) from our IVUS data were 1631, 641, and 346 kPa, respectively. Average lumen stress/strain values from models using ex vivo, S6 and S18 materials with 5 % axial shrink and proper circumferential shrink were 72.76, 81.37, 101.84 kPa and 0.0668, 0.1046, and 0.1489, respectively. The average cap strain values from S18 material models were 150–180 % higher than those from the ex vivo material models. The corresponding percentages for the average cap stress values were 50–75 %. Dropping axial and circumferential shrink consideration led to stress and strain over-estimations. In vivo vessel material properties may be considerably softer than those from ex vivo data. Material stiffness variations may cause 50–75 % stress and 150–180 % strain variations.