National trends in the endovascular and surgical treatment of idiopathic intracranial hypertension.

BACKGROUND: The pattern of surgical treatments for Idiopathic Intracranial Hypertension (IIH) in the United States is not well-studied, specifically the trend of utilizing endovascular venous stenting (EVS) as an emerging technique. METHODS: In this cross-sectional study, we aimed to explore the national trend of utilizing different procedures for the treatment of IIH including EVS, Optic Nerve Sheath Fenestration (ONSF), and CSF Shunting, with a focus on novel endovascular procedures. Moreover, we explored rates of 90-day readmission and length of hospital stay following different procedures, besides the effects of sociodemographic and clinical parameters on procedure choice. RESULTS: 36,437 IIH patients were identified from records between 2010 and 2018. Those in the EVS group were 29 years old on average, and 93.4 % were female. Large academic hospital setting was independently associated with higher EVS utilization, while other factors were not predictive of procedure choice. The proportion of EVS use in IIH hospitalizations increased significantly from 2010 to 2018 (P < 0.001), while there was a relative decline in the frequency of shunting procedures (P = 0.001), with ONSF utilization remaining stable (P = 0.39). The rate of 90-day readmission and length of hospital stay were considerably lower following EVS compared to other procedures (Ps < 0.001). CONCLUSION: This study presents novel population-level data on national trends in the frequency and outcome of EVS for IIH therapy. EVS was associated with shorter length of hospital stays and fewer readmission rates. In addition, a continuous increase in venous stenting compared to other procedures suggests an increasing role for endovascular therapies in IIH.

Internet-Enabled Behaviors in Older Adults During the Pandemic: Patterns of Use, Psychosocial Impacts, and Plans for Continued Utilization.

In response to social distancing measures during the COVID-19 pandemic, there was a need to increase the frequency of internet enabled behaviors (IEBs). To date, little is known about how the pandemic impacted IEBs in older adults, a population that has historically been linked to lower digital literacy and utilization. We administered an online survey between April and July 2021 to 298 adults who were over age 50 (mean age = 73 years; 93.5% non-Hispanic white; 94% smart phone owners; 83.5% retired). Older adults self-reported IEBs for social, shopping, medical, and leisure activities during the pandemic, plans for continued use of these behaviors, and completed measures of psychosocial functioning. 66.8% of respondents reported an overall increase in IEBs during the pandemic, most notably for online meeting attendance. More frequent online meeting use was associated with less depression (r = -0.12, p = .04) and less loneliness (r = -0.14, p = .02). With regard to plans for continued use, 82.5% of the sample reported at least one IEB (M = 2.18, SD = 1.65) that they increased during the pandemic and planned to maintain over time (e.g., online shopping for household goods). Plans for continued use were more likely in participants who used IEBs more overall during the pandemic (r = 0.56, p < .001), and who frequently sought technical support on search engines (r = 0.22, p < .001), or online video sites (r = 0.16, p = .006). In summary, IEBs during the pandemic were associated with favorable psychosocial functioning and expectations for continued use in this sample of predominantly white older adults who had some baseline technological familiarity.

Digital Methods for Performing Daily Tasks Among Older Adults: An Initial Report of Frequency of Use and Perceived Utility.

OBJECTIVE: Digital technologies permit new ways of performing instrumental activities of daily living (iADLs) for older adults, but these approaches are not usually considered in existing iADL measures. The current study investigated how a sample of older adults report using digital versus analog approaches for iADLs. METHOD: 248 older adults completed the Digital and Analog Daily Activities Survey, a newly developed measure of how an individual performs financial, navigation, medication, and other iADLs. RESULTS: The majority of participants reported regularly using digital methods for some iADLs, such as paying bills (67.7%) and using GPS (67.7%). Low digital adopters were older than high adopters (F(2, 245) = 12.24, p < .001), but otherwise the groups did not differ in terms of gender, years of education, or history of neurological disorders. Participants who used digital methods relatively more than analog methods reported greater levels of satisfaction with their approach and fewer daily errors. CONCLUSIONS: Many older adults have adopted digital technologies for supporting daily tasks, which suggests limitations to the validity of current iADL assessments. By capitalizing on existing habits and enriching environments with new technologies, there are opportunities to promote technological reserve in older adults in a manner that sustains daily functioning.

Designing an interprofessional dementia specialty clinic: Conceptualization and evaluation of a patient-centered model.

The need for blueprints to design specialty care interprofessional collaboration (IPC) models is urgent, given the expanding aging population and current challenges in dementia diagnosis and treatment. We describe key steps creating an interprofessional outpatient dementia specialty clinic, efforts to sustain the model, and evaluation of interprofessional effectiveness and clinician satisfaction. The conception for the Comprehensive Memory Center was informed by qualitative research methodologies including focus groups, interviews, and literature reviews. Quantitative evaluation included satisfaction surveys and team effectiveness measures. The IPC model diverges from typical dementia practices through its interprofessional team, visit structure, approach to decision-making, in-house services, and community collaborations. Team retreats and workshops helped build clinician knowledge of interprofessional values and practices to sustain the IPC model. In the first 3.5 years, we served nearly 750 patients and their caregivers. Team evaluation results revealed that increased access to consultation and sharing the workload and emotional burden were beneficial. The majority of team members preferred the IPC model to traditional models of clinical care.

Technology use and subjective cognitive concerns in older adults.

OBJECTIVES: How technology impacts the day to day cognitive functioning of older adults is a matter of some debate. On the one hand, the use of technologies such as smartphones and social media, may lead to more subjective cognitive concerns (SCC) by promoting distractibility and reliance on devices to perform memory tasks. However, continued digital engagement in older adults may also be related to better cognitive functioning. Given these competing viewpoints, our study evaluated if frequency of digital device use was associated with greater or less subjective cognitive concerns. METHOD: Participants were 219 adults over the age of 65 (mean age =75 years) who had internet access. Measures assessing frequency of digital device use along with SCC were administered. Hierarchical multiple regression was used to gage association between frequency of device use and SCC, controlling for relevant demographic and lifestyle factors. RESULTS: Increased frequency of digital device use was associated with less SCC, over and above the influence of demographic factors, across cognitive (but especially in executive) domains. This effect was observed for general device usage, with no statistically significant associations were observed between texting/video call, social media use and SCC. DISCUSSION: Results were broadly consistent with the technological reserve hypothesis in that digital engagement was associated with better experienced cognitive functioning in older adults. While device use may contribute to distractibility in certain cases, the current results add to a burgeoning literature that digital engagement may be a protective factor for cognitive changes with age.

Automatic Segmentation and Quantitative Assessment of Stroke Lesions on MR Images.

Lesion studies are crucial in establishing brain-behavior relationships, and accurately segmenting the lesion represents the first step in achieving this. Manual lesion segmentation is the gold standard for chronic strokes. However, it is labor-intensive, subject to bias, and limits sample size. Therefore, our objective is to develop an automatic segmentation algorithm for chronic stroke lesions on T1-weighted MR images. Methods: To train our model, we utilized an open-source dataset: ATLAS v2.0 (Anatomical Tracings of Lesions After Stroke). We partitioned the dataset of 655 T1 images with manual segmentation labels into five subsets and performed a 5-fold cross-validation to avoid overfitting of the model. We used a deep neural network (DNN) architecture for model training. Results: To evaluate the model performance, we used three metrics that pertain to diverse aspects of volumetric segmentation, including shape, location, and size. The Dice similarity coefficient (DSC) compares the spatial overlap between manual and machine segmentation. The average DSC was 0.65 (0.61−0.67; 95% bootstrapped CI). Average symmetric surface distance (ASSD) measures contour distances between the two segmentations. ASSD between manual and automatic segmentation was 12 mm. Finally, we compared the total lesion volumes and the Pearson correlation coefficient (ρ) between the manual and automatically segmented lesion volumes, which was 0.97 (p-value < 0.001). Conclusions: We present the first automated segmentation model trained on a large multicentric dataset. This model will enable automated on-demand processing of MRI scans and quantitative chronic stroke lesion assessment.

Prospective Observational Cohort Study of Tenecteplase Versus Alteplase in Routine Clinical Practice.

BACKGROUND: A 10-hospital regional network transitioned to tenecteplase as the standard of care stroke thrombolytic in September 2019 because of potential workflow advantages and reported noninferior clinical outcomes relative to alteplase in meta-analyses of randomized trials. We assessed whether tenecteplase use in routine clinical practice reduced thrombolytic workflow times with noninferior clinical outcomes. METHODS: We designed a prospective registry-based observational, sequential cohort comparison of tenecteplase- (n=234) to alteplase-treated (n=354) stroke patients. We hypothesized: (1) an increase in the proportion of patients meeting target times for target door-to-needle time and transfer door-in-door-out time, and (2) noninferior favorable (discharge to home with independent ambulation) and unfavorable (symptomatic intracranial hemorrhage, in-hospital mortality or discharge to hospice) in the tenecteplase group. Total hospital cost associated with each treatment was also compared. RESULTS: Target door-to-needle time within 45 minutes for all patients was superior for tenecteplase, 41% versus 29%; adjusted odds ratio, 1.85 (95% CI, 1.27-2.71); P=0.001; 58% versus 41% by Get With The Guidelines criteria. Target door-in-door-out time within 90 minutes was superior for tenecteplase 37% (15/43) versus 14% (9/65); adjusted odds ratio, 3.62 (95% CI, 1.30-10.74); P=0.02. Favorable outcome for tenecteplase fell within the 6.5% noninferiority margin; adjusted odds ratio, 1.26 (95% CI, 0.89-1.80). Unfavorable outcome was less for tenecteplase, 7.3% versus 11.9%, adjusted odds ratio, 0.77 (95% CI, 0.42-1.37) but did not fall within the prespecified 1% noninferior boundary. Net benefit (%favorable-%unfavorable) was greater for the tenecteplase sample: 37% versus 27%. P=0.02. Median cost per hospital encounter was less for tenecteplase cases ($13 382 versus $15 841; P<0.001). CONCLUSIONS: Switching to tenecteplase in routine clinical practice in a 10-hospital network was associated with shorter door-to-needle time and door-in-door-out times, noninferior favorable clinical outcomes at discharge, and reduced hospital costs. Evaluation in larger, multicenter cohorts is recommended to determine if these observations generalize.

Optimizing Emergency Stroke Transport Strategies Using Physiological Models.

BACKGROUND AND PURPOSE: The criteria for choosing between drip and ship and mothership transport strategies in emergency stroke care is widely debated. Although existing data-driven probability models can inform transport decision-making at an epidemiological level, we propose a novel mathematical, physiologically derived framework that provides insight into how patient characteristics underlying infarct core growth influence these decisions. METHODS: We represent the physiology of time-dependent infarct core growth within an ischemic penumbra as an exponential function with consideration to rate-determining collateral blood flow. Monte Carlo methods generate distributions of infarct core volumes, which are translated to distributions of 90-day modified Rankin Scale scores. We apply the model to a stroke network that serves rural Bastrop County and urban Travis County by simulating transport strategies from thousands of potential patient pickup locations. In every pickup location, the simulation yields a distribution of outcomes corresponding to each transport strategy. A 2-sample Kolmogorov-Smirnov test and Student t test determine which transport strategy provides a significantly better probability of a good outcome for a given pickup location in each respective county (P<0.01). RESULTS: In Travis County, drip and ship provides significantly better probabilities of a good outcome in 24.0% of the pickup locations, while 59.8% favor mothership. In Bastrop County, 11.3% of the pickup locations favor drip and ship, while only 7.1% favor mothership. The remaining pickup locations in each county are not statistically significant in either direction. We also reveal how differing rates of infarct core growth, the application of bypass policies, and the use of large vessel occlusion field tests impact these results. CONCLUSIONS: Modeling stroke physiology enables the use of clinically relevant metrics for determining comparative significance between drip and ship and mothership in a given geography. This formalism can help understand and inform emergency medical service transport decision-making, as well as regional bypass policies.

Predicting apneic events in preterm infants using cardio-respiratory and movement features.

BACKGROUND AND OBJECTIVE: Preterm neonates are prone to episodes of apnea, bradycardia and hypoxia (ABH) that can lead to neurological morbidities or even death. There is broad interest in developing methods for real-time prediction of ABH events to inform interventions that prevent or reduce their incidence and severity. Using advances in machine learning methods, this study develops an algorithm to predict ABH events. METHODS: Following previous studies showing that respiratory instabilities are closely associated with bouts of movement, we present a modeling framework that can predict ABH events using both movement and cardio-respiratory features derived from routine clinical recordings. In 10 preterm infants, movement onsets and durations were estimated with a wavelet-based algorithm that quantified artifactual distortions of the photoplethysmogram signal. For prediction, cardio-respiratory features were created from time-delayed correlations of inter-beat and inter-breath intervals with past values; movement features were derived from time-delayed correlations with inter-breath intervals. Gaussian Mixture Models and Logistic Regression were used to develop predictive models of apneic events. Performance of the models was evaluated with ROC curves. RESULTS: Performance of the prediction framework (mean AUC) was 0.77 ± 0.04 for 66 ABH events on training data from 7 infants. When grouped by the severity of the associated bradycardia during the ABH event, the framework was able to predict 83% and 75% of the most severe episodes in the 7-infant training set and 3-infant test set, respectively. Notably, inclusion of movement features significantly improved the predictions compared with modeling with only cardio-respiratory signals. CONCLUSIONS: Our findings suggest that recordings of movement provide important information for predicting ABH events in preterm infants, and can inform preemptive interventions designed to reduce the incidence and severity of ABH events.

Characterizing the performance of emergency medical transport time metrics in a residentially segregated community.

OBJECTIVE: To derive and characterize the performance of various metrics of emergency transport time in assessing for sociodemographic disparities in the setting of residential segregation. Secondarily to characterize racial disparities in emergency transport time of suspected stroke patients in Austin, Texas. DATA SOURCES: We used a novel dataset of 2518 unique entries with detailed spatial and temporal information on all suspected stroke transports conducted by a public emergency medical service in Central Texas between 2010 and 2018. STUDY DESIGN: We conducted one-way ANOVA tests with post-hoc pairwise t-tests to assess how mean hospital transport times varied by patient race. We also developed a spatially-independent metric of emergency transport urgency, the ratio of expected duration of self-transport to a hospital and the measured transport time by an ambulance. DATA COLLECTION/EXTRACTION: We calculated ambulance arrival and destination times using sequential temporospatial coordinates. We excluded any entries in which patient race was not recorded. We also excluded entries in which ambulances' routes did not pass within 100 m of either the patient's location or the documented hospital destination. PRINCIPAL FINDINGS: We found that mean transport time to a hospital was 2.5 min shorter for black patients compared to white patients. However, white patients' transport times to a hospital were found to be, on average, 4.1 min shorter than expected compared to 3.4 min shorter than expected for black patients. One-way ANOVA testing for the spatially-independent index of emergency transport urgency was not statistically significant, indicating that average transport time did not vary significantly across racial groups when accounting for variations in transport distance. CONCLUSIONS: Using a novel transport urgency index, we demonstrate that these findings represent race-based variation in spatial distributions rather than racial bias in emergency medical transport. These results highlight the importance of closely examining spatial distributions when utilizing temporospatial data to investigate geographically-dependent research questions.

Importance of Community Impact as the Fourth Academic Mission: A Qualitative Study.

Most US medical schools have 3 primary missions: education, research, and clinical service. Recently there have been calls for a fourth primary mission focused on improving health in their surrounding communities. To date, few medical schools have done so. To identify factors supporting and challenges to establishing a sustainable community impact mission, the authors conducted semi-structured key informant interviews with the dean, associate deans, departments chairs, and institute and center directors at a new US medical school that established a fourth "community impact" mission at its conception. Interviewees believed that it was appropriate for a community-focused tax-supported medical school to embrace community impact as a fourth mission to enhance community health outside of its hospitals and clinics. Many also felt that community impact should be an overriding framework for activities in the 3 primary missions. Achieving community impact would require creating a "learning health community" via partnerships with community organizations and linking faculty effort and funding to specific and valid measures of community health improvement. Sustainable funding would require core school funds and a broad portfolio of extramural funding. Faculty promotions with community impact as a focus would need explicit, achievable, and unique milestones. Interviewees made specific suggestions on the support and structure needed to launch and sustain this fourth mission. Establishing a fourth mission of community impact can extend medical schools' influence beyond typical health care venues to enhance the health of their communities and their residents. Doing so requires rethinking organizational structures, support, and measures of success.

Effect of spontaneous movement on respiration in preterm infants.

NEW FINDINGS: What is the central question of this study? The respiratory centres in the brainstem that control respiration receive inputs from various sources, including proprioceptors in muscles and joints and suprapontine centres, which all affect limb movements. What is the effect of spontaneous movement on respiration in preterm infants? What is the main finding and its importance? Apnoeic events tend to be preceded by movements. These activity bursts can cause respiratory instability that leads to an apnoeic event. These findings show promise that infant movements might serve as potential predictors of life-threatening apnoeic episodes, but more research is required. ABSTRACT: A common condition in preterm infants (<37 weeks' gestational age) is apnoea resulting from immaturity and instability of the respiratory system. As apnoeas are implicated in several acute and long-term complications, prediction of apnoeas may preempt their onset and subsequent complications. This study tests the hypothesis that infant movements are a predictive marker for apnoeic episodes and examines the relation between movement and respiration. Movement was detected using a wavelet algorithm applied to the photoplethysmographic signal. Respiratory activity was measured in nine infants using respiratory inductance plethysmography; in an additional eight infants, respiration and partial pressure of airway carbon dioxide ( PCO2 ) were measured by a nasal cannula with side-stream capnometry. In the first cohort, the distribution of movements before and after the onset of 370 apnoeic events was compared. Results showed that apnoeic events were associated with longer movement duration occurring before apnoea onsets compared to after. In the second cohort, respiration was analysed in relation to movement, comparing standard deviation of inter-breath intervals (IBI) before and after apnoeas. Poincaré maps of the respiratory activity quantified variability of airway PCO2 in phase space. Movement significantly increased the variability of IBI and PCO2 . Moreover, destabilization of respiration was dependent on the duration of movement. These findings support that bodily movements of the infants precede respiratory instability. Further research is warranted to explore the predictive value of movement for life-threatening events, useful for clinical management and risk stratification.

Falling off a limit cycle using phase-agnostic stimuli: Applications to clinical oscillopathies.

For over a century, physiological studies have shown that precisely timed pulses can switch off a biological oscillator. This empiric finding has shaped our mechanistic understanding of how perturbations start, stop, and reset biological oscillators and has led to treatments that suppress pathological oscillations using electrical pulses given within specified therapeutic phase windows. Here, we present evidence, using numerical simulations of models of epileptic seizures and reentrant tachycardia, that the phase window can be opened to the entire cycle using novel complex stimulus waveforms. Our results reveal that the trajectories are displaced by such phase-agnostic stimuli off the oscillator's limit cycle and corralled into a region where oscillation is suppressed, irrespective of the phase at which the stimulus was applied. Our findings suggest the need for broadening theoretical understanding of how complex perturbing waveforms interact with biological oscillators to access their arrhythmic states. In clinical practice, oscillopathies may be treated more effectively with non-traditional stimulus waveforms that obviate the need for phase specificity.

The Internal Superior Laryngeal Nerve in Humans: Evidence for Pure Sensory Function.

OBJECTIVES: To determine if the internal branch of the superior laryngeal nerve (iSLN) provides direct motor innervation to the interarytenoid muscle, a laryngeal adductor critical for airway protection. We studied the iSLN-evoked motor response in the interarytenoid and other laryngeal muscles. If the iSLN is purely sensory, there will be no detectable short latency motor response upon supramaximal stimulation, indicating the absence of a direct efferent conduction path. STUDY DESIGN: Intraoperative case series. METHODS: In seven anesthetized patients undergoing laryngectomy for unilateral laryngeal carcinoma, the iSLN of the unaffected side was electrically stimulated intraoperatively with 0.1-ms pulses of progressive intensities until supramaximal stimulation was reached. Electromyographic responses were measured in the ipsilateral interarytenoid, thyroarytenoid, and cricothyroid muscles. RESULTS: None of the subjects exhibited short-latency interarytenoid motor responses to iSLN stimulation. Supramaximal electrical stimulation of the intact iSLN evoked ipsilateral motor responses with long latencies: 18.7-38.5 ms in the interarytenoid (n = 6) and 17.8-24.9 ms in the thyroarytenoid (n = 5). Supramaximal stimulation of the recurrent laryngeal nerve evoked ipsilateral motor responses with short latencies: 1.6-3.9 ms in the interarytenoid (n = 6) and 1.6-2.7 ms in the thyroarytenoid (n = 6). CONCLUSION: The iSLN provides no functional efferent motor innervation to the interarytenoid muscles. The iSLN exclusively evokes an interarytenoid motor response via afferent activation of central neural circuits that mediate the laryngeal reflex arc. These findings suggest that the role of the iSLN in vital laryngopharyngeal functions, such as normal swallowing and protection of the airway from aspiration, is purely sensory. LEVEL OF EVIDENCE: 4 Laryngoscope, 131:E207-E211, 2021.

Falling off a limit cycle using phase-agnostic stimuli: Definitions and conceptual framework.

Nearly a half-century of biomedical research has revealed methods and mechanisms by which an oscillator with bistable limit cycle kinetics can be stopped using critical stimuli applied at a specific phase. Is it possible to construct a stimulus that stops oscillation regardless of the phase at which the stimulus is applied? Using a radial isochron clock model, we demonstrate the existence of such stimulus waveforms, which can take on highly complex shapes but with a surprisingly simple mechanism of rhythm suppression. The perturbation, initiated at any phase of the limit cycle, first corrals the oscillator to a narrow range of new phases, then drives the oscillator to its phase singularity. We further constructed a library of waveforms having different durations, each achieving phase-agnostic suppression of rhythm but with varying rates of phase corralling prior to amplitude suppression. The optimal stimulus energy to achieve phase-agnostic suppression of rhythm is dependent on the rate of phase corralling and the configuration of the phaseless set. We speculate that these results are generic and suggest the existence of stimulus waveforms that can stop the rhythm of more complex oscillators irrespective of the applied phase.

Automated movement detection reveals features of maturation in preterm infants.

Nearly 10% of all births in the United States are preterm. Preterm birth is a major risk for developmental neuromotor disorders. Early characterization of a future developmental outcome is necessary to design early interventions. However, such evaluations are currently subjective and typically happen only several months after birth. The aim of this study was to quantify movement bouts after birth and to determine if features of maturation might be characterized. Four preterm infants were continuously monitored for several months, from a few days after birth until discharge, in the Neonatal Intensive Care Unit. Movement was quantified from the photoplethysmogram using a wavelet-based algorithm. In all 4 infants, maturation was associated with a decrease (p < 0.001) in the occurrence of movement bouts ≤ 30s and an increase (p < 0.001) in longer movement bouts (> 30s). The distribution of movement durations followed a power law function with its exponent defining the characteristic of the distribution. The exponent significantly increased with post-menstrual age. Future research will test whether these maturational changes can predict developmental outcomes.Clinical Relevance- Early identification of changes in features of preterm infant movement may be useful in predicting neuromotor development and potential disorders.

Sensory dysphagia: A case series and proposed classification of an under recognized swallowing disorder.

BACKGROUND: Although sensory feedback is a vital regulator of deglutition, it is not comprehensively considered in the standard dysphagia evaluation. Difficulty swallowing secondary to sensory loss may be termed "sensory dysphagia" and may account for cases receiving diagnoses of exclusion, like functional or idiopathic dysphagia. METHODS AND RESULTS: Three cases of idiopathic dysphagia were suspected to have sensory dysphagia. The patients had (1) effortful swallowing, (2) globus sensation, and (3) aspiration. Endoscopic sensory mapping revealed laryngopharyngeal sensory loss. Despite normal laryngeal motor function during voluntary maneuvers, laryngeal closure was incomplete during swallowing. The causes of sensory loss were identified: cranial neuropathy from Chiari malformation, immune-mediated neuronopathy, and nerve damage from prior traumatic intubation. CONCLUSIONS: Sensory loss may cause dysphagia without primary motor dysfunction. Sensory dysphagia should be classified as a distinct form of swallowing motility disorder to improve diagnosis. Increasing awareness and developing appropriate assessment tools may advance dysphagia care.

Applying Machine Learning Algorithms for Automatic Detection of Swallowing from Sound.

Despite the severe consequences of dysfunctional swallowing, there is no simple method of monitoring swallowing outside of clinical settings. People who cannot swallow cannot eat safely, resulting in profound changes in quality of life and risk of death from aspiration pneumonia. A non-invasive swallowing detector may have widespread impact in both clinical care and research. Detection of swallowing from laryngeal sounds could become an ideal assessment tool because sounds are simple to record, quantifiable, and amenable to software analysis. The focus of this paper is to achieve high accuracy binary swallowing detection from sound recordings. A dataset with 2500 swallow sound samples and 1700 mixed laryngeal noise samples from 15 healthy adults was used to train and test three supervised machine learning algorithms. A decision tree, support vector machine (SVM), and neural network trained with the scaled conjugate gradient (SCG) method had areas under the receiver operating characteristic (ROC) curve of 0.970, 0.961, and 0.971 and average accuracies of 93.2 percent, 86.2 percent, and 93.7 percent respectively. While further work needs to be done to further optimize these algorithms and validate their efficacy, these initial results suggest machine learning strategies may be helpful to improve accuracy of swallowing detection.

Optimizing stimulus waveforms for electroceuticals.

There has been a growing interest in the use of electrical stimulation as a therapy across diverse medical conditions. Most electroceutical devices use simple waveforms, for example sinusoidal or rectangular biphasic pulses. Clinicians empirically tune the waveform parameters (e.g. amplitude, frequency) without altering the fundamental shape of the stimulus. In this article, we review computational strategies that have been used to optimize the shape of stimulus waveforms in order to improve clinical outcomes, and we discuss potential directions for future exploration.

Quantifying Movement in Preterm Infants Using Photoplethysmography.

Long-term recordings of movement in preterm infants might reveal important clinical information. However, measurement of movement is limited because of time-consuming and subjective analysis of video or reluctance to attach additional sensors to the infant. We evaluated whether photoplethysmogram (PPG), routinely used for oximetry in preterm infants in the neonatal intensive care unit (NICU), can provide reliable long-term measurements of movement. In 18 infants [mean post-conceptional age (PCA) 31.10 weeks, range 29-34.29 weeks], we designed and tested a wavelet-based algorithm that detects movement signals from the PPG. The algorithm's performance was optimized relative to subjective assessments of movement using video and accelerometers attached to two limbs and force sensors embedded within the mattress (five infants, three raters). We then applied the optimized algorithm to infants receiving routine care in the NICU without additional sensors. The algorithm revealed a decline in brief movements (< 5 s) with increasing PCA (13 infants, r = - 0.87, p < 0.001, PCA range 27.3-33.9 weeks). Our findings suggest that quantitative relationships between motor activity and clinical outcomes in preterm infants can be studied using routine photoplethysmography.