Toward a Robust Estimation of Respiratory Rate From Pulse Oximeters.

GOAL: Current methods for estimating respiratory rate (RR) from the photoplethysmogram (PPG) typically fail to distinguish between periods of high- and low-quality input data, and fail to perform well on independent "validation" datasets. The lack of robustness of existing methods directly results in a lack of penetration of such systems into clinical practice. The present work proposes an alternative method to improve the robustness of the estimation of RR from the PPG. METHODS: The proposed algorithm is based on the use of multiple autoregressive models of different orders for determining the dominant respiratory frequency in the three respiratory-induced variations (frequency, amplitude, and intensity) derived from the PPG. The algorithm was tested on two different datasets comprising 95 eight-minute PPG recordings (in total) acquired from both children and adults in different clinical settings, and its performance using two window sizes (32 and 64 seconds) was compared with that of existing methods in the literature. RESULTS: The proposed method achieved comparable accuracy to existing methods in the literature, with mean absolute errors (median, 25[Formula: see text]-75[Formula: see text] percentiles for a window size of 32 seconds) of 1.5 (0.3-3.3) and 4.0 (1.8-5.5) breaths per minute (for each dataset respectively), whilst providing RR estimates for a greater proportion of windows (over 90% of the input data are kept). CONCLUSION: Increased robustness of RR estimation by the proposed method was demonstrated. SIGNIFICANCE: This work demonstrates that the use of large publicly available datasets is essential for improving the robustness of wearable-monitoring algorithms for use in clinical practice

MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III

Robust machine learning relies on access to data that can be used with standardized frameworks in important tasks and the ability to develop models whose performance can be reasonably reproduced. In machine learning for healthcare, the community faces reproducibility challenges due to a lack of publicly accessible data and a lack of standardized data processing frameworks. We present MIMIC-Extract, an open-source pipeline for transforming raw electronic health record (EHR) data for critical care patients contained in the publicly-available MIMIC-III database into dataframes that are directly usable in common machine learning pipelines. MIMIC-Extract addresses three primary challenges in making complex health records data accessible to the broader machine learning community. First, it provides standardized data processing functions, including unit conversion, outlier detection, and aggregating semantically equivalent features, thus accounting for duplication and reducing missingness. Second, it preserves the time series nature of clinical data and can be easily integrated into clinically actionable prediction tasks in machine learning for health. Finally, it is highly extensible so that other researchers with related questions can easily use the same pipeline. We demonstrate the utility of this pipeline by showcasing several benchmark tasks and baseline results

Application and Effectiveness of Telehealth to Support Severe Mental Illness Management: Systematic Review

Background: It is important that people with SMI receive early interventions to prevent mental health deterioration or relapse. Telecommunications and other technologies are increasingly used to assist healthcare delivery (‘telehealth’) , providing service users with immediate real-time information to improve the management of chronic health conditions. Telehealth has been found to be successful in improving management and symptoms across a number of health conditions, whilst also being acceptable to users. Initial findings suggest technology could improve quality of life in people with SMI. Objectives: This systematic review aimed to identify the variety of uses and efficacy of teleheal th technology for SMI. Methods: We systematically searched electronic databases from inception to March 2016 (MEDLINE, EMBASE, PsycINFO, Cochrane Central Register of Controlled Trials, AMED, He alth Techno logy Assessment, CINAHL plus and NHS EED ) for randomised controlled trials (RCTs) evaluating telehealth for adults with SMI , published in English. Additional literature was identified by searching reference lists of key articles. The articles meeting the inclusion criteria were systematically reviewed and assessed for quality and risk of bias. Results: The search identified 31 eligible articles, describing 29 trials. The included studies evaluated the use of computers to deliver cognitive rehabilitation (1 5 trials), patient education (3 trials), online self- management interventions (2 trials), and to support consultations (1 trial). Virtual reality (VR) was used to simulate work and social sit uations (2 trials ) and to deliver cognitive training (1 trial). Telephones were used to prompt medication use (3 trials ) and report SMI symptoms to healthcare teams (1 trial ). Remote sensors were used to monitor medication use (1 trial). Telephone support was found effective for improving medication adherence and reducing symptom severity and inpatient days. Computer assisted cognitive rehabilitation was effective in improving cognitive function. The impact of telehealth on other outcomes was inconsistent. Few studies evaluated the 3 use of remote medication telemonitoring, VR, online self-management and computer -mediated consultations, suggesting these are novel technologies for managing SMI, although all were found effective for improving psycho social and behavioural outcomes. The results of this review should be taken in the context of varied quality in study design, with only five studies demonstrating a low risk of bias. Conclusions : A growing variety of telehealth technologies are used to support SMI. Specific types of technology have been found to be effective for som e outcomes, for example telephone prompts for medication adherence, while other types of telehealth had no benefit over traditional methods and were less acceptable to patients. Few studies found benefits for telehealth on quality of life, except for novel technologies with a limited number of trials. Further research is warranted to establish the full potential benefits of telehealth for improving quality of life in SMI, acceptability from the service user perspective, and cost-effectivenes

Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review.

Breathing rate (BR) is a key physiological parameter used in a range of clinical settings. Despite its diagnostic and prognostic value, it is still widely measured by counting breaths manually. A plethora of algorithms have been proposed to estimate BR from the electrocardiogram (ECG) and pulse oximetry (photoplethysmogram, PPG) signals. These BR algorithms provide opportunity for automated, electronic, and unobtrusive measurement of BR in both healthcare and fitness monitoring. This paper presents a review of the literature on BR estimation from the ECG and PPG. First, the structure of BR algorithms and the mathematical techniques used at each stage are described. Second, the experimental methodologies that have been used to assess the performance of BR algorithms are reviewed, and a methodological framework for the assessment of BR algorithms is presented. Third, we outline the most pressing directions for future research, including the steps required to use BR algorithms in wearable sensors, remote video monitoring, and clinical practice

The positive association of infant weight gain with adulthood body mass index has strengthened over time in the Fels Longitudinal Study.

BACKGROUND: Infant weight gain is positively related to adulthood body mass index (BMI), but it is unknown whether or not this association is stronger for individuals born during (compared with before) the obesity epidemic. OBJECTIVES: The aim of the study was to examine how the infant weight gain-adulthood BMI association might have changed across successive birth year cohorts spanning most of the 20th century. METHODS: The sample comprised 346 participants in the Fels Longitudinal Study. Confounder-adjusted regression models were used to test the associations of conditional weight-for-length Z-score, capturing weight change between ages 0-2 years, with young adulthood BMI and blood pressure, including cohort [1933-1949 {N = 137}, 1950-1969 {N = 108}, 1970-1997 {N = 101}] as an effect modifier. RESULTS: Conditional weight-for-length Z-score was positively related to adulthood BMI, but there was significant effect modification by birth year cohort such that the association was over two times stronger in the 1970-1997 cohort (β 2.31; 95% confidence interval 1.59, 3.03) compared with the 1933-1949 (0.98; 0.31, 1.65) and 1950-1969 (0.87; 0.21, 1.54) cohorts. A similar pattern was found for systolic blood pressure. CONCLUSIONS: The infant weight gain-adulthood BMI association was over two times stronger among a cohort born during the obesity epidemic era compared with cohorts born earlier in the 20th century

Semiparametric Multivariate Accelerated Failure Time Model with Generalized Estimating Equations

The semiparametric accelerated failure time model is not as widely used as the Cox relative risk model mainly due to computational difficulties. Recent developments in least squares estimation and induced smoothing estimating equations provide promising tools to make the accelerate failure time models more attractive in practice. For semiparametric multivariate accelerated failure time models, we propose a generalized estimating equation approach to account for the multivariate dependence through working correlation structures. The marginal error distributions can be either identical as in sequential event settings or different as in parallel event settings. Some regression coefficients can be shared across margins as needed. The initial estimator is a rank-based estimator with Gehan's weight, but obtained from an induced smoothing approach with computation ease. The resulting estimator is consistent and asymptotically normal, with a variance estimated through a multiplier resampling method. In a simulation study, our estimator was up to three times as efficient as the initial estimator, especially with stronger multivariate dependence and heavier censoring percentage. Two real examples demonstrate the utility of the proposed method

Envelope Determinants of Equine Lentiviral Vaccine Protection

Lentiviral envelope (Env) antigenic variation and associated immune evasion present major obstacles to vaccine development. The concept that Env is a critical determinant for vaccine efficacy is well accepted, however defined correlates of protection associated with Env variation have yet to be determined. We reported an attenuated equine infectious anemia virus (EIAV) vaccine study that directly examined the effect of lentiviral Env sequence variation on vaccine efficacy. The study identified a significant, inverse, linear correlation between vaccine efficacy and increasing divergence of the challenge virus Env gp90 protein compared to the vaccine virus gp90. The report demonstrated approximately 100% protection of immunized ponies from disease after challenge by virus with a homologous gp90 (EV0), and roughly 40% protection against challenge by virus (EV13) with a gp90 13% divergent from the vaccine strain. In the current study we examine whether the protection observed when challenging with the EV0 strain could be conferred to animals via chimeric challenge viruses between the EV0 and EV13 strains, allowing for mapping of protection to specific Env sequences. Viruses containing the EV13 proviral backbone and selected domains of the EV0 gp90 were constructed and in vitro and in vivo infectivity examined. Vaccine efficacy studies indicated that homology between the vaccine strain gp90 and the N-terminus of the challenge strain gp90 was capable of inducing immunity that resulted in significantly lower levels of post-challenge virus and significantly delayed the onset of disease. However, a homologous N-terminal region alone inserted in the EV13 backbone could not impart the 100% protection observed with the EV0 strain. Data presented here denote the complicated and potentially contradictory relationship between in vitro virulence and in vivo pathogenicity. The study highlights the importance of structural conformation for immunogens and emphasizes the need for antibody binding, not neutralizing, assays that correlate with vaccine protection. © 2013 Craigo et al

N-player quantum games in an EPR setting

The $N$-player quantum game is analyzed in the context of an Einstein-Podolsky-Rosen (EPR) experiment. In this setting, a player's strategies are not unitary transformations as in alternate quantum game-theoretic frameworks, but a classical choice between two directions along which spin or polarization measurements are made. The players' strategies thus remain identical to their strategies in the mixed-strategy version of the classical game. In the EPR setting the quantum game reduces itself to the corresponding classical game when the shared quantum state reaches zero entanglement. We find the relations for the probability distribution for $N$-qubit GHZ and W-type states, subject to general measurement directions, from which the expressions for the mixed Nash equilibrium and the payoffs are determined. Players' payoffs are then defined with linear functions so that common two-player games can be easily extended to the $N$-player case and permit analytic expressions for the Nash equilibrium. As a specific example, we solve the Prisoners' Dilemma game for general $N \ge 2$. We find a new property for the game that for an even number of players the payoffs at the Nash equilibrium are equal, whereas for an odd number of players the cooperating players receive higher payoffs.Comment: 26 pages, 2 figure