Statistical methods for extracting information from the raw accelerometry data and their applications in public health research

Indiana University-Purdue University Indianapolis (IUPUI)Various methods exist to measure physical activity (PA). Subjective methods, such as diaries and surveys are relatively inexpensive ways of measuring one’s PA; how ever, they are riddled with measurement error and bias due to self-report. Wearable accelerometers offer a noninvasive and objective measure of subjects’ PA and are now widely used in observational and clinical studies. Accelerometers record high frequency data and produce an unlabeled time series at the sub-second level. An important activity to identify from such data is walking, since it is often the only form of exercise for certain populations. While much work has been done to advance the use of accelerometers in public health research, methodology is needed for quan tifying the physical characteristics of different types of PA from the raw signal. In my dissertation, I advance the accelerometry research methodology in a three-paper sequence. The first paper is a novel application of functional linear models to model the physical characteristics of walking. We emphasize the signal processing used to prepare the data for analyses, and we apply the methods to a motivating dataset collected in an elder population. The second paper addresses the classification of PA. We designed an experiment and collected the data with the purpose of extracting useful and interpretable features for differentiating among walking, descending stairs, and ascending stairs. We build subject-specific classification models utilizing a tree based classifier. We evaluate the effects of sensor location and tuning parameters on the classification rate of these models. The third paper addresses the classification of walking types at the population level. We propose a robust normalization of features extracted for each subject and compare the model classification results to evaluate the effect of feature normalization. In summary, this work provides a framework for better use of accelerometers in the study of physical activity.2 year

Prediction of sustained harmonic walking in the free-living environment using raw accelerometry data

Objective. Using raw, sub-second level, accelerometry data, we propose and validate a method for identifying and characterizing walking in the free-living environment. We focus on the sustained harmonic walking (SHW), which we define as walking for at least 10 seconds with low variability of step frequency. Approach. We utilize the harmonic nature of SHW and quantify local periodicity of the tri-axial raw accelerometry data. We also estimate fundamental frequency of observed signals and link it to the instantaneous walking (step-to-step) frequency (IWF). Next, we report total time spent in SHW, number and durations of SHW bouts, time of the day when SHW occurred and IWF for 49 healthy, elderly individuals. Main results. Sensitivity of the proposed classification method was found to be 97%, while specificity ranged between 87% and 97% and prediction accuracy between 94% and 97%. We report total time in SHW between 140 and 10 minutes-per-day distributed between 340 and 50 bouts. We estimate the average IWF to be 1.7 steps-per-second. Significance. We propose a simple approach for detection of SHW and estimation of IWF, based on Fourier decomposition. The resulting approach is fast and allows processing of a week-long raw accelerometry data (approx. 150 million measurements) in relatively short time (~half an hour) on a common laptop computer (2.8 GHz Intel Core i7, 16 GB DDR3 RAM)

Bone Density in Children with Single Ventricle Physiology

Background Children with chronic diseases are at risk for low bone mineral density (BMD). There are no studies of BMD in children with congenital heart disease and particularly SV. Children with this defect are often treated with warfarin, suspected to negatively impact BMD in adults. We assessed BMD in patients with single ventricle (SV) physiology and compared the BMD of subjects taking warfarin to those who were not. Methods Subjects 5-12 years with SV were included. BMD z-scores by dual-energy X-ray absorptiometry (DXA) of the spine and total body less head (TBLH) were obtained. Calcium intake, activity level, height, and Tanner stage were assessed. Linear regression models and t-tests were used to investigate differences between participants and normative data as well as between subjects' subgroups. Results Twenty six subjects were included; 16 took warfarin. Mean BMD z-score at the spine was significantly lower than expected at -1.0±0.2 (p<0.0001), as was the BMD z-score for TBLH at - 0.8±0.2 (p<0.0001). Those results remained significant after adjusting for height. Subjects who were on warfarin tended to have lower BMD at both the spine and TBLH than those who were not, with a z-score difference of 0.6±0.46 at the spine (p=0.106) and a difference of 0.4±0.34 at TBLH (p=0.132). Conclusions BMD is significantly reduced in children with SV. Warfarin appears to lower BMD but the effect is less conclusive. Continued evaluation is recommended for these patients at risk for reduced bone density. Evaluation of other cardiac patients on warfarin therapy should also be considered

Bell correlations in a split two-mode-squeezed Bose-Einstein condensate

We propose and analyze a protocol for observing a violation of the Clauser-Horne-Shimony-Holt (CHSH) Bell inequality using two spatially separated Bose-Einstein condensates (BECs). To prepare the Bell-correlated state, spin-changing collisions are used to first prepare a two-mode squeezed BEC. This is then split into two BECs by controlling the spatial wavefunction, e.g., by modifying the trapping potential. Finally, spin-changing collisions are also exploited locally, to compensate local squeezing terms. The correlators appearing in the inequality are evaluated using three different approaches. In the first approach, correlators are estimated using normalized expectation values of number operators, in a similar way to evaluating continuous-variable Bell inequalities. An improvement to this approach is developed using the sign-binning of total spin measurements, which allows for the construction of two-outcome measurements and violations of the CHSH inequality without auxiliary assumptions. Finally, we show a third approach where maximal violations of the CH inequality can be obtained by assigning zero values to local vacua outcomes under a no-enhancement assumption. The effect of loss and imperfect detection efficiency is investigated and the observed violations are found to be robust to noise.Comment: Updated published version; 21 pages, 4 figure

Predicting the glomerular filtration rate in bariatric surgery patients

BACKGROUND/AIMS: Identifying the best method to estimate the glomerular filtration rate (GFR) in bariatric surgery patients has important implications for the clinical care of obese patients and research into the impact of obesity and weight reduction on kidney health. We therefore performed such an analysis in patients before and after surgical weight loss. METHODS: Fasting measured GFR (mGFR) by plasma iohexol clearance before and after bariatric surgery was obtained in 36 severely obese individuals. Estimated GFR was calculated using the Modification of Diet in Renal Disease equation, the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation using serum creatinine only, the CKD-EPI equation using serum cystatin C only and a recently derived equation that uses both serum creatinine and cystatin C (CKD-EPIcreat-cystC) and then compared to mGFR. RESULTS: Participants were primarily middle-aged white females with a mean baseline body mass index of 46 ± 9, serum creatinine of 0.81 ± 0.24 mg/dl and mGFR of 117 ± 40 ml/min. mGFR had a stronger linear relationship with inverse cystatin C before (r = 0.28, p = 0.09) and after (r = 0.38, p = 0.02) surgery compared to the inverse of creatinine (before: r = 0.26, p = 0.13; after: r = 0.11, p = 0.51). mGFR fell by 17 ± 35 ml/min (p = 0.007) following surgery. The CKD-EPIcreat-cystC was unquestionably the best overall performing estimating equation before and after surgery, revealing very little bias and a capacity to estimate mGFR within 30% of its true value over 80% of the time. This was true whether or not mGFR was indexed for body surface area. CONCLUSIONS: In severely obese bariatric surgery patients with normal kidney function, cystatin C is more strongly associated with mGFR than is serum creatinine. The CKD-EPIcreat-cystC equation best predicted mGFR both before and after surgery

Using Simulation to Assess the Influence of Race and Insurer on Shared Decision-making in Periviable Counseling

Introduction: Sociodemographic differences have been observed in the treatment of extremely premature (periviable) neonates, but the source of this variation is not well understood. We assessed the feasibility of using simulation to test the effect of maternal race and insurance status on shared decision making (SDM) in periviable counseling. Methods: We conducted a 2 × 2 factorial simulation experiment in which obstetricians and neonatologists counseled 2 consecutive standardized patients diagnosed with ruptured membranes at 23 weeks, counterbalancing race (black/white) and insurance status using random permutation. We assessed verisimilitude of the simulation in semistructured debriefing interviews. We coded physician communication related to resuscitation, mode of delivery, and steroid decisions using a 9-point SDM coding framework and then compared communication scores by standardized patient race and insurer using analysis of variance. Results: Sixteen obstetricians and 15 neonatologists participated; 71% were women, 84% were married, and 75% were parents; 91% of the physicians rated the simulation as highly realistic. Overall, SDM scores were relatively high, with means ranging from 6.4 to 7.9 (of 9). There was a statistically significant interaction between race and insurer for SDM related to steroid use and mode of delivery (P < 0.01 and P = 0.01, respectively). Between-group comparison revealed nonsignificant differences (P = <0.10) between the SDM scores for privately insured black patients versus privately insured white patients, Medicaid-insured white patients versus Medicaid-insured black patients, and privately insured black patients versus Medicaid-insured black patients. Conclusions: This study confirms that simulation is a feasible method for studying sociodemographic effects on periviable counseling. Shared decision making may occur differentially based on patients’ sociodemographic characteristics and deserves further study

Use of Functional Linear Models to Detect Associations between Characteristics of Walking and Continuous Responses Using Accelerometry Data

Various methods exist to measure physical activity. Subjective methods, such as diaries and surveys, are relatively inexpensive ways of measuring one&rsquo;s physical activity; however, they are prone to measurement error and bias due to self-reporting. Wearable accelerometers offer a non-invasive and objective measure of one&rsquo;s physical activity and are now widely used in observational studies. Accelerometers record high frequency data and each produce an unlabeled time series at the sub-second level. An important activity to identify from the data collected is walking, since it is often the only form of activity for certain populations. Currently, most methods use an activity summary which ignores the nuances of walking data. We propose methodology to model specific continuous responses with a functional linear model utilizing spectra obtained from the local fast Fourier transform (FFT) of walking as a predictor. Utilizing prior knowledge of the mechanics of walking, we incorporate this as additional information for the structure of our transformed walking spectra. The methods were applied to the in-the-laboratory data obtained from the Developmental Epidemiologic Cohort Study (DECOS)

Effectiveness of implementing a wake up and breathe program on sedation and delirium in the ICU

OBJECTIVES: Mechanically ventilated critically ill patients receive significant amounts of sedatives and analgesics that increase their risk of developing coma and delirium. We evaluated the impact of a "Wake-up and Breathe Protocol" at our local ICU on sedation and delirium. DESIGN: A pre/post implementation study design. SETTING: A 22-bed mixed surgical and medical ICU. PATIENTS: Seven hundred two consecutive mechanically ventilated ICU patients from June 2010 to January 2013. INTERVENTIONS: Implementation of daily paired spontaneous awakening trials (daily sedation vacation plus spontaneous breathing trials) as a quality improvement project. MEASUREMENTS AND MAIN RESULTS: After implementation of our program, there was an increase in the mean Richmond Agitation Sedation Scale scores on weekdays of 0.88 (p < 0.0001) and an increase in the mean Richmond Agitation Sedation Scale scores on weekends of 1.21 (p < 0.0001). After adjusting for age, race, gender, severity of illness, primary diagnosis, and ICU, the incidence and prevalence of delirium did not change post implementation of the protocol (incidence: 23% pre vs 19.6% post; p = 0.40; prevalence: 66.7% pre vs 55.3% post; p = 0.06). The combined prevalence of delirium/coma decreased from 90.8% pre protocol implementation to 85% postimplementation (odds ratio, 0.505; 95% CI, 0.299-0.853; p = 0.01). CONCLUSIONS: Implementing a "Wake Up and Breathe Program" resulted in reduced sedation among critically ill mechanically ventilated patients but did not change the incidence or prevalence of delirium