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Background: Infection with HIV-1 results in marked immunologic insults and structural damage to the intestinal mucosa, including compromised barrier function. While the development of highly active antiretroviral therapy (HAART) has been a major advancement in the treatment of HIV-1 infection, the need for novel complementary interventions to help restore intestinal structural and functional integrity remains unmet. Known properties of pre-, pro-, and synbiotics suggest that they may be useful tools in achieving this goal.Methods: This was a 4-week parallel, placebo-controlled, randomized pilot trial in HIV-infected women on antiretroviral therapy. A synbiotic formulation (Synbiotic 2000®) containing 4 strains of probiotic bacteria (1010each) plus 4 nondigestible, fermentable dietary fibers (2.5 g each) was provided each day, versus a fiber-only placebo formulation. The primary outcome was bacterial translocation. Secondary outcomes included the levels of supplemented bacteria in stool, the activation phenotype of peripheral T-cells and monocytes, and plasma levels of C-reactive protein and soluble CD14.Results: Microbial translocation, as measured by plasma bacterial 16S ribosomal DNA concentration, was not altered by synbiotic treatment. In contrast, the synbiotic formulation resulted in significantly elevated levels of supplemented probiotic bacterial strains in stool, including L. plantarum and P. pentosaceus, with the colonization of these two species being positively correlated with each other. T-cell activation phenotype of peripheral blood lymphocytes showed modest changes in response to synbiotic exposure, with HLA-DR expression slightly elevated on a minor population of CD4+ T-cells which lack expression of HLA-DR or PD-1. In addition, CD38 expression on CD8+ T-cells was slightly lower in the fiber-only group. Plasma levels of soluble CD14 and C-reactive protein were unaffected by synbiotic treatment in this study.Conclusions: Synbiotic treatment for 4 weeks can successfully augment the levels of probiotic species in the gut during chronic HIV-1 infection. Associated changes in microbial translocation appear to be absent, and markers of systemic immune activation appear largely unchanged. These findings may help inform future studies aimed at testing pre- and probiotic approaches to improve gut function and mucosal immunity in chronic HIV-1 infection.Trial registration: Clinical Trials.gov: NCT00688311. © 2012 Schunter et al.;licensee BioMed Central Ltd.

Unlabelled: This report describes a pilot study to evaluate feasibility of new home-based assessment technologies applicable to clinical trials for prevention of cognitive loss and Alzheimer disease.Methods: Community-dwelling nondemented individuals >or=75 years old were recruited and randomized to 1 of 3 assessment methodologies: (1) mail-in questionnaire/ live telephone interviews (MIP); (2) automated telephone with interactive voice recognition (IVR); and (3) internet-based computer Kiosk (KIO). Brief versions of cognitive and noncognitive outcomes were adapted to the different methodologies and administered at baseline and 1-month. An Efficiency measure, consisting of direct staff-to-participant time required to complete assessments, was also compared across arms.Results: Forty-eight out of 60 screened participants were randomized. The dropout rate across arms from randomization through 1-month was different: 33% for KIO, 25% for IVR, and 0% for MIP (Fisher Exact Test P=0.04). Nearly all participants who completed baseline also completed 1-month assessment (38 out of 39). The 1-way ANOVA across arms for total staff-to-participant direct contact time (ie, training, baseline, and 1-month) was significant: F (2,33)=4.588; P=0.017, with lowest overall direct time in minutes for IVR (Mn=44.4; SD=21.5), followed by MIP (Mn=74.9; SD=29.9), followed by KIO (Mn=129.4; SD=117.0).Conclusions: In this sample of older individuals, a higher dropout rate occurred in those assigned to the high-technology assessment techniques; however, once participants had completed baseline in all 3 arms, they continued participation through 1 month. High-technology home-based assessment methods, which do not require live testers, began to emerge as more time-efficient over the brief time of this pilot, despite initial time-intensive participant training. [ABSTRACT FROM AUTHOR]

Replay is the reactivation of one or more neural patterns that are similar to the activation patterns experienced during past waking experiences. Replay was first observed in biological neural networks during sleep, and it is now thought to play a critical role in memory formation, retrieval, and consolidation. Replay-like mechanisms have been incorporated in deep artificial neural networks that learn over time to avoid catastrophic forgetting of previous knowledge. Replay algorithms have been successfully used in a wide range of deep learning methods within supervised, unsupervised, and reinforcement learning paradigms. In this letter, we provide the first comprehensive comparison between replay in the mammalian brain and replay in artificial neural networks. We identify multiple aspects of biological replay that are missing in deep learning systems and hypothesize how they could be used to improve artificial neural networks., (© 2021 Massachusetts Institute of Technology.)

Supervised classification methods often assume the train and test data distributions are the same and that all classes in the test set are present in the training set. However, deployed classifiers often require the ability to recognize inputs from outside the training set as unknowns. This problem has been studied under multiple paradigms including out-of-distribution detection and open set recognition. For convolutional neural networks, there have been two major approaches: 1) inference methods to separate knowns from unknowns and 2) feature space regularization strategies to improve model robustness to novel inputs. Up to this point, there has been little attention to exploring the relationship between the two approaches and directly comparing performance on large-scale datasets that have more than a few dozen categories. Using the ImageNet ILSVRC-2012 large-scale classification dataset, we identify novel combinations of regularization and specialized inference methods that perform best across multiple open set classification problems of increasing difficulty level. We find that input perturbation and temperature scaling yield significantly better performance on large-scale datasets than other inference methods tested, regardless of the feature space regularization strategy. Conversely, we find that improving performance with advanced regularization schemes during training yields better performance when baseline inference techniques are used; however, when advanced inference methods are used to detect open set classes, the utility of these combersome training paradigms is less evident., Competing Interests: One author in this study, CK, was employed at a commercial company, Paige, New York during the preparation of this manuscript. This company played no role in the sponsorship, design, data collection and analysis, decision to publish, or preparation of the manuscript. This interest does not alter our adherence to PLOS ONE policies on sharing data and materials.

Introduction: There is an unmet need for effective methods for conducting dementia prevention trials., Methods: Home-based assessment study compared feasibility and efficiency, ability to capture change over time using in-home instruments, and ability to predict cognitive conversion using predefined triggers in a randomized clinical trial in (1) mail-in questionnaire/live telephone interviews, (2) automated telephone/interactive voice recognition, and (3) internet-based computer Kiosk technologies. Primary endpoint was defined as cognitive conversion., Results: Analysis followed a modified intent-to-treat principle. Dropout rates were low and similar across technologies but participants in Kiosk were more likely to dropout earlier. Staff resources needed were higher in Kiosk. In-home instruments distinguished conversion and stable groups. Cognitively stable group showed improvement in cognitive measures. Triggering was associated with higher likelihood of conversion but statistically significant only in mail-in questionnaire/live telephone interviews., Discussion: Relatively low efficiency of internet-based assessment compared with testing by live-assessors has implications for internet-based recruitment and assessment efforts currently proposed for diverse populations., (Published by Elsevier Inc.)

Purpose: Surface imaging (SI) offers a nonionizing, near real time alternative to radiographic imaging for intrafraction radiosurgery localization. In this work, we systematically compared a commercial SI system vs a commercial room mounted x-ray localization system in phantom., Methods: An anthropomorphic head phantom with fiducial markers was imaged with linear accelerator on-board x-ray imaging, SI, and room mounted x-ray imaging (RM) at ±45° and ±90° couch angles for three different head tilts and six different isocenters (72 total positions). The shifts generated by the three systems were compared as functions of couch angle, head tilt, and isocenter position with the on-board imaging shifts used as ground truth. Two sample Kolmogorov-Smirnov tests were used to evaluate equivalence of the groups., Results: The magnitude of the displacement vectors for RM minus on-board imaging and SI minus on-board imaging over all 72 phantom positions were 0.7 ± 0.3 mm for both cases. The RM and SI showed no significant difference based on couch angle or isocenter position. Both systems showed decreasing accuracy with increasing couch angle, but both systems agreed with ground truth to <=1.1 mm at all couch angles. The exaggerated chin-up head orientation showed significantly different shifts for SI and RM based on increased variance in the SI measurements, although both had submillimeter accuracy on average. The standard deviation of the real time SI displacement vector was <0.06 mm over all measurements, during which the on-board imaging panels partially blocked the lateral camera pods for half the time., Conclusions: RM and SI showed similar accuracy over measurements at 72 different phantom positions. SI showed minimal performance loss with camera pods blocked. SI is a feasible option for intra-fraction radiosurgery localization based on these phantom measurements., (© 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Study Objective: High-dose intravenous vitamin C is a potential treatment option for patients with sepsis and may interfere with point-of-care (POC) blood glucose (BG) testing. This study aimed to determine if vitamin C dosing used for sepsis affected POC BG level results., Design: Prospective observational pilot study., Setting: Intensive care unit in a large academic tertiary care medical center., Patients: Five consecutive critically ill adults hospitalized between April 1 and June 1, 2017, who received two or more doses of intravenous vitamin C 1500 mg for the treatment of sepsis and had at least two paired POC BG levels and laboratory venous BG levels measured within 1 hour of each other during vitamin C therapy., Measurements and Main Results: The performance of POC BG level measurement was compared with the reference method of laboratory BG level measurement. The concordance to minimum accuracy criteria for BG meters set forth by the International Organization for Standardization (ISO) 15197:2013, the measurement of agreement between POC BG level and laboratory BG level using the Bland-Altman method, and the clinical accuracy through Parkes error grid analysis were assessed. A total of 16 paired POC and laboratory BG level measurements from the five patients were included. The accuracy of POC BG with laboratory BG level measurements during vitamin C administration according to ISO 15197:2013 criteria was 81.3%, which did not meet the minimum accuracy criteria of 95%. The Bland-Altman analysis showed a mean difference between POC and laboratory BG levels of 8.9 mg/dl, and the Parkes error grid analysis showed that the differences between POC and laboratory BG level measurements would not have resulted in a change in clinical action., Conclusion: The accuracy and agreement of POC and laboratory BG level measurements in critically ill patients receiving vitamin C were consistent with previously published reports in critically ill patients not receiving vitamin C and did not demonstrate clinically significant interference due to vitamin C dosing for sepsis., (© 2018 Pharmacotherapy Publications, Inc.)

Introduction : Increased variability in motor function has been observed during the initial stages of cognitive decline. However, the natural variability of postural control, as well as its association with cognitive status and decline, remains unknown. The objective of this pilot study was to characterize the day-to-day variability in postural sway in non-demented older adults. We hypothesized that older adults with a lower cognitive status would have higher day-to-day variability in postural sway. Materials and Methods : A Nintendo Wii balance board (WBB) was used to quantify postural sway in the home twice daily for 30 days in 20 non-demented, community-dwelling older adults: once under a single-task condition and once under a dual-task condition (using a daily word search task administered via a Nook tablet). Mean sway distance, velocity, area, centroidal frequency and frequency dispersion were derived from the center of pressure data acquired from the WBB. Results : Linear relationships were observed between the day-to-day variability in postural sway and cognitive status (indexed by cognitive global z-scores). More variability in time-domain postural sway (sway distance and area) and less variability in frequency-domain postural sway (centroidal sway frequency) were associated with a lower cognitive status under both the single- and dual-task conditions. Additionally, lower cognitive performance rates on the daily word search task were related to a lower cognitive status. Discussion : This small pilot study conducted on a short time scale motivates large-scale implementations over more extended time periods. Tracking longitudinal changes in postural sway may further our understanding of early-stage postural decline and its association with cognitive decline and, in turn, may aid in the early detection of dementia during preclinical stages when the utility of disease-modifying therapies would be greatest.

Background: Prothrombin complex concentrates (PCCs) have become the first-line therapy for warfarin reversal in the setting of central nervous system (CNS) hemorrhage. Randomized, controlled studies comparing agents for warfarin reversal excluded patients with international normalized ratio (INR) <2, yet INR values of 1.6-1.9 are also associated with poor outcomes., Methods: We retrospectively reviewed our use of a low-dose (15 units/kg) strategy of 4-factor PCC (4F-PCC) on warfarin reversal (INR 1.6-1.9) in the setting of both traumatic and spontaneous intracranial bleeding., Results: A total of 21/134 (15.7%) patients with either spontaneous or traumatic intracranial hemorrhage presented with an INR value of 1.6-1.9. Nine patients (43%) presented with traumatic bleeding and 12 (57%) with spontaneous bleeding. The median (IQR) presenting INR was 1.8 (1.7, 1.9) which decreased to 1.3 (1.2, 1.3) following the administration of low-dose 4F-PCC (median dose = 1062 units; 15.2 units/kg). A total of 19/20 (95%) patients achieved a goal INR value of ≤1.5 on the first check following dosing and 17/20 (85%) achieved an INR value ≤1.3. One patient did not have follow-up INR testing due to withdrawal of life support. No patient experienced hematoma expansion within 48 h of 4F-PCC, and there were no thromboembolic events within 72 h of administration., Conclusions: The administration of low dose (15 units/kg) of 4F-PCC for urgent warfarin reversal in the setting of CNS hemorrhage was effective in correcting the INR in patients presenting with INR values of 1.6-1.9. Further assessment of low-dose PCC for urgent reversal of modest INR elevation is warranted.

Performing a procedure on the wrong patient or site is one of the greatest errors that can occur in medicine. The addition of automation has been shown to reduce errors in many processes. In this work we explore the use of an automated patient identification process using optical surface imaging for radiotherapy treatments. Surface imaging uses visible light to align the patient to a reference surface in the treatment room. It is possible to evaluate the similarity between a daily set-up surface image and the reference image using distance to agreement between the points on the two surfaces. The higher the percentage overlapping points within a defined distance, the more similar the surfaces. This similarity metric was used to intercompare 16 left-sided breast patients. The reference surface for each patient was compared to 10 daily treatment surfaces for the same patient, and 10 surfaces from each of the other 15 patients (for a total of 160 comparisons per patient), looking at the percent of points overlapping. For each patient, the minimum same-patient similarity score was higher than the maximum different-patient score. For the group as a whole a threshold was able to classify correct and incorrect patients with high levels of accuracy. A 10-fold cross-validation using linear discriminant analysis gave cross-validation loss of 0.0074. An automated process using surface imaging is a feasible option to provide nonharmful daily patient identification verification using currently available technology.

Unlabelled: Numerous studies have demonstrated that CD8(+) T lymphocytes suppress virus replication during human immunodeficiency virus (HIV)/simian immunodeficiency virus (SIV) infection. However, the mechanisms underlying this activity of T cells remain incompletely understood. Here, we conducted CD8(+) T lymphocyte depletion in 15 rhesus macaques (RMs) infected intravenously (i.v.) with SIVmac239. At day 70 postinfection, the animals (10 progressors with high viremia and 5 controllers with low viremia) were CD8 depleted by i.v. administration of the antibody M-T807R1. As expected, CD8 depletion resulted in increased virus replication, more prominently in controllers than progressors, which correlated inversely with predepletion viremia. Of note, the feature of CD8(+) T lymphocyte predepletion that correlated best with the increase in viremia postdepletion was the level of CD8(+) T-bet(+) lymphocytes. We next found that CD8 depletion resulted in a homogenous increase of SIV RNA in superficial and mesenteric lymph nodes, spleen, and the gastrointestinal tract of both controllers and progressors. Interestingly, the level of SIV DNA increased postdepletion in both CD4(+) central memory T lymphocytes (TCM) and CD4(+) effector memory T lymphocytes (TEM) in progressor RMs but decreased in the CD4(+) TCM of 4 out of 5 controllers. Finally, we found that CD8 depletion is associated with a greater increase in CD4(+) T lymphocyte activation (measured by Ki-67 expression) in controllers than in progressors. Overall, these data reveal a differential impact of CD8(+) T lymphocyte depletion between controller and progressor SIV-infected RMs, emphasizing the complexity of the in vivo antiviral role of CD8(+) T lymphocytes., Importance: In this study, we further dissect the impact of CD8(+) T lymphocytes on HIV/SIV replication during SIV infection. CD8(+) T lymphocyte depletion leads to a relatively homogenous increase in viral replication in peripheral blood and tissues. CD8(+) T lymphocyte depletion resulted in a more prominent increase in viral loads and CD4(+) T lymphocyte activation in controllers than in progressors. Interestingly, we found T-bet expression on CD8(+) T lymphocytes to be the best predictor of viral load increase following depletion. The levels of SIV DNA increase postdepletion in both CD4(+) TCM and TEM in progressor RMs but decrease in the CD4(+) TCM of controllers. The findings described in this study provide key insights into the differential functions of CD8(+) T lymphocytes in controller and progressor RMs., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

The Nintendo Wii balance board (WBB) has generated significant interest in its application as a postural control measurement device in both the clinical and (basic, clinical, and rehabilitation) research domains. Although the WBB has been proposed as an alternative to the "gold standard" laboratory-grade force plate, additional research is necessary before the WBB can be considered a valid and reliable center of pressure (CoP) measurement device. In this study, we used the WBB and a laboratory-grade AMTI force plate (AFP) to simultaneously measure the CoP displacement of a controlled dynamic load, which has not been done before. A one-dimensional inverted pendulum was displaced at several different displacement angles and load heights to simulate a variety of postural sway amplitudes and frequencies (<1 Hz). Twelve WBBs were tested to address the issue of inter-device variability. There was a significant effect of sway amplitude, frequency, and direction on the WBB's CoP measurement error, with an increase in error as both sway amplitude and frequency increased and a significantly greater error in the mediolateral (ML) (compared to the anteroposterior (AP)) sway direction. There was no difference in error across the 12 WBB's, supporting low inter-device variability. A linear calibration procedure was then implemented to correct the WBB's CoP signals and reduce measurement error. There was a significant effect of calibration on the WBB's CoP signal accuracy, with a significant reduction in CoP measurement error (quantified by root-mean-squared error) from 2-6 mm (before calibration) to 0.5-2 mm (after calibration). WBB-based CoP signal calibration also significantly reduced the percent error in derived (time-domain) CoP sway measures, from -10.5% (before calibration) to -0.05% (after calibration) (percent errors averaged across all sway measures and in both sway directions). In this study, we characterized the WBB's CoP measurement error under controlled, dynamic conditions and implemented a linear calibration procedure for WBB CoP signals that is recommended to reduce CoP measurement error and provide more reliable estimates of time-domain CoP measures. Despite our promising results, additional work is necessary to understand how our findings translate to the clinical and rehabilitation research domains. Once the WBB's CoP measurement error is fully characterized in human postural sway (which differs from our simulated postural sway in both amplitude and frequency content), it may be used to measure CoP displacement in situations where lower accuracy and precision is acceptable.

Loneliness is a common condition in elderly associated with severe health consequences including increased mortality, decreased cognitive function, and poor quality of life. Identifying and assisting lonely individuals is therefore increasingly important-especially in the home setting-as the very nature of loneliness often makes it difficult to detect by traditional methods. One critical component in assessing loneliness unobtrusively is to measure time spent out-of-home, as loneliness often presents with decreased physical activity, decreased motor functioning, and a decline in activities of daily living, all of which may cause decrease in the amount of time spent outside the home. Using passive and unobtrusive in-home sensing technologies, we have developed a methodology for detecting time spent out-of-home based on logistic regression. Our approach was both sensitive (0.939) and specific (0.975) in detecting time out-of-home across over 41,000 epochs of data collected from four subjects monitored for at least 30 days each in their own homes. In addition to linking time spent out-of-home to loneliness, (r = -0.44, p = 0.011) as measured by the UCLA Loneliness Index, we demonstrate its usefulness in other applications such as uncovering general behavioral patterns of elderly and exploring the link between time spent out-of-home and physical activity ( r = 0.415, p = 0.031), as measured by the Berkman Social Disengagement Index.

A low CD4/CD8 ratio in elderly HIV-uninfected adults is associated with increased morbidity and mortality. A subset of HIV-infected adults receiving effective antiretroviral therapy (ART) fails to normalize this ratio, even after they achieve normal CD4+ T cell counts. The immunologic and clinical characteristics of this clinical phenotype remain undefined. Using data from four distinct clinical cohorts and three clinical trials, we show that a low CD4/CD8 ratio in HIV-infected adults during otherwise effective ART (after CD4 count recovery above 500 cells/mm3) is associated with a number of immunological abnormalities, including a skewed T cell phenotype from naïve toward terminally differentiated CD8+ T cells, higher levels of CD8+ T cell activation (HLADR+CD38+) and senescence (CD28- and CD57+CD28-), and higher kynurenine/tryptophan ratio. Changes in the peripheral CD4/CD8 ratio are also reflective of changes in gut mucosa, but not in lymph nodes. In a longitudinal study, individuals who initiated ART within six months of infection had greater CD4/CD8 ratio increase compared to later initiators (>2 years). After controlling for age, gender, ART duration, nadir and CD4 count, the CD4/CD8 ratio predicted increased risk of morbidity and mortality. Hence, a persistently low CD4/CD8 ratio during otherwise effective ART is associated with increased innate and adaptive immune activation, an immunosenescent phenotype, and higher risk of morbidity/mortality. This ratio may prove useful in monitoring response to ART and could identify a unique subset of individuals needed of novel therapeutic interventions.

We explored the relationship between sleep disturbances and mild cognitive impairment (MCI) in community-dwelling seniors. Recent evidence suggests that sleep habits are differentially compromised in different subtypes of MCI, but the relationship between sleep disruption and MCI remains poorly understood. We gathered daily objective measures of sleep disturbance from 45 seniors, including 16 with MCI (mean age, 86.9±4.3 y), over a 6-month period. We also collected self-report measures of sleep disturbance. Although there were no differences between groups in any of our self-report measures, we found that amnestic MCI (aMCI) volunteers had less disturbed sleep than both nonamnestic MCI (naMCI) and cognitively intact volunteers, as measured objectively by movement in bed at night (F2,1078=4.30, P=0.05), wake after sleep onset (F2,1078=41.6, P<0.001), and number of times up at night (F2,1078=26.7, P<0.001). The groups did not differ in total sleep time. In addition, the aMCI group had less day-to-day variability in these measures than the intact and naMCI volunteers. In general, the naMCI volunteers showed a level of disturbed sleep that was intermediate to that of aMCI and intact volunteers. These differences in sleep disruption between aMCI and naMCI may be related to differences in the pathology underlying these MCI subtypes.

Objectives: To ascertain the association between self-report of low mood and unobtrusively measured behaviors (walking speed, time out of residence, frequency of room transitions, and computer use) in community-dwelling older adults using novel monitoring technologies., Design: Longitudinal cohort study of older adults whose homes were outfitted with activity sensors. Participants completed Internet-based weekly health questionnaires with questions about mood., Setting: Apartments and homes of older adults living in the Portland, Oregon, metropolitan area., Participants: Adults, average age 84, followed for an average of 3.7 years (n = 157)., Measurements: Mood was assessed according to self-report each week. Walking speed, time spent out of residence, and room transitions were estimated using data from sensors; computer use was measured by timing actual use. The association between global or weekly low mood and the four behavior measures was ascertained, adjusting for baseline characteristics., Results: Eighteen thousand nine hundred sixty weekly observations of mood were analyzed; 2.6% involved low mood. Individuals who reported low mood more often had no average differences in any behavior parameters from those who reported low mood less often. During weeks when they reported low mood, participants spent significantly less time out of residence and on the computer but showed no change in walking speed or room transitions., Conclusion: Low mood in these community-dwelling older adults involved going out of the house less and using the computer less but no consistent changes in movements. Technologies to monitor in-home behavior may have potential for research and clinical care., (© Published 2014. This article is a U.S. Government work and is in the public domain in the U.S.A.)

This report describes the baseline experience of the multicenter, Home-Based Assessment study, designed to develop methods for dementia prevention trials using novel technologies for test administration and data collection. Nondemented individuals of 75 years of age or more were recruited and evaluated in-person using established clinical trial outcomes of cognition and function, and randomized to one of 3 assessment methodologies: (1) mail-in questionnaire/live telephone interviews [mail-in/phone (MIP)]; (2) automated telephone with interactive voice recognition; and (3) internet-based computer Kiosk. Brief versions of cognitive and noncognitive outcomes were adapted to each methodology and administered at baseline and repeatedly over a 4-year period. "Efficiency" measures assessed the time from screening to baseline, and staff time required for each methodology. A total of 713 individuals signed consent and were screened; 640 met eligibility and were randomized to one of 3 assessment arms; and 581 completed baseline. Dropout, time from screening to baseline, and total staff time were highest among those assigned to internet-based computer Kiosk. However, efficiency measures were driven by nonrecurring start-up activities suggesting that differences may be mitigated over a long trial. Performance among Home-Based Assessment instruments collected through different technologies will be compared with established outcomes over this 4-year study.

The CCR5 inhibitor maraviroc has been hypothesized to decrease T-cell activation in HIV-infected individuals, but its independent immunologic effects have not been established in a placebo-controlled trial. We randomized 45 HIV-infected subjects with CD4 counts <350 cells per mm(3) and plasma HIV RNA levels <48 copies per mL on antiretroviral therapy (ART) to add maraviroc vs placebo to their regimen for 24 weeks followed by 12 weeks on ART alone. Compared with placebo-treated subjects, maraviroc-treated subjects unexpectedly experienced a greater median increase in % CD38+HLA-DR+ peripheral blood CD8+ T cells at week 24 (+2.2% vs -0.7%, P = .014), and less of a decline in activated CD4+ T cells (P < .001). The % CD38+HLA-DR+ CD4+ and CD8+ T cells increased nearly twofold in rectal tissue (both P < .001), and plasma CC chemokine receptor type 5 (CCR5) ligand (macrophage-inflammatory protein 1β) levels increased 2.4-fold during maraviroc intensification (P < .001). During maraviroc intensification, plasma lipopolysaccharide declined, whereas sCD14 levels and neutrophils tended to increase in blood and rectal tissue. Although the mechanisms explaining these findings remain unclear, CCR5 ligand-mediated activation of T cells, macrophages, and neutrophils via alternative chemokine receptors should be explored. These results may have relevance for trials of maraviroc for HIV preexposure prophylaxis and graft-versus-host disease. This trial was registered at www.clinicaltrials.gov as #NCT00735072.

Sleep apnea is a serious condition that afflicts many individuals and is associated with serious health complications. Polysomnography, the gold standard for assessing and diagnosing sleep apnea, uses breathing sensors that are intrusive and can disrupt the patient's sleep during the overnight testing. We investigated the use of breathing signals derived from non-contact force sensors (i.e. load cells) placed under the supports of the bed as an alternative to traditional polysomnography breathing sensors (e.g. nasal pressure, oral-nasal thermistor, chest belt and abdominal belt). The apnea-hypopnea index estimated using the load cells was not different than that estimated using standard polysomnography leads (t44  = 0.37, P = 0.71). Overnight polysomnography sleep studies scored using load cell breathing signals had an intra-class correlation coefficient of 0.97 for the apnea-hypopnea index and an intra-class correlation coefficient of 0.85 for the respiratory disturbance index when compared with scoring using traditional polysomnography breathing sensors following American Academy of Sleep Medicine guidelines. These results demonstrate the feasibility of using unobtrusive load cells installed under the bed to measure the apnea-hypopnea index., (© 2013 European Sleep Research Society.)

Objective: The objective of this study was to assess the effects of HAART initiation on CD4(+) T-cell repopulation and T-cell immune activation in rectal and duodenal mucosa., Design: The effects of HAART on the gastrointestinal tract remain controversial, and studies have reached different conclusions regarding its effectiveness at restoring mucosal CD4(+) T cells depending upon time of initiation, duration of treatment and gastrointestinal tract region studied., Methods: We obtained blood, rectal biopsies and duodenal biopsies from 14 chronically infected individuals at baseline and at 4-9 months post-HAART initiation. We examined CD4(+) T-cell frequencies in blood, rectum and duodenum at both time points, and performed a detailed assessment of CD4(+) T-cell phenotype, immune activation marker expression and HIV-specific CD8(+) T-cell responses in blood and rectal mucosa., Results: CD4(+) T-cell percentages increased significantly in blood, rectal and duodenal mucosa after 4-9 months of HAART (P = 0.02, 0.0005, 0.0002), but remained lower than in uninfected controls. HIV-specific CD8(+) T-cell responses in blood and rectal mucosa declined following HAART initiation (P = 0.0015, 0.021). CD8(+) T-cell coexpression of CD38 and HLA-DR in blood and mucosa, as well as plasma sCD14, declined significantly. CD28 expression on blood and mucosal CD8(+) T cells increased, whereas programmed death receptor-1 expression on blood HIV-specific CD4(+) and CD8(+) T cells decreased., Conclusion: Within the first months of HAART, limited CD4(+) T-cell reconstitution occurs in small and large intestinal mucosa. Nevertheless, decreased immune activation and increased CD28 expression suggest rapid immunological benefits of HAART despite incomplete CD4(+) T-cell reconstitution.

Incessant scratching as a result of diseases such as atopic dermatitis causes skin break down, poor sleep quality, and reduced quality of life for affected individuals. In order to develop more effective therapies, there is a need for objective measures to detect scratching. Wrist actigraphy, which detects wrist movements over time using micro-accelerometers, has shown great promise in detecting scratch because it is lightweight, usable in the home environment, can record longitudinally, and does not require any wires. However, current actigraphy-based scratch-detection methods are limited in their ability to discriminate scratch from other nighttime activities. Our previous work demonstrated the separability of scratch from both walking and restless sleep using a clustering technique which employed four features derived from the actigraphic data: number of accelerations above 0.01 gs, epoch variance, peak frequency, and autocorrelation value at one lag. In this paper, we extended these results by employing these same features as independent variables in a logistic regression model. This allows us to directly estimate the conditional probability of scratching for each epoch. Our approach outperforms competing actigraphy-based approaches and has both high sensitivity (0.96) and specificity (0.92) for identifying scratch as validated on experimental data collected from 12 healthy subjects. The model must still be fully validated on clinical data, but shows promise for applications to clinical trials and longitudinal studies of scratch.

The healthcare system is in crisis due to challenges including escalating costs, the inconsistent provision of care, an aging population, and high burden of chronic disease related to health behaviors. Mitigating this crisis will require a major transformation of healthcare to be proactive, preventive, patient-centered, and evidence-based with a focus on improving quality-of-life. Information technology, networking, and biomedical engineering are likely to be essential in making this transformation possible with the help of advances, such as sensor technology, mobile computing, machine learning, etc. This paper has three themes: 1) motivation for a transformation of healthcare; 2) description of how information technology and engineering can support this transformation with the help of computational models; and 3) a technical overview of several research areas that illustrate the need for mathematical modeling approaches, ranging from sparse sampling to behavioral phenotyping and early detection. A key tenet of this paper concerns complementing prior work on patient-specific modeling and simulation by modeling neuropsychological, behavioral, and social phenomena. The resulting models, in combination with frequent or continuous measurements, are likely to be key components of health interventions to enhance health and wellbeing and the provision of healthcare.

CD8(+) T cells inhibit virus replication in SIV-infected rhesus macaques. However, it is unclear to what extent the viral suppression mediated by CD8(+) T cells reflects direct killing of infected cells as opposed to indirect, noncytolytic mechanisms. In this study, we used functional genomics to investigate noncytolytic mechanisms of in vivo viral suppression mediated by CD8(+) lymphocytes. Eight chronically SIVmac239-infected rhesus macaques underwent CD8(+) lymphocyte depletion, and RNA from whole blood was obtained prior to depletion, during the nadir of CD8(+) cell depletion, and after CD8(+) lymphocyte numbers had rebounded. We observed significant downregulation of the expression of genes encoding factors that can suppress SIV replication, including the CCR5-binding chemokine CCL5/RANTES and CCL4 and several members of the tripartite motif-containing (TRIM) family. Surprisingly, we also noted a strong, widespread downregulation of α- and θ-defensins with anti-HIV activity, which are not expressed by CD8(+) T cells. After cessation of depleting antibody treatment, we observed induction of a transcriptional signature indicative of B lymphocyte activation. Validation experiments demonstrated that animals during this period had elevated levels of B cells coupled with higher expression of the proliferative marker Ki67, indicating that CD8(+) depletion triggered a potent expansion of B cell numbers. Collectively, these data identify antiviral pathways perturbed by in vivo CD8(+) T cell depletion that may contribute to noncytolytic control of SIV replication.

With the rising age of the population, there is increased need to help elderly maintain their independence. Smart homes, employing passive sensor networks and pervasive computing techniques, enable the unobtrusive assessment of activities and behaviors of the elderly which can be useful for health state assessment and intervention. Due to the multiple health benefits associated with socializing, accurately tracking whether an individual has visitors to their home is one of the more important aspects of elders' behaviors that could be assessed with smart home technology. With this goal, we have developed a preliminary SVM model to identify periods where untagged visitors are present in the home. Using the dwell time, number of sensor firings, and number of transitions between major living spaces (living room, dining room, kitchen and bathroom) as features in the model, and self report from two subjects as ground truth, we were able to accurately detect the presence of visitors in the home with a sensitivity and specificity of 0.90 and 0.89 for subject 1, and of 0.67 and 0.78 for subject 2, respectively. These preliminary data demonstrate the feasibility of detecting visitors with in-home sensor data, but highlight the need for more advanced modeling techniques so the model performs well for all subjects and all types of visitors.

Poor quality of sleep increases the risk of many adverse health outcomes. Some measures of sleep, such as sleep efficiency or sleep duration, are calculated from periods of time when a patient is asleep and awake. The current method for assessing sleep and wakefulness is based on polysomnography, an expensive and inconvenient method of measuring sleep in a clinical setting. In this paper, we suggest an alternative method of detecting periods of sleep and wake that can be obtained unobtrusively in a patient's own home by placing load cells under the supports of their bed. Specifically, we use a support vector machine to classify periods of sleep and wake in a cohort of patients admitted to a sleep lab. The inputs to the classifier are subject demographic information, a statistical characterization of the load cell derived signals, and several sleep parameters estimated from the load cell data that are related to movement and respiration. Our proposed classifier achieves an average sensitivity of 0.808 and specificity of 0.812 with 90% confidence intervals of (0.790, 0.821) and (0.798, 0.826), respectively, when compared to the "gold-standard" sleep/wake annotations during polysomnography. As this performance is over 27 sleep patients with a wide variety of diagnosis levels of sleep disordered breathing, age, body mass index, and other demographics, our method is robust and works well in clinical practice.

Quality of sleep is an important attribute of an individual's health state and its assessment is therefore a useful diagnostic feature. Changes in the patterns of mobility in bed during sleep can be a disease marker or can reflect various abnormal physiological and neurological conditions. This paper describes a method for detection of movement in bed that is evaluated on data collected from patients admitted for regular polysomnography. The system is based on load cells installed at the supports of a bed. Since the load cell signal varies the most during movement, the approach uses a weighted combination of the short-term mean-square differences of each load cell signal to capture the variations in the signal caused by movement. We use a single univariate Gaussian model to represent each class: movement versus non-movement. We assess the performance of the method against manual annotation performed by a sleep clinic technician from seventeen patients. The proposed detection method achieved an overall sensitivity of 97.9% and specificity of 98.7%.

Background: Executive dysfunction has previously been found to be a risk factor for falls. The aim of this study is to investigate the association between executive dysfunction and risk of falling and to determine if this association is independent of balance., Methods: Participants were 188 community-dwelling individuals aged 65 and older. All participants underwent baseline and annual evaluations with review of health history, standardized neurologic examination, neuropsychological testing, and qualitative and quantitative assessment of motor function. Falls were recorded prospectively using weekly online health forms., Results: During 13 months of follow-up, there were 65 of 188 participants (34.6%) who reported at least one fall. Univariate analysis showed that fallers were more likely to have lower baseline scores in executive function than non-fallers (p = 0.03). Among participants without balance impairment we found that higher executive function z-scores were associated with lower fall counts (p = 0.03) after adjustment for age, sex, health status and prior history of falls using negative binomial regression models. This relationship was not present among participants with poor balance., Conclusions: Lower scores on executive function tests are a risk factor for falls in participants with minimal balance impairment. However, this effect is attenuated in individuals with poor balance where physical or more direct motor systems factors may play a greater role in fall risk.

Background: The relationship between gut microbial community composition at the higher-taxonomic order level and local and systemic immunologic abnormalities in HIV disease may provide insight into how bacterial translocation impacts HIV disease., Methods: Antiretroviral-naive patients with HIV underwent upper endoscopy before and 9 months after starting antiretroviral treatment. Duodenal tissue was paraffin-embedded for immunohistochemical analysis and digested for fluorescence activated cell sorting for T-cell subsets and immune activation (CD38+/HLA-DR+) enumeration. Stool samples were provided from patients and control subjects for comparison. Metagenomic microbial DNA was extracted from feces for optimized 16S ribosomal RNA gene (rDNA) real-time quantitative polymerase chain reaction assays designed to quantify panbacterial loads and the relative abundances of proinflammatory Enterobacteriales order and the dominant Bacteroidales and Clostridiales orders., Results: Samples from 10 HIV subjects before initiating and from six subjects receiving antiretroviral treatment were available for analysis. There was a trend for a greater proportion of Enterobacteriales in HIV-positive subjects compared with control subjects (P = 0.099). There were significant negative correlations between total bacterial load and duodenal CD4 and CD8 T-cell activation levels (r = -0.74, P = 0.004 and r = -0.67, P = 0.013, respectively). The proportions of Enterobacteriales and Bacteroidales were significantly correlated with duodenal CD4 T-cell depletion and peripheral CD8 T-cell activation, respectively., Conclusions: These data represent the first report of quantitative molecular and cellular correlations between total/universal and order-level gut bacterial populations and gastrointestinal-associated lymphoid tissue levels of immune activation in HIV-infected subjects. The correlations between lower overall 16S rDNA levels and tissue immune activation suggest that the gut microbiome may contribute to immune activation and influence HIV progression.

Objectives: To describe a longitudinal community cohort study, Intelligent Systems for Assessing Aging Changes, that has deployed an unobtrusive home-based assessment platform in many seniors homes in the existing community., Methods: Several types of sensors have been installed in the homes of 265 elderly persons for an average of 33 months. Metrics assessed by the sensors include total daily activity, time out of home, and walking speed. Participants were given a computer as well as training, and computer usage was monitored. Participants are assessed annually with health and function questionnaires, physical examinations, and neuropsychological testing., Results: Mean age was 83.3 years, mean years of education was 15.5, and 73% of cohort were women. During a 4-week snapshot, participants left their home twice a day on average for a total of 208 min per day. Mean in-home walking speed was 61.0 cm/s. Participants spent 43% of days on the computer averaging 76 min per day., Discussion: These results demonstrate for the first time the feasibility of engaging seniors in a large-scale deployment of in-home activity assessment technology and the successful collection of these activity metrics. We plan to use this platform to determine if continuous unobtrusive monitoring may detect incident cognitive decline.

Background: Some human immunodeficiency virus (HIV)-infected individuals are not able to achieve a normal CD4(+) T cell count despite prolonged, treatment-mediated viral suppression. We conducted an intensification study to assess whether residual viral replication contributes to replenishment of the latent reservoir and whether mucosal HIV-specific T cell responses limit the reservoir size., Methods: Thirty treated subjects with CD4(+) T cell counts of <350 cells/mm(3) despite viral suppression for ≥ 1 year were randomized to add raltegravir (400 mg twice daily) or matching placebo for 24 weeks. The primary end points were the proportion of subjects with undetectable plasma viremia (determined using an ultrasensitive assay with a lower limit of detection of <.3 copy/mL) and a change in the percentage of CD38(+)HLA-DR(+)CD8(+) T cells in peripheral blood mononuclear cells (PBMCs)., Results: The proportion of subjects with undetectable plasma viremia did not differ between the 2 groups (P = .42). Raltegravir intensification did not have a significant effect on immune activation or HIV-specific responses in PBMCs or gut-associated lymphoid tissue., Conclusions: Low-level viremia is not likely to be a significant cause of suboptimal CD4(+) T cell gains during HIV treatment., Clinical Trials Registration: NCT00631449.

We describe a low-cost wearable system that tracks the location of individuals indoors using commonly available inertial navigation sensors fused with radio frequency identification (RFID) tags placed around the smart environment. While conventional pedestrian dead reckoning (PDR) calculated with an inertial measurement unit (IMU) is susceptible to sensor drift inaccuracies, the proposed wearable prototype fuses the drift-sensitive IMU with a RFID tag reader. Passive RFID tags placed throughout the smart-building then act as fiducial markers that update the physical locations of each user, thereby correcting positional errors and sensor inaccuracy. Experimental measurements taken for a 55 m × 20 m 2D floor space indicate an over 1200% improvement in average error rate of the proposed RFID-fused system over dead reckoning alone.

Scratching is a symptom of many dermatological disorders, especially atopic dermatitis. For the development of anti-itch medications, there is a need for objective measures of scratching. Wrist actigraphy (monitoring wrist and hand movements with micro-accelerometers) is a promising method for assessing scratching; however, currently available technology has a limited capacity to discriminate scratching from other similar movements. In this study, we investigated methods to improve the specificity of actigraphy for scratch detection on movement data collected from subjects using the PAM-RL actigraph. A k-means cluster analysis was used to differentiate scratching from walking and restless sleep, which are potential confounds for nighttime scratching. Features used in the analysis include variance, peak frequency, autocorrelation value at one lag, and number of counts above 0.01 g's. The k-means cluster analysis exhibited a high sensitivity (0.90 ± 0.10) and specificity for walking (0.98 ± 0.05) and restless sleep (0.88 ± 0.06), respectively, demonstrating the separability of these activities. This work indicates that the features described here can be used to develop a classifier that discriminates scratch from other activities. The described method of scratch detection shows promise as an objective method for assessing scratching movements in clinical trials and longitudinal studies of scratch.

Sleep is characterized by episodes of immobility interrupted by periods of voluntary and involuntary movement. Increased mobility in bed can be a sign of disrupted sleep that may reduce sleep quality. This paper describes a method for classification of the type of movement in bed using load cells installed at the corners of a bed. The approach is based on Gaussian Mixture Models using a time-domain feature representation. The movement classification system is evaluated on data collected in the laboratory, and it classified correctly 84.6% of movements. The unobtrusive aspect of this approach is particularly valuable for longer-term home monitoring against a standard clinical setting.

In-home monitoring of gait velocity with passive PIR sensors in a smart home has been shown to be an effective method of continuously and unobtrusively measuring this important predictor of cognitive function and mobility. However, passive measurements of velocity are nonspecific with regard to who generated each measurement or walking event. As a result, this method is not suitable for multi-person homes without additional information to aid in the disambiguation of gait velocities. In this paper we propose a method based on Gaussian mixture models (GMMs) combined with infrequent clinical assessments of gait velocity to model in-home walking speeds of two or more residents. Modeling the gait parameters directly allows us to avoid the more difficult problem of assigning each measured velocity individually to the correct resident. We show that if the clinically measured gait velocities of residents are separated by at least 15 cm/s a GMM can be accurately fit to the in-home gait velocity data. We demonstrate the accuracy of this method by showing that the correlation between the means of the GMMs and the clinically measured gait velocities is 0.877 (p value < 0.0001) with bootstrapped 95% confidence intervals of (0.79, 0.94) for 54 measurements of 20 subjects living in multi-person homes. Example applications of using this method to track in-home mean velocities over time are also given.

Ubiquitous and unobtrusive in-home monitoring has the potential to detect physical and mental decline earlier and with higher precision than current clinical methods. However, given that this field is in its infancy, the specific metrics through which these changes are detected are not well defined. The work presented here offers room-transitions, the act of physically moving from one area of a home to another, as a quantifiable measure for total daily activity that can be inferred from a network of passive infrared sensors. We describe a method to calculate this value from raw sensor data and validate this method on an acute health event: an 18-day quarantine at a retirement community that was initiated in the midst of a norovirus outbreak. The results from this case study show that room-transition values increased significantly as subjects remained in their homes during the quarantine, demonstrating a mean increase of 12 transitions per day. Furthermore, a time-adjusted measure of room-transitions is examined that did not significantly change across the group. Finally, the healthy subjects and those that fell ill were analyzed separately, and significant differences were found between them for both the raw and time-adjusted metrics. As detection algorithms improve, these types of measures may be useful in the early detection of a change in health status.

Gait velocity has repeatedly been shown to be an important indicator and predictor of both cognitive and physical function, especially in elderly. However, clinical gait assessments are conducted infrequently and cannot distinguish between abrupt changes in function and changes that occur more slowly over time. Collecting gait measurements continuously in-home has recently been proposed and validated to overcome these clinical limitations. In this paper, we describe the longitudinal analysis of in-home gait velocity collected unobtrusively from passive infrared motion sensors. We first describe a model for the probability density function of the in-home gait velocities. We then describe estimation of the evolution of the density function over time and report empirically determined algorithm parameters that have performed well over a wide variety of different gait velocity data. Finally, we demonstrate how this approach allows detection of significant events (abrupt changes in function) and slower changes over time in gait velocity data collected from a sample of two elderly subjects in the Intelligent Systems for Assessing Aging Changes (ISAAC) study.

Individuals who suffer from acid reflux at night, who snore chronically, or who have sleep apnea are frequently encouraged to sleep in a particular lying position. Side sleeping decreases the frequency and severity of obstructive respiratory events (e.g. apnea and hypopnea) in patients with positional sleep apnea. It has been suggested that individuals with Gastroesophageal Reflux Disease sleep on their left sides in order to help minimize symptoms. In this paper, we present a method of predicting the position of an individual lying on the bed using load cells placed under each of the bed supports. Our results suggest that load cells utilized in this manner could be successfully implemented into a system that tracks or helps train individuals to sleep in a particular lying position.

Gait velocity has been shown to quantitatively estimate risk of future hospitalization, a predictor of disability, and has been shown to slow prior to cognitive decline. In this paper, we describe a system for continuous and unobtrusive in-home assessment of gait velocity, a critical metric of function. This system is based on estimating walking speed from noisy time and location data collected by a "sensor line" of restricted view passive infrared motion detectors. We demonstrate the validity of our system by comparing with measurements from the commercially available GAITRite walkway system gait mat. We present the data from 882 walks from 27 subjects walking at three different subject-paced speeds (encouraged to walk slowly, normal speed, or fast) in two directions through a sensor line. The experimental results show that the uncalibrated system accuracy (average error) of estimated velocity was 7.1 cm/s (SD = 11.3 cm/s), which improved to 1.1 cm/s (SD = 9.1 cm/s) after a simple calibration procedure. Based on the average measured walking speed of 102 cm/s, our system had an average error of less than 7% without calibration and 1.1% with calibration.

Quality of sleep is an important attribute of an individual's health state and its assessment is therefore a useful diagnostic feature. Changes in the patterns of motor activities during sleep can be a disease marker, or can reflect various abnormal physiological and neurological conditions. Presently, there are no convenient, unobtrusive ways to assess quality of sleep outside of a clinic. This paper describes a system for unobtrusive detection of movement in bed that uses load cells installed at the corners of a bed. The system focuses on identifying when a movement occurs based on the forces sensed by the load cells. The movement detection approach estimates the energy in each load cell signal over short segments to capture the variations caused by movement. The accuracy of the detector is evaluated using data collected in the laboratory. The detector is capable of detecting voluntary movements in bed while the subjects were awake, with an average equal error rate of 3.22% (+/-0.54). Its performance is invariant with respect to the individual's characteristics, e.g., weight, as well as those of the bed. The simplicity of the resulting algorithms and their relative insensitivity to the weight and height of the monitored individual make the approach practical and easily deployable in residential and clinical settings.

Highly active antiretroviral therapy (HAART) enables long-term suppression of plasma HIV-1 loads in infected persons, but low-level virus persists and rebounds following cessation of therapy. During HAART, this virus resides in latently infected cells, such as resting CD4(+) T cells, and in other cell types that may support residual virus replication. Therapeutic eradication will require elimination of virus from all reservoirs. We report here a comprehensive analysis of these reservoirs in fluids, cells, and tissues in a rhesus macaque model that mimics HAART in HIV-infected humans. This nonhuman primate model uses RT-SHIV, a chimera of simian immunodeficiency virus containing the HIV-1 reverse transcriptase (RT). Methods were developed for extraction, preamplification, and real-time PCR analyses of viral DNA (vDNA) and viral RNA (vRNA) in tissues from RT-SHIV-infected macaques. These methods were used to identify viral reservoirs in RT-SHIV-infected macaques treated with a potent HAART regimen consisting of efavirenz, emtricitabine, and tenofovir. Plasma virus loads at necropsy ranged from 11 to 28 copies of vRNA per ml. Viral RNA and DNA were detected during HAART, in tissues from numerous anatomical locations. Additional analysis provided evidence for full-length viral RNA in tissues of animals with virus suppressed by HAART. The highest levels of vDNA and vRNA in HAART-treated macaques were in lymphoid tissues, particularly the spleen, lymph nodes, and gastrointestinal tract tissues. This study is the first comprehensive analysis of the tissue and organ distribution of a primate AIDS virus during HAART. These data demonstrate widespread persistence of residual virus in tissues during HAART.

Disrupted sleep patterns are a significant problem in the elderly, leading to increased cognitive dysfunction and risk of nursing home placement. A cost-effective and unobtrusive way to remotely monitor changing sleep patterns over time would enable improved management of this important health problem. We have developed an algorithm to derive sleep parameters such as bed time, rise time, sleep latency, and nap time from passive infrared sensors distributed around the home. We evaluated this algorithm using 404 days of data collected in the homes of 8 elderly community-dwelling elders. Data from this algorithm were highly correlated to ground truth measures (bed mats) and were surprisingly robust to variability in sensor layout and sleep habits.

In this paper we describe a preliminary modeling and analysis of a unique data set comprising unobtrusive and continuous measurements of gait velocity in the elder participants' residences. The data have been collected as a part of a longitudinal study aimed at early detection of cognitive decline. We motivate these analyses by first presenting evidence that suggests significant relationship between gait parameters and cognitive functions. We then describe a simple, model-based approach to the analysis of gait velocity using a weighted correlation function estimates. One of the main challenges is due to the fact that the daily estimates of the gait parameters vary with the number of walks. We illustrate the importance of using weighted as opposed to unweighted estimates on a sample of different houses. The correlation functions appear to capture behavioral differences that can be related to the cognitive functioning of the participants.

A patient's sleep/wake schedule is an important step underlying clinical evaluation of sleep-related complaints. Aspects related to timing of a person's sleep routine provide important clues regarding diagnosis and treatments. Solutions for sleep complaints may sometimes rely solely on changes in habits and life style, based on what is learned from daily rest-activity patterns. This paper describes an approach for determining two states, in-bed and out-of-bed, using load cells under the bed. These states are important because they can help characterize rest-activity patterns at nighttime or detect bed exits in hospitals or nursing homes. The information derived from the load cells is valuable as an objective and continuous measure of daily patterns, and it is particularly valuable in sleep studies in populations who would not be able to remember specific hours to complete sleep diaries. The approach is evaluated on data collected in a laboratory experiment, in a sleep clinic, and also on data collected from residents of an assisted-living facility.

Poor medication adherence is one of the major causes of illness and of treatment failure in the United States. The objective of this study was to conduct an initial evaluation of a context-aware reminder system, which generated reminders at an opportune time to take the medication. Ten participants aged 65 or older, living alone and managing their own medications, participated in the study. Participants took a low-dose vitamin C tablet twice daily at times that they specified. Participants were considered adherent if they took the vitamin within 90 minutes (before or after) of the prescribed time. Adherence and activity in the home was measured using a system of sensors, including an instrumented pillbox. There were three phases of the study: baseline, in which there was no prompting; time-based, in which there was prompting at the prescribed times for pill-taking; and context-aware, in which participants were only prompted if they forgot to take their pills and were likely able to take their pills. The context-based prompting resulted in significantly better adherence (92.3%) as compared to time-based (73.5%) or no prompting (68.1%) conditions (p < 0.0002, chi(2) = 17.0). In addition, subjects had better adherence in the morning than in the evening. We have shown in this study that a system that generates reminders at an opportune time to take the medication significantly improves adherence. This study indicates that context-aware prompting may provide improved adherence over standard time-based reminders.

Objective: This was a cross-sectional study of the ability of independently living healthy elders to follow a medication regimen. Participants were divided into a group with High Cognitive Function (HCF) or Low Cognitive Function (LCF) based on their scores on the ADAS-Cog., Method: Thirty-eight participants aged 65 or older and living independently in the community followed a twice-daily vitamin C regimen for 5 weeks. Adherence was measured using an electronic 7-day pillbox., Results: The LCF group had significantly poorer total adherence than the HCF group (LCF: 63.9 +/- 11.2%, HCF: 86.8 +/- 4.3%, t( 36) = 2.57, p = .007), and there was a 4.1 relative risk of non-adherence in the LCF group as compared to the HCF group., Discussion: This study has important implications for the conduct of clinical drug trials, as it provides strong evidence that even very mild cognitive impairment in healthy elderly has a detrimental impact on medication adherence.

Today most conclusions about cumulative knowledge in psychology are based on meta-analysis. We first present an examination of the important statistical differences between fixed-effects (FE) and random-effects (RE) models in meta-analysis and between two different RE procedures, due to Hedges and Vevea, and to Hunter and Schmidt. The implications of these differences for the appropriate interpretation of published meta-analyses are explored by applying the two RE procedures to 68 meta-analyses from five large meta-analytic studies previously published in Psychological Bulletin. Under the assumption that the goal of research is generalizable knowledge, results indicated that the published FE confidence intervals (CIs) around mean effect sizes were on average 52% narrower than their actual width, with similar results being produced by the two RE procedures. These nominal 95% FE CIs were found to be on average 56% CIs. Because most meta-analyses in the literature use FE models, these findings suggest that the precision of meta-analysis findings in the literature has often been substantially overstated, with important consequences for research and practice.

Walking speed and activity are important measures of functional ability in the elderly. Our earlier studies have suggested that continuous monitoring may allow us to detect changes in walking speed that are also predictive of cognitive changes. We evaluated the use of passive infrared (PIR) sensors for measuring walking speed in the home on an ongoing basis. In comparisons with gait mat estimates (ground truth) and the results of a timed walk test (the clinical gold standard) in 18 subjects, we found that the clinical measure overestimated typical walking speed, and the PIR sensor estimations of walking speed were highly correlated to actual gait speed. Examination of in-home walking patterns from more than 100,000 walking speed samples for these subjects suggested that we can accurately assess walking speed in the home. We discuss the potential of this approach for continuous assessment.

Accurate assessment of mobility in bed presents challenges to clinicians and researchers alike. Mobility is traditionally assessed by either overnight polysomnograph recording or wrist actigraphy. This paper describes an alternative system for unobtrusive and continuous monitoring of sleep movements that uses load sensors installed at the corners of a bed. This work is focused on the detection and classification of clinically relevant types of movement based on the forces sensed by load cells. The accuracy of the system for detecting movement has been evaluated using data collected in a laboratory setting. We also present a comparison of the proposed system with wrist-actigraphy.

Sleep disturbances are prevalent, financially taxing, and have a negative effect on health and quality of life. One of the most common sleep disturbances is obstructive sleep apnea-hypopnea syndrome (OSAHS) which frequently goes undiagnosed. The gold standard for diagnosing OSAHS is polysomnography (PSG)-a procedure that is inconvenient, time-consuming, and interferes with normal sleep patterns. We are investigating an alternative to PSG in which unobtrusive load cells fitted under the bed are used to monitor movement, heart rate, and respiration. In this paper we describe how load cell data can be used to distinguish between clinically relevant disordered breathing (apneas and hypopneas) and normal respiration. The method correctly classified disordered breathing segments with a sensitivity of 0.77 and a specificity of 0.91.