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Effect of wearable sensor dynamics on physical activity estimates: A comparison between SCI vs. healthy individuals.
Jayaraman, C, Mummidisetty, CK, Jayaraman, A
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2016;:3282-3285
Abstract
Accuracy of physical activity estimates predicted by activity monitoring technologies may be affected by device location, analysis algorithms, type of technology (i.e. wearable/stickable) and population demographics (disability) being studied. Consequently, the main purpose of this investigation was to study such sensor dynamics (i.e. effect of device location, type and population demographics on energy expenditure estimates) of two commercial activity monitors. It was hypothesized that device location, population studied (disability), choice of proprietary algorithm and type of technology used will significantly impact the accuracy of the predicted physical activity metrics. 10 healthy controls and eight individuals with spinal cord injury (SCI) performed structured activities in a laboratory environment. All participants wore, (i) three ActiGraph-G3TX's one each on their wrist, waist & ankle, (ii) a stickable activity monitor (Metria-IH1) on their upper-arm and (3) a Cosmed-K4B2 metabolic unit, while performing sedentary (lying), low intensity (walk 50 steps at self-speed) and vigorous activity (a 6 minute walk test). To validate the hypothesis, the energy expenditures (EE) predicted by ActiGraph-GT3X and Metria-IH1 were benchmarked with estimated EE per Cosmed K4B2 metabolic unit. To verify the step count accuracy predicted by ActiGraph-GT3X's and Metria-IH1, the manually calculated step count during the low intensity activity were compared to estimates from both devices. Results suggest that Metria-IH1 out-performed ActiGraph-GT3X in estimating EE during sedentary activity in both groups. The device location and population demographics, significantly affected the accuracy of predicted estimates. In conclusion, selecting activity monitor locations, analysis algorithm and choice of technology plays based on the movement threshold of population being studied can pave a better way for reliable healthcare decisions and data analytics in population with SCI.
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The use of a portable breath analysis device in monitoring type 1 diabetes patients in a hypoglycaemic clamp: validation with SIFT-MS data.
Walton, C, Patel, M, Pitts, D, Knight, P, Hoashi, S, Evans, M, Turner, C
Journal of breath research. 2014;(3):037108
Abstract
Monitoring blood glucose concentrations is a necessary but tedious task for people suffering from diabetes. It has been noted that breath in people suffering with diabetes has a different odour and thus it may be possible to use breath analysis to monitor the blood glucose concentration. Here, we evaluate the analysis of breath using a portable device containing a single mixed metal oxide sensor during hypoglycaemic glucose clamps and compare that with the use of SIFT-MS described in previously published work on the same set of patients. Outputs from both devices have been correlated with the concentration of blood glucose in eight volunteers suffering from type 1 diabetes mellitus. The results demonstrate that acetone as measured by SIFT-MS and the sensor output from the breath sensing device both correlate linearly with blood glucose; however, the sensor response and acetone concentrations differ greatly between patients with the same blood glucose. It is therefore unlikely that breath analysis can entirely replace blood glucose testing.
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Noninvasive blood glucose monitoring during oral intake of different sugars with optical coherence tomography in human subjects.
Zhang, Y, Wei, H, Yang, H, He, Y, Wu, G, Xie, S, Zhu, Z, He, R
Journal of biophotonics. 2013;(9):699-707
Abstract
The potential of OCT applied to noninvasive blood glucose monitoring has attracted significant efforts. In this work we investigated the feasibility of OCT in monitoring blood glucose during oral intake of different sugars in humans. Five groups of experiments were performed, in which different sugars were used. The OCT signal slope (OCTSS) changed with variation of blood glucose concentration (BGC). A good correlation between OCTSS and BGC was observed in these experiments. The averaged correlation coefficients R between OCTSS and BGC are 0.900, 0.836, 0.895 and 0.884, corresponding to oral administration of glucose, fructose, sucrose and mixed sugar, respectively. Our studies demonstrated the capability and accuracy of the OCT system in monitoring BGC noninvasively and it could become a powerful tool in daily blood glucose monitoring for patients.
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Coregulated approach to feeding preterm infants with lung disease: effects during feeding.
Thoyre, SM, Holditch-Davis, D, Schwartz, TA, Melendez Roman, CR, Nix, W
Nursing research. 2012;(4):242-51
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Abstract
BACKGROUND Very preterm (VP) infants are at risk for poor oral feeding endurance, early cessation of eating, poor fluid management with aspiration risk, behavioral distress, and unstable heart rate (HR) and oxygenation during feeding. OBJECTIVE The study aims to determine the preliminary effectiveness of a coregulated approach (CoReg) to oral feeding for VP infants at risk for lung disease. METHODS A randomized, within-subject, cross-over design was used with 20 VP infants requiring oxygen at the start of oral feeding. Infants were bottle-fed by the Usual Care approach and by the CoReg approach on two consecutive days for an average of four feedings each. Intervention components included coregulation of suck, swallow, and breathe rhythms using enhanced auditory assessment, infant-guided feeding onsets, and infant positioning in a semielevated, side-lying position. Infant physiology metrics (HR and SaO2) were collected continuously before and during the feeding. Behavioral and auditory indicators of regulation were coded continuously from videotape during the feeding. RESULTS Up to 75 feedings were analyzed (40 Usual Care and 35 CoReg) using repeated measures modeling. CoReg feedings were characterized by more frequent preparation of the infant for the feeding, were more commonly initiated in response to infant readiness cues, had more rest periods and breath regulation events, and had fewer sucking stimulation events. CoReg feedings had less SaO2 variability, decline, and time spent in a desaturated state; less HR fluctuation and decline; less behavioral disorganization; better fluid management; and less observed effort to breathe. DISCUSSION Support is provided for an approach to feeding vulnerable infants. Enhanced auditory assessment of infant feeding rhythms increases the responsiveness of the feeder and improves infant behavioral and physiological responses.
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Food intake monitoring: an acoustical approach to automated food intake activity detection and classification of consumed food.
Päßler, S, Wolff, M, Fischer, WJ
Physiological measurement. 2012;(6):1073-93
Abstract
Obesity and nutrition-related diseases are currently growing challenges for medicine. A precise and timesaving method for food intake monitoring is needed. For this purpose, an approach based on the classification of sounds produced during food intake is presented. Sounds are recorded non-invasively by miniature microphones in the outer ear canal. A database of 51 participants eating seven types of food and consuming one drink has been developed for algorithm development and model training. The database is labeled manually using a protocol with introductions for annotation. The annotation procedure is evaluated using Cohen's kappa coefficient. The food intake activity is detected by the comparison of the signal energy of in-ear sounds to environmental sounds recorded by a reference microphone. Hidden Markov models are used for the recognition of single chew or swallowing events. Intake cycles are modeled as event sequences in finite-state grammars. Classification of consumed food is realized by a finite-state grammar decoder based on the Viterbi algorithm. We achieved a detection accuracy of 83% and a food classification accuracy of 79% on a test set of 10% of all records. Our approach faces the need of monitoring the time and occurrence of eating. With differentiation of consumed food, a first step toward the goal of meal weight estimation is taken.
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Blood glucose controller for neonatal intensive care: virtual trials development and first clinical trials.
Le Compte, A, Chase, JG, Lynn, A, Hann, C, Shaw, G, Wong, XW, Lin, J
Journal of diabetes science and technology. 2009;(5):1066-81
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Abstract
BACKGROUND Premature neonates often experience hyperglycemia, which has been linked to worsened outcomes. Insulin therapy can assist in controlling blood glucose (BG) levels. However, a reliable, robust control protocol is required to avoid hypoglycemia and to ensure that clinically important nutrition goals are met. METHODS This study presents an adaptive, model-based predictive controller designed to incorporate the unique metabolic state of the neonate. Controller performance was tested and refined in virtual trials on a 25-patient retrospective cohort. The effects of measurement frequency and BG sensor error were evaluated. A stochastic model of insulin sensitivity was used in control to provide a guaranteed maximum 4% risk of BG < 72 mg/dl to protect against hypoglycemia as well as account for patient variability over 1-3 h intervals when determining the intervention. The resulting controller is demonstrated in two 24 h clinical neonatal pilot trials at Christchurch Women's Hospital. RESULTS Time in the 72-126 mg/dl BG band was increased by 103-161% compared to retrospective clinical control for virtual trials of the controller, with fewer hypoglycemic measurements. Controllers were robust to BG sensor errors. The model-based controller maintained glycemia to a tight target control range and accounted for interpatient variability in patient glycemic response despite using more insulin than the retrospective case, illustrating a further measure of controller robustness. Pilot clinical trials demonstrated initial safety and efficacy of the control method. CONCLUSIONS A controller was developed that made optimum use of the very limited available BG measurements in the neonatal intensive care unit and provided robustness against BG sensor error and longer BG measurement intervals. It used more insulin than typical sliding scale approaches or retrospective hospital control. The potential advantages of a model-based approach demonstrated in simulation were applied to initial clinical trials.
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Long-term monitoring of patients with infantile-onset Pompe disease on enzyme replacement therapy using a urinary glucose tetrasaccharide biomarker.
Young, SP, Zhang, H, Corzo, D, Thurberg, BL, Bali, D, Kishnani, PS, Millington, DS
Genetics in medicine : official journal of the American College of Medical Genetics. 2009;(7):536-41
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Abstract
PURPOSE To investigate the correlation of the urinary glucose tetrasaccharide, Glcalpha1-6Glcalpha1-4Glcalpha1-4Glc, (Glc4) with skeletal muscle glycogen content and the long-term clinical response to enzyme replacement therapy with recombinant human acid alpha glucosidase in infantile Pompe disease. METHODS Eighteen patients, < or =6 months old, were enrolled in a clinical trial of enzyme replacement therapy for up to 142 weeks. Urinary Glc4, skeletal muscle glycogen, and other clinical and laboratory assessments were made at baseline and at regular intervals. Urinary Glc4 was determined using an isotope-dilution tandem mass spectrometric assay. The clinical response to treatment was defined according to the motor function response. Trends in urinary Glc4 were correlated with the clinical response and compared with serum enzyme markers of skeletal muscle damage, creatine kinase, aspartate aminotransferase, and alanine aminotransferase. RESULTS Urinary Glc4, in contrast to the serum markers, correlated closely with skeletal muscle glycogen content and with the clinical response. Patients with the best response to treatment maintained the lowest levels of Glc4 throughout the trial. CONCLUSION The results from this study support the use of urinary Glc4 for monitoring patients with infantile-onset Pompe disease on therapy.
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Optical dialysis adequacy sensor: wavelength dependence of the ultra violet absorbance in the spent dialysate to the removed solutes.
Jerotskaja, J, Lauri, K, Tanner, R, Luman, M, Fridolin, I
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2007;:2960-3
Abstract
A need for dialysate-based, on-line, continuous monitoring systems for the control of dialysis efficiency and the prevention of dialysis-associated complications is arisen due to increasing number of dialysis patients and related treatment quality requirements. The aim of this study was to investigate the wavelength dependence between the the ultra-violet (UV) absorbance in the spent dialysate and the retained solutes removed during the hemodialysis in order to explain possibilities to estimate removal of the solutes by the optical dialysis adequacy sensor. Ten uremic patients, during 30 hemodialysis treatments, were followed at the Department of Dialysis and Nephrology, North-Estonian Regional Hospital. The dialysate samples were taken and analyzed with spectrophotometer to get absorbance spectra. The results confirm previous studies considering similarity for the UV-spectrum on the spent dialysate samples during a single dialysis session indicating presence of the same type of chromophores in the spent dialysate removed from the patient's blood for different patients groups. At the same time the highest correlation in the spent dialysate for urea, creatinine, potassium, and phosphate was obtained at the wavelength 237 nm that is a new finding compared to earlier results. The highest correlation between the UV-absorbance and uric acid in the spent dialysate was obtained at the wavelength 294 nm. Presence of at least two different wavelength ranges may add selectivity for monitoring several compounds. Our study indicates that the technique has a potential to estimate the removal of retained substances.
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Associations between particulate sulfate and organic carbon exposures and heart rate variability in patients with or at risk for cardiovascular diseases.
Chuang, KJ, Chan, CC, Su, TC, Lin, LY, Lee, CT
Journal of occupational and environmental medicine. 2007;(6):610-7
Abstract
OBJECTIVE It is still unknown whether specific components in fine particles are associated with heart rate variability (HRV) reduction. METHODS We recruited 46 patients with or at risk for cardiovascular diseases to measure 24-hour HRV by ambulatory electrocardiographic monitoring. Fixed-site air-monitoring stations were used to represent participants' exposures to particles with aerodynamic diameters less than 10 microm (PM 10) and 2.5 microm (PM2.5), and particulate components of sulfate, nitrate, organic carbon (OC) and elemental carbon, and gaseous pollutants. RESULTS We found that HRV reduction was associated with sulfate, OC, and PM2.5 but not with the other five pollutants in single-pollutant models. Sulfate was found to remain in significant association with HRV reduction adjusting for OC and PM2.5 in three-pollutant models. CONCLUSIONS Exposures to sulfate and OC in PM2.5 were associated with HRV reduction in patients with or at risk for cardiovascular diseases.
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Using pedometers to promote physical activity among working urban women.
Garbers, S, Nelson, JA, Rosenberg, T, Chiasson, MA
Preventing chronic disease. 2006;(2):A67