Principles for Designing Context-Aware Applications for Physical Activity Promotion

Mobile devices with embedded sensors have become commonplace, carried by billions of people worldwide. Their potential to influence positive health behaviors such as physical activity in people is just starting to be realized. Two critical ingredients, an accurate understanding of human behavior and use of that knowledge for building computational models, underpin all emerging behavior change applications. Early research prototypes suggest that such applications would facilitate people to make difficult decisions to manage their complex behaviors. However, the progress towards building real-world systems that support behavior change has been much slower than expected. The extreme diversity in real-world contextual conditions and user characteristics has prevented the conception of systems that scale and support end-users’ goals. We believe that solutions to the many challenges of designing context-aware systems for behavior change exist in three areas: building behavior models amenable to computational reasoning, designing better tools to improve our understanding of human behavior, and developing new applications that scale existing ways of achieving behavior change. With physical activity as its focus, this thesis addresses some crucial challenges that can move the field forward. Specifically, this thesis provides the notion of sweet spots, a phenomenological account of how people make and execute their physical activity plans. The key contribution of this concept is in its potential to improve the predictability of computational models supporting physical activity planning. To further improve our understanding of the dynamic nature of human behavior, we designed and built Heed, a low-cost, distributed and situated self-reporting device. Heed’s single-purpose and situated nature proved its use as the preferred device for self-reporting in many contexts. We finally present a crowdsourcing system that leverages expert knowledge to write personalized behavior change messages for large-scale context-aware applications.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144089/1/gparuthi_1.pd

Estimation of sleep recovery in shift working long-haul truck drivers – A heart rate variability based study

Prolonged work hours, shortened and irregular sleep patterns often leads to inadequate recovery in shift workers resulting in increased sleepiness or fatigue during the day. Heart rate and heart rate variability (HRV) have been often used in occupational health studies to examine sleep quality and recovery. The aim of the current study was to determine the factors affecting the recovery process in shift working long-haul truck drivers and to as-sess the impact different shifts have on the drivers’ sleep health. Of the recruited volunteers, data collected from 38 volunteers (Age: 38.46 ± 10.89 years) satisfied the inclusion criteria for this study. Driver demographics and background questionnaires were obtained prior to measurements. R-R intervals and actigraphy data were collected for three intensive measurement days (non-night shift, night shift and lei-sure day) and subjective measures of sleep quality, recorded on the sleep-diary, were used for the analyses. Several time- and frequency-domain HRV indices were calculated in 10-minute segments and averaged on an hourly basis and for the entire duration of sleep. All tests for statistical significance was conducted on a within-subject basis. Comparison of HRV indices over the entire sleep duration recorded on different in-tensive measurement days revealed no significant differences except for LF/HF ratio (Lei-sure day vs. Night shift, p <0.05). Sleep duration and efficiency were significantly lower on duty days. Regression analyses indicated VLF power was strong predictor of recovery and 31% of the outcome was influenced by explanatory factors. SDNN (r = 0.555, ad-justed r2 = 0.248, F(9, 92) = 5.166, p <0.001), RMSSD (r = 0.414, adjusted r2 = 0.131, F(9.92) = 4.229, p <0.05) and HF power (r = 0.460, adjusted r2 = 0.165, F(9.92) = 4.526, p <0.001) were significantly associated with age and sleep duration. Short-term variabil-ity indices, RMSSD and HF power, were moderately influenced by diurnal variations. The results suggest that despite the fact that shift type does not have any direct con-sequences on sleep recovery, the odd work hours and irregular sleep schedules pose an indirect effect. The truncated sleep length, especially seen after night shift work, have been significantly associated with the impaired recovery and is contributed to by other short-term (diurnal variations) and long-term (ageing) factors. These results provide a basis for planning shift schedules such that direct or indirect manifestations of shift type-related influence on recovery are mitigated

Unsupervised Heart-rate Estimation in Wearables With Liquid States and A Probabilistic Readout

Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine intelligent approach for heart-rate estimation from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach lies in (1) encoding spatio-temporal properties of ECG signals directly into spike train and using this to excite recurrently connected spiking neurons in a Liquid State Machine computation model; (2) a novel learning algorithm; and (3) an intelligently designed unsupervised readout based on Fuzzy c-Means clustering of spike responses from a subset of neurons (Liquid states), selected using particle swarm optimization. Our approach differs from existing works by learning directly from ECG signals (allowing personalization), without requiring costly data annotations. Additionally, our approach can be easily implemented on state-of-the-art spiking-based neuromorphic systems, offering high accuracy, yet significantly low energy footprint, leading to an extended battery life of wearable devices. We validated our approach with CARLsim, a GPU accelerated spiking neural network simulator modeling Izhikevich spiking neurons with Spike Timing Dependent Plasticity (STDP) and homeostatic scaling. A range of subjects are considered from in-house clinical trials and public ECG databases. Results show high accuracy and low energy footprint in heart-rate estimation across subjects with and without cardiac irregularities, signifying the strong potential of this approach to be integrated in future wearable devices.Comment: 51 pages, 12 figures, 6 tables, 95 references. Under submission at Elsevier Neural Network

Signaling by FGF4 and FGF8 is required for axial elongation of the mouse embryo

AbstractFibroblast growth factor (FGF) signaling has been shown to play critical roles in vertebrate segmentation and elongation of the embryonic axis. Neither the exact roles of FGF signaling, nor the identity of the FGF ligands involved in these processes, has been conclusively determined. Fgf8 is required for cell migration away from the primitive streak when gastrulation initiates, but previous studies have shown that drastically reducing the level of FGF8 later in gastrulation has no apparent effect on somitogenesis or elongation of the embryo. In this study, we demonstrate that loss of both Fgf8 and Fgf4 expression during late gastrulation resulted in a dramatic skeletal phenotype. Thoracic vertebrae and ribs had abnormal morphology, lumbar and sacral vertebrae were malformed or completely absent, and no tail vertebrae were present. The expression of Wnt3a in the tail and the amount of nascent mesoderm expressing Brachyury were both severely reduced. Expression of genes in the NOTCH signaling pathway involved in segmentation was significantly affected, and somite formation ceased after the production of about 15–20 somites. Defects seen in the mutants appear to result from a failure to produce sufficient paraxial mesoderm, rather than a failure of mesoderm precursors to migrate away from the primitive streak. Although the epiblast prematurely decreases in size, we did not detect evidence of a change in the proliferation rate of cells in the tail region or excessive apoptosis of epiblast or mesoderm cells. We propose that FGF4 and FGF8 are required to maintain a population of progenitor cells in the epiblast that generates mesoderm and contributes to the stem cell population that is incorporated in the tailbud and required for axial elongation of the mouse embryo after gastrulation

Ionization Constants of Some Hydroxycoumarins in Dioxane-Water & Ethanol- Water Media

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Unilateral absence of pulmonary artery: a radiographically occult cause of life-threatening hemoptysis

Unilateral absence or agenesis of pulmonary artery (UAPA) is a rare congenital abnormality with an estimated prevelance of 1 in 2,00,000 adults. The entity occurs commonly in association with other congenital heart diseases like septal defects or patent ductus arteriosus. The condition usually runs a benign clinical course with patients usually presenting clinically in adulthood with history of recurrent respiratory tract infections. Two such patients presented with recurrent respiratory tract infections, breathlessness and hemoptysis. The chest radiograph of first patient was reported as normal in the referring hospital, while that of second patient showed volume loss in left lung. CT Pulmonary Angiography (CTPA) was then performed which demonstrated the absence of right and left pulmonary arteries respectively in the first and second patients. Pulmonary artery branches were reformed distally by multiple collaterals arising from systemic arteries. The entire spectrum, including embryology, imaging features and management of UAPA are discussed. UAPA remains a potential cause for life-threatening hemoptysis, due to extensive collateralization associated with the condition. It is important for radiologists to be aware of this uncommon entity in order to suspect it on a routine chest radiograph, diagnose it and map associated collaterals on CTPA and also embolize the bleeding collaterals

An observational study of the healing time, associated factors, and complications during non-operative management of patients with blunt abdominal trauma

Background: Non-operative management (NOM) has shown success in the management of cases of blunt abdominal trauma (BAT), especially in hemodynamically stable patients, even if there is a higher grade of injury.Objectives: The aim of this study was to determine the healing rate with NOM and associated risk factors of non-healing in patients with BAT.Methods: This prospective study was conducted on 20 hemodynamically stable patients of BAT who were treated in a tertiary care hospital by NOM. Clinical monitoring and biochemical investigations were done. The patients were followed-up for three months. The outcome measures were the average time of healing and complications. A p-value less than 0.05 was considered statistically significant.Results: The mean age of the patients was 24.5 years with 18 (90%) males and 2(10%) females. Nine patients (45%) had isolated liver injury, 8 (40%) had isolated splenic injury, 1 (5%) had isolated left renal injury, 1 (5%) had combined liver and splenic injury and 1 (5%) had combined liver and right renal injury. At 3 months of follow-up, 16 (80%) cases showed complete healing, 3(15%) showed incomplete healing and 1 (5%) patient with grade 4 splenic injury had failure of NOM. On performing univariate regression analysis, grade 3/4 was an independent risk factor of non-healing with an odds ratio of 5.667.Conclusion: In conclusion, NOM appears to be a safe and effective management protocol for patients with BAT, provided regular follow-ups and monitoring are done

Engaging consumers via online brand communities to achieve brand love and positive recommendations

Purpose – This study aims to investigate the influence of brand relationship quality and consumer community identification on consumer engagement. This study also examines the mediating role of consumer engagement between brand relationship quality and consumer community identification with brand love. Positive word of mouth is taken as an outcome variable. Design/methodology/approach – To test the proposed relationships, data were collected from 580 social media-based brand community followers and analysed through structural equation modelling. Findings – Results corroborate brand relationship quality and consumer community identification as critical drivers of consumer engagement on the online platforms. The results further reveal a positive association between consumer engagement and brand love which consequently foster positive word of mouth. The findings also corroborate the partial as well as full mediating role of consumer engagement on different proposed associations. Originality/value – This study offers an in-depth insight of specific motivations to engage consumers in the virtual domain, make them adore their brands and spread a positive word. All of these outcomes are crucial in offering competitive advantages to firms. This study validates the relevance of consumer engagement interactions in contemporary firms’ relationship marketing strategies

Mobile Phone Buying Decisions Among Young Adults: An Empirical Study of Influencing Factors

Background: The mobile phone shopping behavior of adults has been extensively studied in the past. However, given the novelty and dynamism of this domain and the multitude of new contributing factors coming into play, such studies soon become obsolete. Consequently, this phenomenon needs to be studied frequently within the context of contemporary social, technological, and market norms. In the same league, there is a pressing need to empirically examine the mobile shopping behavior of young adults in Pakistan. In this context, the last known such study was published in 2008. This paper provides a study of factors influencing mobile phone shopping behavior within the context of young adults in Pakistan. Methods: A questionnaire-based survey consisting of a five-point Likert scale was conducted. The survey was disseminated via social media, and participation was voluntary. Over a period of two weeks, 416 respondents completed the survey to report mobile shopping behavior. We employed Confirmatory Factor Analysis (CFA) within the Structured Equation Modeling (SEM) model using AMOS 24. We chose CFA over Ordinary Least Squares (OLS) because the application of OLS is limited by compliance to simplifying assumptions. In contrast, SEM-CFA is a more robust method that also addresses the issue of multicollinearity, a common problem in survey data. Findings: The empirical results suggest that the Service Encounter and Convenience have coefficients of 0.049 [P=0.265] and 0.02 [P=0.682] only, suggesting a statistically insignificant influence of the two factors on the mobile phone buying behavior. Similarly, Avoidance of Core Service Failure and Response only has a coefficient -0.05 [P=0.401], suggesting a feeble and statistically insignificant negative effect on the mobile phone buying behavior in Pakistan. However, Price and Attractiveness have been found to have coefficients of 0.436 [P=0.00] and 0.155 [P=0.00], indicating that these two key factors are having a positive and significant influence on the mobile phone buying behavior in young adults in Pakistan. Contribution: The finding reveals mobile shopping behavior of young Pakistani adults might not be influenced by either Service Encounter or Convenience. Instead, the Price and Attractiveness of the mobile phone seem to affect the adults towards buying the mobile phone. Recommendations: The price of the mobile phones needs to follow the target market, and the product category should also be identified according to the characteristics of the target market. In addition, the attractiveness of the mobile phone needs to be maintained even if the prices are lower, as this should positively influence the buyers. Further research is suggested to include cultural and social factors in this context