Efficient Personalized Learning for Wearable Health Applications using HyperDimensional Computing

Health monitoring applications increasingly rely on machine learning techniques to learn end-user physiological and behavioral patterns in everyday settings. Considering the significant role of wearable devices in monitoring human body parameters, on-device learning can be utilized to build personalized models for behavioral and physiological patterns, and provide data privacy for users at the same time. However, resource constraints on most of these wearable devices prevent the ability to perform online learning on them. To address this issue, it is required to rethink the machine learning models from the algorithmic perspective to be suitable to run on wearable devices. Hyperdimensional computing (HDC) offers a well-suited on-device learning solution for resource-constrained devices and provides support for privacy-preserving personalization. Our HDC-based method offers flexibility, high efficiency, resilience, and performance while enabling on-device personalization and privacy protection. We evaluate the efficacy of our approach using three case studies and show that our system improves the energy efficiency of training by up to $45.8\times$ compared with the state-of-the-art Deep Neural Network (DNN) algorithms while offering a comparable accuracy

Edge-centric Optimization of Multi-modal ML-driven eHealth Applications

Smart eHealth applications deliver personalized and preventive digital healthcare services to clients through remote sensing, continuous monitoring, and data analytics. Smart eHealth applications sense input data from multiple modalities, transmit the data to edge and/or cloud nodes, and process the data with compute intensive machine learning (ML) algorithms. Run-time variations with continuous stream of noisy input data, unreliable network connection, computational requirements of ML algorithms, and choice of compute placement among sensor-edge-cloud layers affect the efficiency of ML-driven eHealth applications. In this chapter, we present edge-centric techniques for optimized compute placement, exploration of accuracy-performance trade-offs, and cross-layered sense-compute co-optimization for ML-driven eHealth applications. We demonstrate the practical use cases of smart eHealth applications in everyday settings, through a sensor-edge-cloud framework for an objective pain assessment case study

Adaptation to Motherhood and Its Influential Factors in the First Year Postpartum in Iranian Primiparous

Background: Postpartum is a significant transition period for women and could be markedly stressful. Postpartum stress is a well-established risk factor for poor parenting practices and inadequate mother-infant interaction. Objectives: The present study aimed to assess adaptation to motherhood and its influential factors in the first year postpartum in Iranian women. Methods: This cross-sectional study was performed in an urban area in the north of Iran. Inclusion criteria were age of more than 18 years, primiparous women, having healthy children in less than one year postpartum, Persian literacy, and willingness to participate in the research. Ill and disabled women, those with a history of depression, and high-risk pregnancies were excluded from the study. Convenience sampling was employed in seven health centers, and 536 subjects were selected. Data were collected using the scale of the experiences of Iranian first-time mothers in maternal role adaptation and demographic questionnaires. Data analysis was performed using descriptive statistics and regression and ordinal logistic regression. Results: None of the women had poor adaptation to motherhood. In addition, 2.6% of the subjects had average adaptation, 78.8% had good adaptation, and 18.6% had excellent adaptation. According to the logistic regression results, favorable economic status increased the possibility of appropriate adaptation by twice (OR=2.03; CI: 1.3-3.004; P<0.001). Conclusion: Provision of proper counseling services requires the recognition of the influential factors in adaptation to motherhood. According to the results, adaption of women to motherhood in the first year postpartum largely depends on the economic support of the mother and infant

Molecular assay on Crimean Congo Hemorrhagic Fever virus in ticks (Ixodidae) collected from Kermanshah Province, Western Iran

Background: Crimean-Congo Hemorrhagic Fever (CCHF) is a feverous and hemorrhagic disease endemic in some parts of Iran and caused by an arbovirus related to Bunyaviridae family and Nairovirusgenus. The main virus reservoir in the nature is ticks, however small vertebrates and a wide range of domestic and wild animals are regarded as reservoir hosts. This study was conducted to determine the infection rate of CCHF virus in hard ticks of Sarpole- Zahab County, Kermanshah province, west of Iran. Methods: From total number of 851 collected ticks from 8 villages, 131 ticks were selected randomlyand investigated for detection of CCHF virus using RT-PCR. Results: The virus was found in 3.8 of the tested ticks. Hyalommaanatolicum, H.asiaticum and Rhipicephalus sanguineus species were found to have viral infection, with the highest infection rate (11.11) in Rh. sanguineus. Conclusion: These findings provide epidemiological evidence for planning control strategies of the disease in the study area

A Bispecific Antibody Based Assay Shows Potential for Detecting Tuberculosis in Resource Constrained Laboratory Settings

The re-emergence of tuberculosis (TB) as a global public health threat highlights the necessity of rapid, simple and inexpensive point-of-care detection of the disease. Early diagnosis of TB is vital not only for preventing the spread of the disease but also for timely initiation of treatment. The later in turn will reduce the possible emergence of multi-drug resistant strains of Mycobacterium tuberculosis. Lipoarabinomannan (LAM) is an important non-protein antigen of the bacterial cell wall, which is found to be present in different body fluids of infected patients including blood, urine and sputum. We have developed a bispecific monoclonal antibody with predetermined specificities towards the LAM antigen and a reporter molecule horseradish peroxidase (HRPO). The developed antibody was subsequently used to design a simple low cost immunoswab based assay to detect LAM antigen. The limit of detection for spiked synthetic LAM was found to be 5.0 ng/ml (bovine urine), 0.5 ng/ml (rabbit serum) and 0.005 ng/ml (saline) and that for bacterial LAM from M. tuberculosis H37Rv was found to be 0.5 ng/ml (rabbit serum). The assay was evaluated with 21 stored clinical serum samples (14 were positive and 7 were negative in terms of anti-LAM titer). In addition, all 14 positive samples were culture positive. The assay showed 100% specificity and 64% sensitivity (95% confidence interval). In addition to good specificity, the end point could be read visually within two hours of sample collection. The reported assay might be used as a rapid tool for detecting TB in resource constrained laboratory settings

Ebola GP-Specific Monoclonal Antibodies Protect Mice and Guinea Pigs from Lethal Ebola Virus Infection

Ebola virus (EBOV) causes acute hemorrhagic fever in humans and non-human primates with mortality rates up to 90%. So far there are no effective treatments available. This study evaluates the protective efficacy of 8 monoclonal antibodies (MAbs) against Ebola glycoprotein in mice and guinea pigs. Immunocompetent mice or guinea pigs were given MAbs i.p. in various doses individually or as pools of 3–4 MAbs to test their protection against a lethal challenge with mouse- or guinea pig-adapted EBOV. Each of the 8 MAbs (100 µg) protected mice from a lethal EBOV challenge when administered 1 day before or after challenge. Seven MAbs were effective 2 days post-infection (dpi), with 1 MAb demonstrating partial protection 3 dpi. In the guinea pigs each MAb showed partial protection at 1 dpi, however the mean time to death was significantly prolonged compared to the control group. Moreover, treatment with pools of 3–4 MAbs completely protected the majority of animals, while administration at 2–3 dpi achieved 50–100% protection. This data suggests that the MAbs generated are capable of protecting both animal species against lethal Ebola virus challenge. These results indicate that MAbs particularly when used as an oligoclonal set are a potential therapeutic for post-exposure treatment of EBOV infection

Production of Coturnix quail immunoglobulins Y (IgYs) against Vibrio parahaemolyticus and Vibrio vulnificus

This research article published by Springer Nature Switzerland AG., 2011Production of chicken immunoglobulins Y (IgYs) and their applications in prophylactic, therapeutic, detection of microbial contaminants and as a diagnostic tool has been widely studied with limited information from other avians. This study produced Coturnix quail (Coturnix coturnix japonica) egg yolk IgYs against Vibrio parahaemolyticus and Vibrio vulnificus. Formalin inactivated (FIVP, FIVV, mixed FI-VP/VV) and heat inactivated (HIVP, HIVV, mixed HI-VP/VV) Vibrio immunogens (109 CFU/mL) were intramuscularly immunized into quail through thigh muscles. Egg yolk IgY was purified by water dilution-ammonium sulfate precipitation method and the activity was determined by enzyme-linked immunosorbent assay (ELISA). Formalin inactivated immunogens induced high humoral immune response for both V. parahaemolyticus and V. vulnificus over heat inactivated immunogens. However, IgYs resulted from HIVP and FIVV immunogens, showed high specificity to V. parahaemolyticus and V. vulnificus respectively. Detection limits of the indirect ELISA using the produced IgYs were 105 CFU/mL for V. parahaemolyticus and 106 CFU/mL for V. vulnificus. The developed antibodies showed high binding affinity to their corresponding immunogens, very little cross reactivity to Staphylococcus aureus and not other bacteria strains (p<0.05), a phenomenon which was also observed in Western blot