A Real-time Human Pose Estimation Approach for Optimal Sensor Placement in Sensor-based Human Activity Recognition

Sensor-based Human Activity Recognition facilitates unobtrusive monitoring of human movements. However, determining the most effective sensor placement for optimal classification performance remains challenging. This paper introduces a novel methodology to resolve this issue, using real-time 2D pose estimations derived from video recordings of target activities. The derived skeleton data provides a unique strategy for identifying the optimal sensor location. We validate our approach through a feasibility study, applying inertial sensors to monitor 13 different activities across ten subjects. Our findings indicate that the vision-based method for sensor placement offers comparable results to the conventional deep learning approach, demonstrating its efficacy. This research significantly advances the field of Human Activity Recognition by providing a lightweight, on-device solution for determining the optimal sensor placement, thereby enhancing data anonymization and supporting a multimodal classification approach

The CHARGE study: an epidemiologic investigation of genetic and environmental factors contributing to autism.

Causes and contributing factors for autism are poorly understood. Evidence suggests that prevalence is rising, but the extent to which diagnostic changes and improvements in ascertainment contribute to this increase is unclear. Both genetic and environmental factors are likely to contribute etiologically. Evidence from twin, family, and genetic studies supports a role for an inherited predisposition to the development of autism. Nonetheless, clinical, neuroanatomic, neurophysiologic, and epidemiologic studies suggest that gene penetrance and expression may be influenced, in some cases strongly, by the prenatal and early postnatal environmental milieu. Sporadic studies link autism to xenobiotic chemicals and/or viruses, but few methodologically rigorous investigations have been undertaken. In light of major gaps in understanding of autism, a large case-control investigation of underlying environmental and genetic causes for autism and triggers of regression has been launched. The CHARGE (Childhood Autism Risks from Genetics and Environment) study will address a wide spectrum of chemical and biologic exposures, susceptibility factors, and their interactions. Phenotypic variation among children with autism will be explored, as will similarities and differences with developmental delay. The CHARGE study infrastructure includes detailed developmental assessments, medical information, questionnaire data, and biologic specimens. The CHARGE study is linked to University of California-Davis Center for Children's Environmental Health laboratories in immunology, xenobiotic measurement, cell signaling, genomics, and proteomics. The goals, study design, and data collection protocols are described, as well as preliminary demographic data on study participants and on diagnoses of those recruited through the California Department of Developmental Services Regional Center System

Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML

Medical applications of machine learning (ML) have experienced a surge in popularity in recent years. The intensive care unit (ICU) is a natural habitat for ML given the abundance of available data from electronic health records. Models have been proposed to address numerous ICU prediction tasks like the early detection of complications. While authors frequently report state-of-the-art performance, it is challenging to verify claims of superiority. Datasets and code are not always published, and cohort definitions, preprocessing pipelines, and training setups are difficult to reproduce. This work introduces Yet Another ICU Benchmark (YAIB), a modular framework that allows researchers to define reproducible and comparable clinical ML experiments; we offer an end-to-end solution from cohort definition to model evaluation. The framework natively supports most open-access ICU datasets (MIMIC III/IV, eICU, HiRID, AUMCdb) and is easily adaptable to future ICU datasets. Combined with a transparent preprocessing pipeline and extensible training code for multiple ML and deep learning models, YAIB enables unified model development. Our benchmark comes with five predefined established prediction tasks (mortality, acute kidney injury, sepsis, kidney function, and length of stay) developed in collaboration with clinicians. Adding further tasks is straightforward by design. Using YAIB, we demonstrate that the choice of dataset, cohort definition, and preprocessing have a major impact on the prediction performance - often more so than model class - indicating an urgent need for YAIB as a holistic benchmarking tool. We provide our work to the clinical ML community to accelerate method development and enable real-world clinical implementations. Software Repository: https://github.com/rvandewater/YAIB.Comment: Main benchmark: https://github.com/rvandewater/YAIB, Cohort generation: https://github.com/rvandewater/YAIB-cohorts, Models: https://github.com/rvandewater/YAIB-model

Neonatal cytokines and chemokines and risk of Autism Spectrum Disorder: the Early Markers for Autism (EMA) study: a case-control study.

BackgroundBiologic markers of infection and inflammation have been associated with Autism Spectrum Disorders (ASD) but prior studies have largely relied on specimens taken after clinical diagnosis. Research on potential biologic markers early in neurodevelopment is required to evaluate possible causal pathways and screening profiles.ObjectiveTo investigate levels of cytokines and chemokines in newborn blood specimens as possible early biologic markers for autism.MethodsWe conducted a population-based case-control study nested within the cohort of infants born from July 2000 to September 2001 to women who participated in the prenatal screening program in Orange County, California, USA. The study population included children ascertained from the California Department of Developmental Services with Autism Spectrum Disorder (ASD, n = 84), or developmental delay but not ASD (DD, n = 49), and general population controls randomly sampled from the birth certificate files and frequency matched to ASD cases on sex, birth month and birth year (GP, n = 159). Cytokine and chemokine concentrations were measured in archived neonatal blood specimens collected for routine newborn screening.ResultsCytokines were not detected in the vast majority of newborn samples regardless of case or control status. However, the chemokine monocyte chemotactic protein-1 (MCP-1) was elevated and the chemokine Regulated upon Activation Normal T-Cell Expressed and Secreted (RANTES) was decreased in ASD cases compared to GP controls. The chemokines macrophage inflammatory protein-1alpha (MIP-1α) and RANTES were decreased in children with DD compared to GP controls.ConclusionMeasurement of immune system function in the first few days of life may aid in the early identification of abnormal neurodevelopment and shed light on the biologic mechanisms underlying normal neurodevelopment

The Care2Report System: Automated Medical Reporting as an Integrated Solution to Reduce Administrative Burden in Healthcare

Documenting patient medical information in the electronic medical record is a time-consuming task at the expense of direct patient care. We propose an integrated solution to automate the process of medical reporting. This vision is enabled through the integration of speech and action recognition technology with semantic interpretation based on knowledge graphs. This paper presents our dialogue summarization pipeline that transforms speech into a medical report via transcription and formal representation. We discuss the functional and technical architecture of our Care2Report system along with an initial system evaluation with data of real consultation sessions

Increased Anti-Phospholipid Antibodies in Autism Spectrum Disorders

Autism spectrum disorders (ASD) are characterized by impairments in communication, social interactions, and repetitive behaviors. While the etiology of ASD is complex and likely involves the interplay of genetic and environmental factors, growing evidence suggests that immune dysfunction and the presence of autoimmune responses including autoantibodies may play a role in ASD. Anti-phospholipid antibodies are believed to occur from both genetic and environmental factors and have been linked to a number of neuropsychiatric symptoms such as cognitive impairments, anxiety, and repetitive behaviors. In the current study, we investigated whether there were elevated levels of anti-phospholipid antibodies in a cross-sectional analysis of plasma of young children with ASD compared to age-matched typically developing (TD) controls and children with developmental delays (DD) other than ASD. We found that levels of anti-cardiolipin, β2-glycoprotein 1, and anti-phosphoserine antibodies were elevated in children with ASD compared with age-matched TD and DD controls. Further, the increase in antibody levels was associated with more impaired behaviors reported by parents. This study provides the first evidence for elevated production of anti-phospholipid antibodies in young children with ASD and provides a unique avenue for future research into determining possible pathogenic mechanisms that may underlie some cases of ASD

Increased midgestational IFN-γ, IL-4 and IL-5 in women bearing a child with autism: A case-control study

<p>Abstract</p> <p>Background</p> <p>Immune anomalies have been documented in individuals with autism spectrum disorders (ASDs) and their family members. It is unknown whether the maternal immune profile during pregnancy is associated with the risk of bearing a child with ASD or other neurodevelopmental disorders.</p> <p>Methods</p> <p>Using Luminex technology, levels of 17 cytokines and chemokines were measured in banked serum collected from women at 15 to 19 weeks of gestation who gave birth to a child ultimately diagnosed with (1) ASD (<it>n </it>= 84), (2) a developmental delay (DD) but not autism (<it>n </it>= 49) or (3) no known developmental disability (general population (GP); <it>n </it>= 159). ASD and DD risk associated with maternal cytokine and chemokine levels was estimated by using multivariable logistic regression analysis.</p> <p>Results</p> <p>Elevated concentrations of IFN-γ, IL-4 and IL-5 in midgestation maternal serum were significantly associated with a 50% increased risk of ASD, regardless of ASD onset type and the presence of intellectual disability. By contrast, elevated concentrations of IL-2, IL-4 and IL-6 were significantly associated with an increased risk of DD without autism.</p> <p>Conclusion</p> <p>The profile of elevated serum IFN-γ, IL-4 and IL-5 was more common in women who gave birth to a child subsequently diagnosed with ASD. An alternative profile of increased IL-2, IL-4 and IL-6 was more common for women who gave birth to a child subsequently diagnosed with DD without autism. Further investigation is needed to characterize the relationship between these divergent maternal immunological phenotypes and to evaluate their effect on neurodevelopment.</p

Correlations of Gene Expression with Blood Lead Levels in Children with Autism Compared to Typically Developing Controls

The objective of this study was to examine the correlation between gene expression and lead (Pb) levels in blood in children with autism (AU, n = 37) compared to typically developing controls (TD, n = 15). We postulated that, though lead levels did not differ between the groups, AU children might metabolize lead differently compared to TD children. RNA was isolated from blood and processed on Affymetrix microarrays. Separate analyses of covariance (ANCOVA) corrected for age and gender were performed for TD, AU, and all subjects (AU + TD). To reduce false positives, only genes that overlapped these three ANCOVAs were considered. Thus, 48 probe sets correlated with lead levels in both AU and TD subjects and were significantly different between the groups (p(Diagnosis × log2 Pb) < 0.05). These genes were related mainly to immune and inflammatory processes, including MHC Class II family members and CD74. A large number (n = 791) of probe sets correlated (P ≤ 0.05) with lead levels in TD but not in AU subjects; and many probe sets (n = 162) correlated (P ≤ 0.05) with lead levels in AU but not in TD subjects. Only 30 probe sets correlated (P ≤ 0.05) with lead levels in a similar manner in the AU and TD groups. These data show that AU and TD children display different associations between transcript levels and low levels of lead. We postulate that this may relate to the underlying genetic differences between the two groups, though other explanations cannot be excluded

Correlations Between Gene Expression and Mercury Levels in Blood of Boys With and Without Autism

Gene expression in blood was correlated with mercury levels in blood of 2- to 5-year-old boys with autism (AU) compared to age-matched typically developing (TD) control boys. This was done to address the possibility that the two groups might metabolize toxicants, such as mercury, differently. RNA was isolated from blood and gene expression assessed on whole genome Affymetrix Human U133 expression microarrays. Mercury levels were measured using an inductively coupled plasma mass spectrometer. Analysis of covariance (ANCOVA) was performed and partial correlations between gene expression and mercury levels were calculated, after correcting for age and batch effects. To reduce false positives, only genes shared by the ANCOVA models were analyzed. Of the 26 genes that correlated with mercury levels in both AU and TD boys, 11 were significantly different between the groups (P(Diagnosis*Mercury) ≤ 0.05). The expression of a large number of genes (n = 316) correlated with mercury levels in TD but not in AU boys (P ≤ 0.05), the most represented biological functions being cell death and cell morphology. Expression of 189 genes correlated with mercury levels in AU but not in TD boys (P ≤ 0.05), the most represented biological functions being cell morphology, amino acid metabolism, and antigen presentation. These data and those in our companion study on correlation of gene expression and lead levels show that AU and TD children display different correlations between transcript levels and low levels of mercury and lead. These findings might suggest different genetic transcriptional programs associated with mercury in AU compared to TD children

Increased anti-phospholipid antibodies in autism spectrum disorders.

Autism spectrum disorders (ASD) are characterized by impairments in communication, social interactions, and repetitive behaviors. While the etiology of ASD is complex and likely involves the interplay of genetic and environmental factors, growing evidence suggests that immune dysfunction and the presence of autoimmune responses including autoantibodies may play a role in ASD. Anti-phospholipid antibodies are believed to occur from both genetic and environmental factors and have been linked to a number of neuropsychiatric symptoms such as cognitive impairments, anxiety, and repetitive behaviors. In the current study, we investigated whether there were elevated levels of anti-phospholipid antibodies in a cross-sectional analysis of plasma of young children with ASD compared to age-matched typically developing (TD) controls and children with developmental delays (DD) other than ASD. We found that levels of anti-cardiolipin, β 2-glycoprotein 1, and anti-phosphoserine antibodies were elevated in children with ASD compared with age-matched TD and DD controls. Further, the increase in antibody levels was associated with more impaired behaviors reported by parents. This study provides the first evidence for elevated production of anti-phospholipid antibodies in young children with ASD and provides a unique avenue for future research into determining possible pathogenic mechanisms that may underlie some cases of ASD