Non Invasive Tools for Early Detection of Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) describe a set of neurodevelopmental disorders. ASD represents a significant public health problem. Currently, ASDs are not diagnosed before the 2nd year of life but an early identification of ASDs would be crucial as interventions are much more effective than specific therapies starting in later childhood. To this aim, cheap an contact-less automatic approaches recently aroused great clinical interest. Among them, the cry and the movements of the newborn, both involving the central nervous system, are proposed as possible indicators of neurological disorders. This PhD work is a first step towards solving this challenging problem. An integrated system is presented enabling the recording of audio (crying) and video (movements) data of the newborn, their automatic analysis with innovative techniques for the extraction of clinically relevant parameters and their classification with data mining techniques. New robust algorithms were developed for the selection of the voiced parts of the cry signal, the estimation of acoustic parameters based on the wavelet transform and the analysis of the infant’s general movements (GMs) through a new body model for segmentation and 2D reconstruction. In addition to a thorough literature review this thesis presents the state of the art on these topics that shows that no studies exist concerning normative ranges for newborn infant cry in the first 6 months of life nor the correlation between cry and movements. Through the new automatic methods a population of control infants (“low-risk”, LR) was compared to a group of “high-risk” (HR) infants, i.e. siblings of children already diagnosed with ASD. A subset of LR infants clinically diagnosed as newborns with Typical Development (TD) and one affected by ASD were compared. The results show that the selected acoustic parameters allow good differentiation between the two groups. This result provides new perspectives both diagnostic and therapeutic

Action compositionality with focus on neurodevelopmental disorders

A central question in motor neuroscience is how the Central Nervous System (CNS) would handle flexibility at the effector level, that is, how the brain would solve the problem coined by Nikolai Bernstein as the “degrees of freedom problem”, or the task of controlling a much larger number of degrees of freedom (dofs) that is often needed to produce behavior. Flexibility is a bless and a curse: while it enables the same body to engage in a virtually infinite number of behaviors, the CNS is left with the job of figuring out the right subset of dofs to use and how to control and coordinate these degrees. Similarly, at the level of perception, the CNS seeks to obtain information pertaining to the action and actors involved based on perceived motion of other people’s dofs. This problem is believed to be solved with a particular dimensionality reduction strategy, where action production would consist of tuning only a few parameters that control and coordinate a small number of motor primitives, and action perception would take place by applying grouping processes that would solve the inverse problem, that is to identify the motor primitives and the corresponding tuning parameters used by an actor. These parameters can encode not only information on the action per se, but also higher-order cognitive cues like body language or emotion. This compositional view of action representation has an obvious parallel with language: we can think of primitives as words and cognitive systems (motor, perceptual) as different languages. Little is known, however, about how words/primitives would be formed from low-level signals measured at each dof. Here we introduce the SB-ST method, a bottom-up approach to find full-body postural primitives as a set of key postures, that is, vectors corresponding to key relationships among dofs (such as joint rotations) which we call spatial basis (SB) and second, we impose a parametric model to the spatio-temporal (ST) profiles of each SB vector. We showcase the method by applying SB vectors and ST parameters to study vertical jumps of young adults (YAD) typically developing (TD) children and children with Developmental Coordination Disorder (DCD) obtained with motion capture. We also go over a number of other topics related with compositionality: we introduce a top-down system of tool-use primitives based on kinematic events between body parts and objects. The kinematic basis of these events is inspired by the hand-to-object velocity signature reported by movement psychologists in the 1980’s. We discuss the need for custom-made movement measurement strategies to study action primitives on some target populations, for example infants. Having the right tools to record infant movement would be of help, for example, to research in Autism Spectrum Disorder (ASD) where early sensorimotor abnormalities were shown to be linked to future diagnoses of ASD and the development of the typical social traits ASD is mostly known for. We continue the discussion on infant movement measurement where we present an alternative way of processing movement data by using textual descriptions as re- placements to the actual movement signals observed in infant behavioral trials. We explore the fact that these clinical descriptions are freely available as a byproduct of the diagnosis process itself. A typical/atypical classification experiment shows that, at the level of sentences, traditionally used text features in Natural Language Processing such as term frequencies and TF-IDF computed from unigrams and bigrams can be potentially helpful. In the end, we sketch a conceptual, compositional model of action generation based on exploratory results on the jump data, according to which the presence of disorders would be related not to differences in key postures, but in how they are controlled throughout execution. We next discuss the nature of action and actor information representation by analyzing a second dataset with arm-only data (bi-manual coordination and object manipulations) with more target populations than in the jump dataset: TD and DCD children, YAD and seniors with and without Parkinson’s Disease (PD). Multiple group analyses on dofs coupled with explained variances at SB representations suggest that the cost of representing a task as performed by an actor may be equivalent to the cost of representing the task alone. Plus, group discriminating information appears to be more compressed than task-only discriminating information, and because this compression happens at the top spatial bases, we conjecture that groups may be recognized faster than tasks

Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice

This Special Issue shows a range of potential opportunities for the application of wearable movement sensors in motor rehabilitation. However, the papers surely do not cover the whole field of physical behavior monitoring in motor rehabilitation. Most studies in this Special Issue focused on the technical validation of wearable sensors and the development of algorithms. Clinical validation studies, studies applying wearable sensors for the monitoring of physical behavior in daily life conditions, and papers about the implementation of wearable sensors in motor rehabilitation are under-represented in this Special Issue. Studies investigating the usability and feasibility of wearable movement sensors in clinical populations were lacking. We encourage researchers to investigate the usability, acceptance, feasibility, reliability, and clinical validity of wearable sensors in clinical populations to facilitate the application of wearable movement sensors in motor rehabilitation

Cultivate Quantitative Magnetic Resonance Imaging Methods to Measure Markers of Health and Translate to Large Scale Cohort Studies

Magnetic Resonance Imaging (MRI) is an indispensable tool in healthcare and research, with a growing demand for its services. The appeal of MRI stems from its non-ionizing radiation nature, ability to generate high-resolution images of internal organs and structures without invasive procedures, and capacity to provide quantitative assessments of tissue properties such as ectopic fat, body composition, and organ volume. All without long term side effects. Nine published papers are submitted which show the cultivation of quantitative measures of ectopic fat within the liver and pancreas using MRI, and the process of validating whole-body composition and organ volume measurements. All these techniques have been translated into large-scale studies to improve health measurements in large population cohorts. Translating this work into large-scale studies, including the use of artificial intelligence, is included. Additionally, an evaluation accompanies these published studies, appraising the evolution of these quantitative MRI techniques from the conception to their application in large cohort studies. Finally, this appraisal provides a summary of future work on crowdsourcing of ground truth training data to facilitate its use in wider applications of artificial intelligence.In conclusion, this body of work presents a portfolio of evidence to fulfil the requirements of a PhD by published works at the University of Salford

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

GVSU Undergraduate and Graduate Catalog, 2021-2022

Grand Valley State University 2021-2022 undergraduate and graduate course catalog. Course catalogs are published annually to provide students with information and guidance for enrollment.https://scholarworks.gvsu.edu/course_catalogs/1096/thumbnail.jp

Serotonergic modulation of the ventral pallidum by 5HT1A, 5HT5A, 5HT7 AND 5HT2C receptors

Introduction: Serotonin's involvement in reward processing is controversial. The large number of serotonin receptor sub-types and their individual and unique contributions have been difficult to dissect out, yet understanding how specific serotonin receptor sub-types contribute to its effects on areas associated with reward processing is an essential step. Methods: The current study used multi-electrode arrays and acute slice preparations to examine the effects of serotonin on ventral pallidum (VP) neurons. Approach for statistical analysis: extracellular recordings were spike sorted using template matching and principal components analysis, Consecutive inter-spike intervals were then compared over periods of 1200 seconds for each treatment condition using a student’s t test. Results and conclusions: Our data suggests that excitatory responses to serotonin application are pre-synaptic in origin as blocking synaptic transmission with low-calcium aCSF abolished these responses. Our data also suggests that 5HT1a, 5HT5a and 5HT7 receptors contribute to this effect, potentially forming an oligomeric complex, as 5HT1a antagonists completely abolished excitatory responses to serotonin application, while 5HT5a and 5HT7 only reduced the magnitude of excitatory responses to serotonin. 5HT2c receptors were the only serotonin receptor sub-type tested that elicited inhibitory responses to serotonin application in the VP. These findings, combined with our previous data outlining the mechanisms underpinning dopamine's effects in the VP, provide key information, which will allow future research to fully examine the interplay between serotonin and dopamine in the VP. Investigation of dopamine and serotonins interaction may provide vital insights into our understanding of the VP's involvement in reward processing. It may also contribute to our understanding of how drugs of abuse, such as cocaine, may hijack these mechanisms in the VP resulting in sensitization to drugs of abuse

Smoking and Second Hand Smoking in Adolescents with Chronic Kidney Disease: A Report from the Chronic Kidney Disease in Children (CKiD) Cohort Study

The goal of this study was to determine the prevalence of smoking and second hand smoking [SHS] in adolescents with CKD and their relationship to baseline parameters at enrollment in the CKiD, observational cohort study of 600 children (aged 1-16 yrs) with Schwartz estimated GFR of 30-90 ml/min/1.73m2. 239 adolescents had self-report survey data on smoking and SHS exposure: 21 [9%] subjects had “ever” smoked a cigarette. Among them, 4 were current and 17 were former smokers. Hypertension was more prevalent in those that had “ever” smoked a cigarette (42%) compared to non-smokers (9%), p\u3c0.01. Among 218 non-smokers, 130 (59%) were male, 142 (65%) were Caucasian; 60 (28%) reported SHS exposure compared to 158 (72%) with no exposure. Non-smoker adolescents with SHS exposure were compared to those without SHS exposure. There was no racial, age, or gender differences between both groups. Baseline creatinine, diastolic hypertension, C reactive protein, lipid profile, GFR and hemoglobin were not statistically different. Significantly higher protein to creatinine ratio (0.90 vs. 0.53, p\u3c0.01) was observed in those exposed to SHS compared to those not exposed. Exposed adolescents were heavier than non-exposed adolescents (85th percentile vs. 55th percentile for BMI, p\u3c 0.01). Uncontrolled casual systolic hypertension was twice as prevalent among those exposed to SHS (16%) compared to those not exposed to SHS (7%), though the difference was not statistically significant (p= 0.07). Adjusted multivariate regression analysis [OR (95% CI)] showed that increased protein to creatinine ratio [1.34 (1.03, 1.75)] and higher BMI [1.14 (1.02, 1.29)] were independently associated with exposure to SHS among non-smoker adolescents. These results reveal that among adolescents with CKD, cigarette use is low and SHS is highly prevalent. The association of smoking with hypertension and SHS with increased proteinuria suggests a possible role of these factors in CKD progression and cardiovascular outcomes

Play Among Books

How does coding change the way we think about architecture? Miro Roman and his AI Alice_ch3n81 develop a playful scenario in which they propose coding as the new literacy of information. They convey knowledge in the form of a project model that links the fields of architecture and information through two interwoven narrative strands in an “infinite flow” of real books