scholarly journals Integrating Behavior of Children with Profound Intellectual, Multiple, or Severe Motor Disabilities With Location and Environment Data Sensors for Independent Communication and Mobility: App Development and Pilot Testing (Preprint)

2021 ◽  
Author(s):  
Von Ralph Dane Marquez Herbuela ◽  
Tomonori Karita ◽  
Yoshiya Furukawa ◽  
Yoshinori Wada ◽  
Yoshihiro Yagi ◽  
...  
Keyword(s):  
Application Programming Interface ◽  
Environmental Data ◽  
Data Sources ◽  
Single Subject ◽  
Body Parts ◽  
Cross Sectional ◽  
Motor Disabilities ◽  
Severe Motor ◽  
Outdoor Location ◽  
Child Caregiver

BACKGROUND Children with profound intellectual and multiple disabilities (PIMD) or severe motor and intellectual disabilities (SMID) only communicate through movements, vocalizations, body postures, muscle tensions, or facial expressions on a pre- or protosymbolic level. Yet, to the best of our knowledge, there are few systems developed to specifically aid in categorizing and interpreting behaviors of children with PIMD or SMID to facilitate independent communication and mobility. Further, environmental data such as weather variables were found to have associations with human affects and behaviors among typically developing children; however, studies involving children with neurological functioning impairments that affect communication or those who have physical and/or motor disabilities are unexpectedly scarce. OBJECTIVE This paper describes the design and development of the ChildSIDE app, which collects and transmits data associated with children’s behaviors, and linked location and environment information collected from data sources (GPS, iBeacon device, ALPS Sensor, and OpenWeatherMap application programming interface [API]) to the database. The aims of this study were to measure and compare the server/API performance of the app in detecting and transmitting environment data from the data sources to the database, and to categorize the movements associated with each behavior data as the basis for future development and analyses. METHODS This study utilized a cross-sectional observational design by performing multiple single-subject face-to-face and video-recorded sessions among purposively sampled child-caregiver dyads (children diagnosed with PIMD/SMID, or severe or profound intellectual disability and their primary caregivers) from September 2019 to February 2020. To measure the server/API performance of the app in detecting and transmitting data from data sources to the database, frequency distribution and percentages of 31 location and environment data parameters were computed and compared. To categorize which body parts or movements were involved in each behavior, the interrater agreement κ statistic was used. RESULTS The study comprised 150 sessions involving 20 child-caregiver dyads. The app collected 371 individual behavior data, 327 of which had associated location and environment data from data collection sources. The analyses revealed that ChildSIDE had a server/API performance >93% in detecting and transmitting outdoor location (GPS) and environment data (ALPS sensors, OpenWeatherMap API), whereas the performance with iBeacon data was lower (82.3%). Behaviors were manifested mainly through hand (22.8%) and body movements (27.7%), and vocalizations (21.6%). CONCLUSIONS The ChildSIDE app is an effective tool in collecting the behavior data of children with PIMD/SMID. The app showed high server/API performance in detecting outdoor location and environment data from sensors and an online API to the database with a performance rate above 93%. The results of the analysis and categorization of behaviors suggest a need for a system that uses motion capture and trajectory analyses for developing machine- or deep-learning algorithms to predict the needs of children with PIMD/SMID in the future.

Design of Marine Data Warehouse ETL System

2014 ◽  
Vol 668-669 ◽  
pp. 1374-1377 ◽  
Author(s):  
Wei Jun Wen
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Data Warehouse ◽  
Environmental Data ◽  
Data Sources ◽  
Quality Data ◽  
Critical Step ◽  
Marine Data ◽  
Data Extracting ◽  
Marine Environmental

ETL refers to the process of data extracting, transformation and loading and is deemed as a critical step in ensuring the quality, data specification and standardization of marine environmental data. Marine data, due to their complication, field diversity and huge volume, still remain decentralized, polyphyletic and isomerous with different semantics and hence far from being able to provide effective data sources for decision making. ETL enables the construction of marine environmental data warehouse in the form of cleaning, transformation, integration, loading and periodic updating of basic marine data warehouse. The paper presents a research on rules for cleaning, transformation and integration of marine data, based on which original ETL system of marine environmental data warehouse is so designed and developed. The system further guarantees data quality and correctness in analysis and decision-making based on marine environmental data in the future.

Demonstration of the relationship between MSD and online learning during the COVID-19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kochu Therisa Karingada ◽  
Michael Sony
Keyword(s):  
Online Learning ◽  
Undergraduate Students ◽  
Online Survey ◽  
Cross Sectional Study ◽  
The Body ◽  
Body Parts ◽  
Cross Sectional ◽  
Content Type ◽  
The Right ◽  
Almost All

PurposeThe COVID-19 pandemic lockdown has caught many educational institutions by surprise and warranted an abrupt migration from offline to online learning. This has resulted in an education change, without any time for due consideration, as regards its impact on musculoskeletal disorders (MSD) on students. The purpose of this study is to investigate MSD related to online learning during the COVID-19 pandemic lockdown.Design/methodology/approachA cross-sectional study was conducted on undergraduate students in India. In total, 261 students participated in this online survey.FindingsThe study finds that around 80% of students have reported some symptom in the head, neck and eyes since they started online learning. In total, 58% have reported MSD symptom in the right shoulder and 56% in the right hand fingers. Besides, more than 40 % of students experienced some MSD symptoms, in almost all the body parts studied, due to online learning. Correlation analysis is conducted between time spent on online learning per day and MSD symptoms.Originality/valueThis is the first study conducted on MSD and online learning during COVID-19 pandemic.

scholarly journals Vulnerabilities of children admitted to a pediatric inpatient care unit

2014 ◽  
Vol 32 (4) ◽  
pp. 367-373 ◽  
Author(s):  
Larissa Natacha de Oliveira ◽  
Márcia Koja Breigeiron ◽  
Sofia Hallmann ◽  
Maria Carolina Witkowski
Keyword(s):  
Illicit Drugs ◽  
Total Sample ◽  
University Hospital ◽  
Cross Sectional ◽  
Health History ◽  
History Of ◽  
Pediatric Inpatient ◽  
Inpatient Units ◽  
Child Caregiver ◽  
Networks Of Support

OBJECTIVE: To identify the vulnerabilities of children admitted to a pediatric inpatient unit of a university hospital.METHODS: Cross-sectional, descriptive study from April to September 2013 with36 children aged 30 days to 12 years old, admitted to medical-surgical pediatric inpatient units of a university hospital and their caregivers. Data concerning sociocultural, socioeconomic and clinical context of children and their families were collected by interview with the child caregiver and from patients, records, and analyzed by descriptive statistics.RESULTS: Of the total sample, 97.1% (n=132) of children had at least one type of vulnerability, the majority related to the caregiver's level of education, followed by caregiver's financial situation, health history of the child, caregiver's family situation, use of alcohol, tobacco, and illicit drugs by the caregiver, family's living conditions, caregiver's schooling, and bonding between the caregiver and the child. Only 2.9% (n=4) of the children did not show any criteria to be classified in a category of vulnerability.CONCLUSIONS: Most children were classified has having a social vulnerability. It is imperative to create networks of support between the hospital and the primary healthcare service to promote healthcare practices directed to the needs of the child and family.

scholarly journals Point, Walk, Talk: Links Between Three Early Milestones, from Observation and Parental Report

2019 ◽  
Author(s):  
Charlotte Moore ◽  
Shannon Dailey ◽  
Hallie Garrison ◽  
Andrei Amatuni ◽  
Elika Bergelson
Keyword(s):  
Data Collection ◽  
Early Development ◽  
Data Sources ◽  
Longitudinal Analyses ◽  
Parental Report ◽  
Cross Sectional ◽  
Data Collection Methods ◽  
Early Communication ◽  
Symbolic Thinking ◽  
Collection Methods

Around their first birthdays, infants begin to point, walk, and talk. These abilities are appreciable both by researchers with strictly standardized criteria and caregivers with more relaxed notions of what each of these skills entails. Here we compare the onsets of these skills and links among them across two data collection methods: observation and parental report. We examine pointing, walking, and talking in a sample of 44 infants studied longitudinally from 6–18 months. In this sample, links between pointing and vocabulary were tighter than those between walking and vocabulary, supporting a unified socio-communicative growth account. Indeed, across several cross-sectional and longitudinal analyses, pointers had larger vocabularies than their non-pointing peers. In contrast to previous work, this did not hold for walkers’ vs. crawlers’ vocabularies in our sample. Comparing across data sources, we find that reported and observed estimates of the growing vocabulary and of age of walk onset were closely correlated, while agreement between parents and researchers on pointing onset and talking onset was weaker. Taken together, these results support a developmental account in which gesture and language are intertwined aspects of early communication and symbolic thinking, whereas the shift from crawling to walking appears indistinct from age in its relation with language. We conclude that pointing, walking, and talking are on similar timelines yet distinct from one another, and discuss methodological and theoretical implications in the context of early development.

scholarly journals Prevalence of Work-Related Musculoskeletal Disorders: Psychological and Physical Risk Factors

2021 ◽  
Vol 18 (17) ◽  
pp. 9361
Author(s):  
K. Saraswathi Krishnan ◽  
Gunasunderi Raju ◽  
Omar Shawkataly
Keyword(s):  
Risk Factors ◽  
Female Gender ◽  
Cross Sectional Study ◽  
Musculoskeletal Symptoms ◽  
Body Region ◽  
Left Shoulder ◽  
Body Parts ◽  
Cross Sectional ◽  
Work Related ◽  
Lower Back

Purpose—This study aimed to estimate the prevalence and risk factors of MSD pain in various anatomical regions among nurses. Method—A cross-sectional study involving a self-administered questionnaire by registered nurses with clinical experience. Data was collected using convenience sampling after obtaining informed consent. The results were drawn from a total of 300 nurses. Results—The nurses presented with occasional mental exhaustion (44.3%) and often physical exhaustion (44.0%). Almost all (97.3%) the nurses complained of having work-related pain during the last 12 months. Body parts with the most pain were the lower back (86.7%), ankles (86.7%), neck (86.0%), shoulders (85.0%), lower legs (84.7%) and upper back (84.3%). The pain frequency was rated as occasional pain for the neck and upper back, pain was often felt for the rest of the parts. Nurses complained of severe pain in the lower back (19.7%), right shoulder (29.7%) and left shoulder (30.3%). The frequency of having musculoskeletal symptoms in any body region was increased with age, lower education level, female gender, high BMI, job tenure and lifestyle. Conclusions—Nurses’ WRMSD complaints should be taken seriously to curb further risk and musculoskeletal hazards.

scholarly journals The Level of Children’s Independence with Cerebral Palsy in Several Regions in Java and Sumatra

2020 ◽  
Vol 5 (1) ◽  
pp. 1-12
Author(s):  
Bambang Trisnowiyanto
Keyword(s):  
Cerebral Palsy ◽  
Health Workers ◽  
Brain Lesion ◽  
Clinical Manifestations ◽  
Total Sample ◽  
Body Parts ◽  
Research Subjects ◽  
Cross Sectional ◽  
Children With Cerebral Palsy ◽  
Gmfcs Level

Background:  The most common disorder or disability in childhood is cerebral palsy, obtained during the antenatal, perinatal or early postnatal period. Cerebral palsy is a non-progressive injury or brain lesion with very variable clinical manifestations. children with cerebral palsy have impaired movement, ability levels and functional limitations and affected body parts. Therefore, to find out the level of independence in children with cerebral palsy, it is necessary to have an examination carried out by health workers, especially physiotherapy. In this case, an examination using the Gross Motor Function Classification System (GMFCS). The purpose of this study was to determine the degree of independence of children with cerebral palsy in several regions in Java and Sumatra. Methods: A total of 315 children with cerebral palsy (mean ± SD)  participated in this cross-sectional study design. The research was conducted in March-June 2019. GMFCS data was collected from children with cerebral palsy in the parent community of cerebral palsy in 10 cities. The Kolmogorov-Smirnov test used for data normality test. Result: Overall research subjects from 10 cerebral palsy communities with a total sample of 315 children, most cerebral palsy with GMFCS level 4 as many as 117 children (37.1%), then GMFCS level 3 as many as 84 children (26.7%), GMFCS level 5 is 67 children (21.3%), level 2 GMFCS is 24 children (7.6%), and at least children with level 1 GMFCS are 23 children (7.3%). Conclusion: The conclusion is from a total of 315 children with cerebral palsy, the level of Indonesian children's independence based on GMFCS most of them are less independent.

scholarly journals A Correlative Study Between Personality Traits and the Preference of Site Selection in Cosmetic Treatment

2021 ◽  
Vol 12 ◽  
Author(s):  
Huan Qian ◽  
Yuxiao Ling ◽  
Chen Wang ◽  
Cameron Lenahan ◽  
Mengwen Zhang ◽  
...  
Keyword(s):  
Personality Traits ◽  
Cosmetic Surgery ◽  
Treatment Options ◽  
Well Being ◽  
The Body ◽  
Eysenck Personality Questionnaire ◽  
Body Parts ◽  
Personality Profiles ◽  
Cross Sectional ◽  
Face Contour

Background: Cosmetic treatment was closely associated with beauty seekers' psychological well-being. Patients who seek cosmetic surgery often show anxiety. Nevertheless, not much is known regarding how personality traits relate to the selection of body parts that receive cosmetic treatment.Aims: This study aims to investigate the correlation between personality traits and various selection sites for cosmetic treatment via Eysenck Personality Questionnaire (EPQ).Methods: A cross-sectional approach was adopted to randomly recruited patients from a general hospital planning to undergo cosmetic treatments. All respondents completed the EPQ and provided their demographic information. The EPQ involves four scales: the extraversion (E), neuroticism (N), psychoticism (P), and lying scales (L). Psychological scales were evaluated to verify that people who selected different body sites for cosmetic intervention possessed different personality portraits.Results: A total of 426 patients with an average age of 32.14 ± 8.06 were enrolled. Among them, 384 were females, accounting for more than 90% of patients. Five treatment sites were analyzed, including the body, eye, face contour, nose, and skin. Comparatively, patients with neuroticism were more likely to undergo and demand rhinoplasty (OR 1.15, 95% CI 1.07–1.24, P < 0.001). Face contour treatment was commonly associated with extraversion (OR 1.05, 95% CI 1.00–1.11, P = 0.044), psychoticism (OR 1.13, CI 1.03–1.25, P = 0.013), and neuroticism (OR 1.05, CI 1.01–1.10, P = 0.019).Conclusions: This novel study attempted to determine the personality profiles of beauty seekers. The corresponding assessments may provide references for clinical treatment options and enhance postoperative satisfaction for both practitioners and patients.

scholarly journals An Ontology-based Visual Analytics for Apple Variety Testing

2021 ◽  
Author(s):  
Ekaterina Chuprikova ◽  
Abraham Mejia Aguilar ◽  
Roberto Monsorno
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Data Integration ◽  
Visual Analytics ◽  
Agricultural Sector ◽  
Environmental Data ◽  
Data Sources ◽  
Apple Variety ◽  
Testing Program ◽  
Variety Testing

<p>Increasing agricultural production challenges, such as climate change, environmental concerns, energy demands, and growing expectations from consumers triggered the necessity for innovation using data-driven approaches such as visual analytics. Although the visual analytics concept was introduced more than a decade ago, the latest developments in the data mining capacities made it possible to fully exploit the potential of this approach and gain insights into high complexity datasets (multi-source, multi-scale, and different stages). The current study focuses on developing prototypical visual analytics for an apple variety testing program in South Tyrol, Italy. Thus, the work aims (1) to establish a visual analytics interface enabled to integrate and harmonize information about apple variety testing and its interaction with climate by designing a semantic model; and (2) to create a single visual analytics user interface that can turn the data into knowledge for domain experts. </p><p>This study extends the visual analytics approach with a structural way of data organization (ontologies), data mining, and visualization techniques to retrieve knowledge from an extensive collection of apple variety testing program and environmental data. The prototype stands on three main components: ontology, data analysis, and data visualization. Ontologies provide a representation of expert knowledge and create standard concepts for data integration, opening the possibility to share the knowledge using a unified terminology and allowing for inference. Building upon relevant semantic models (e.g., agri-food experiment ontology, plant trait ontology, GeoSPARQL), we propose to extend them based on the apple variety testing and climate data. Data integration and harmonization through developing an ontology-based model provides a framework for integrating relevant concepts and relationships between them, data sources from different repositories, and defining a precise specification for the knowledge retrieval. Besides, as the variety testing is performed on different locations, the geospatial component can enrich the analysis with spatial properties. Furthermore, the visual narratives designed within this study will give a better-integrated view of data entities' relations and the meaningful patterns and clustering based on semantic concepts.</p><p>Therefore, the proposed approach is designed to improve decision-making about variety management through an interactive visual analytics system that can answer "what" and "why" about fruit-growing activities. Thus, the prototype has the potential to go beyond the traditional ways of organizing data by creating an advanced information system enabled to manage heterogeneous data sources and to provide a framework for more collaborative scientific data analysis. This study unites various interdisciplinary aspects and, in particular: Big Data analytics in the agricultural sector and visual methods; thus, the findings will contribute to the EU priority program in digital transformation in the European agricultural sector.</p><p>This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 894215.</p>

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