scholarly journals A Systematic Review of Automatic Health Monitoring in Calves: Glimpsing the Future From Current Practice

2021 ◽  
Vol 8 ◽  
Author(s):  
Dengsheng Sun ◽  
Laura Webb ◽  
P. P. J. van der Tol ◽  
Kees van Reenen
Keyword(s):  
Health Monitoring ◽  
Information Integration ◽  
Health Assessment ◽  
Data Interpretation ◽  
Sensor Technology ◽  
Future Research ◽  
Calf Health ◽  
Health Checks ◽  
Monitoring Tools ◽  
Sensitivity Specificity

Infectious diseases, particularly bovine respiratory disease (BRD) and neonatal calf diarrhea (NCD), are prevalent in calves. Efficient health-monitoring tools to identify such diseases on time are lacking. Common practice (i.e., health checks) often identifies sick calves at a late stage of disease or not at all. Sensor technology enables the automatic and continuous monitoring of calf physiology or behavior, potentially offering timely and precise detection of sick calves. A systematic overview of automated disease detection in calves is still lacking. The objectives of this literature review were hence: to investigate previously applied sensor validation methods used in the context of calf health, to identify sensors used on calves, the parameters these sensors monitor, and the statistical tools applied to identify diseases, to explore potential research gaps and to point to future research opportunities. To achieve these objectives, systematic literature searches were conducted. We defined four stages in the development of health-monitoring systems: (1) sensor technique, (2) data interpretation, (3) information integration, and (4) decision support. Fifty-four articles were included (stage one: 26; stage two: 19; stage three: 9; and stage four: 0). Common parameters that assess the performance of these systems are sensitivity, specificity, accuracy, precision, and negative predictive value. Gold standards that typically assess these parameters include manual measurement and manual health-assessment protocols. At stage one, automatic feeding stations, accelerometers, infrared thermography cameras, microphones, and 3-D cameras are accurate in screening behavior and physiology in calves. At stage two, changes in feeding behaviors, lying, activity, or body temperature corresponded to changes in health status, and point to health issues earlier than manual health checks. At stage three, accelerometers, thermometers, and automatic feeding stations have been integrated into one system that was shown to be able to successfully detect diseases in calves, including BRD and NCD. We discuss these findings, look into potentials at stage four, and touch upon the topic of resilience, whereby health-monitoring system might be used to detect low resilience (i.e., prone to disease but clinically healthy calves), promoting further improvements in calf health and welfare.

scholarly journals High dose antipsychotic treatment monitoring audit

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S348-S348
Author(s):  
Jake Scott ◽  
Jose Belda
Keyword(s):  
Side Effects ◽  
Physical Health ◽  
Health Monitoring ◽  
Clinical Benefit ◽  
Health Assessment ◽  
Antipsychotic Treatment ◽  
High Dose ◽  
Health Checks ◽  
Increased Risk ◽  
Multi Disciplinary Team

AimsTo quantify how many patients were prescribed high dose antipsychotic treatment (HDAT) and establish whether guidance for monitoring HDAT was being followed in an Assertive Outreach Team.BackgroundSevere mental health disorders are associated with significant premature mortality, predominantly due to physical health conditions. Antipsychotic medications are associated with side effects, including metabolic syndrome and QT prolongation, which increase the risk of serious physical illness. HDAT is defined as when the total dose of antipsychotics prescribed exceeds 100% of the maximum BNF dose, if each dose is expressed a percentage of its maximum dose. There is limited evidence of clinical benefit with HDAT but an increased risk of side effects. Patients prescribed HDAT should therefore be monitored for side effects and clinical benefit. Sussex Partnership NHS Foundation Trust developed a form specifically for this purpose, to be completed in addition to a physical health assessment.MethodAll patients on caseload were audited using the electronic notes. Current inpatients were excluded, as inpatient HDAT monitoring forms are attached to paper drug charts and therefore were not available for review.ResultA total of 61 patients were audited. Nine were excluded due to being inpatients. 16 were on community treatment orders and 26 were prescribed a long-acting antipsychotic injection. 10 were prescribed clozapine. The median number of medications prescribed was one. Four patients were prescribed HDAT ranging from 117-150% of the maximum BNF dose. Of these four, one had a HDAT form but this was out of date. 39 of 52 (75%) patients audited had had a physical health assessment in the past 12 months. Two of the 13 missing a physical health assessment were on HDAT.ConclusionPhysical health monitoring should be carried out for all patients on antipsychotics, but is particularly important for patients on HDAT. This audit identified a problem in both general physical health checks and HDAT monitoring. On discussion with the multi-disciplinary team a number of barriers to appropriate physical health monitoring were identified. There was a lack of awareness within the multi-disciplinary team that patients were receiving HDAT and regarding the implications for side effects. A reliable system to highlight the need for physical health checks was also missing and the team did not have sufficient equipment to perform the necessary checks. Identifying these barriers should enable improvements in physical health and HDAT monitoring which can be re-audited.

Data fusion approaches for structural health monitoring and system identification: Past, present, and future

2018 ◽  
Vol 19 (2) ◽  
pp. 552-586 ◽  
Author(s):  
Rih-Teng Wu ◽  
Mohammad Reza Jahanshahi
Keyword(s):  
Structural Health Monitoring ◽  
Data Fusion ◽  
Health Monitoring ◽  
Health Assessment ◽  
Heterogeneous Data ◽  
Future Research ◽  
Theoretical Concepts ◽  
Structural Health ◽  
Multiple Sensors ◽  
Robust Decisions

During the past decades, significant efforts have been dedicated to develop reliable methods in structural health monitoring. The health assessment for the target structure of interest is achieved through the interpretation of collected data. At the beginning of the 21st century, the rapid advances in sensor technologies and data acquisition platforms have led to the new era of Big Data, where a huge amount of heterogeneous data are collected by a variety of sensors. The increasing accessibility and diversity of the data resources provide new opportunities for structural health monitoring, while the aggregation of information obtained from multiple sensors to make robust decisions remains a challenging problem. This article presents a comprehensive review of the recent data fusion applications in structural health monitoring. State-of-the-art theoretical concepts and applications of data fusion in structural health monitoring are presented. Challenges for data fusion in structural health monitoring are discussed, and a roadmap is provided for future research in this area.

scholarly journals Practical Implementation of Structural Health Monitoring in Multi-Story Buildings

Buildings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 263
Author(s):  
Arvindan Sivasuriyan ◽  
D.S. Vijayan ◽  
Wojciech Górski ◽  
Łukasz Wodzyński ◽  
Magdalena Daria Vaverková ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Real Time ◽  
Health Monitoring ◽  
Sensor Technology ◽  
Future Research ◽  
Practical Implementation ◽  
Building Structures ◽  
Element Analysis ◽  
Self Monitoring ◽  
Structural Health

This study investigated operational and structural health monitoring (SHM) as well as damage evaluations for building structures. The study involved damage detection and the assessment of buildings by placing sensors and by assuming weak areas, and considered situations of assessment and self-monitoring. From this perspective, advanced sensor technology and data acquisition techniques can systematically monitor a building in real time. Furthermore, the structure’s response and behavior were observed and recorded to predict the damage to the building. In this paper, we discuss the real-time monitoring and response of buildings, which includes both static and dynamic analyses along with numerical simulation studies such as finite element analysis (FEA), and recommendations for the future research and development of SHM are made.

scholarly journals A Review of Recent Distributed Optical Fiber Sensors Applications for Civil Engineering Structural Health Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1818
Author(s):  
Mattia Francesco Bado ◽  
Joan R. Casas
Keyword(s):  
Structural Health Monitoring ◽  
Optical Fiber ◽  
Health Monitoring ◽  
Optical Fiber Sensors ◽  
Vibration Monitoring ◽  
Fiber Sensors ◽  
Structural Health ◽  
Comprehensive Collection ◽  
Monitoring Tools ◽  
Distributed Optical Fiber

The present work is a comprehensive collection of recently published research articles on Structural Health Monitoring (SHM) campaigns performed by means of Distributed Optical Fiber Sensors (DOFS). The latter are cutting-edge strain, temperature and vibration monitoring tools with a large potential pool, namely their minimal intrusiveness, accuracy, ease of deployment and more. Its most state-of-the-art feature, though, is the ability to perform measurements with very small spatial resolutions (as small as 0.63 mm). This review article intends to introduce, inform and advise the readers on various DOFS deployment methodologies for the assessment of the residual ability of a structure to continue serving its intended purpose. By collecting in a single place these recent efforts, advancements and findings, the authors intend to contribute to the goal of collective growth towards an efficient SHM. The current work is structured in a manner that allows for the single consultation of any specific DOFS application field, i.e., laboratory experimentation, the built environment (bridges, buildings, roads, etc.), geotechnical constructions, tunnels, pipelines and wind turbines. Beforehand, a brief section was constructed around the recent progress on the study of the strain transfer mechanisms occurring in the multi-layered sensing system inherent to any DOFS deployment (different kinds of fiber claddings, coatings and bonding adhesives). Finally, a section is also dedicated to ideas and concepts for those novel DOFS applications which may very well represent the future of SHM.

A Comparison Between Self-Reported and Investigator-Measured Cardiovascular Risk-Related Biometric Numbers

2021 ◽  
pp. 019394592110135
Author(s):  
Sohye Lee ◽  
Catherine Pantik ◽  
Sree Duggirala ◽  
Ruth Lindquist
Keyword(s):  
Cardiovascular Risk ◽  
Fasting Blood Glucose ◽  
Health Assessment ◽  
Density Lipoprotein ◽  
Educational Interventions ◽  
Personal Knowledge ◽  
Future Research ◽  
Cardiovascular Risks ◽  
Convenience Sample ◽  
Glucose Levels

The purpose of this study was to examine individuals’ knowledge of cardiovascular risk-related biometric numbers and to compare self-reported and investigator-measured numbers in a convenience sample of adults in the Midwest region. Sociodemographic data and personal knowledge of cardiovascular risk-related biometric numbers were assessed using self-reported questionnaires. Investigators conducted health assessments to obtain biometric numbers. Among the 224 participants, participants’ reported knowledge about their cardiovascular risk-related biometric numbers was low, especially for high-density lipoprotein and fasting blood glucose levels. Participants’ knowledge was associated with education level and the recency of their last healthcare visit for health assessment. We found statistically significant mean differences between self-reported and investigator-measured blood pressure, and weight. This study found that there were discrepancies between self-reported and investigator-measured cardiovascular risk-related numbers. Future research is needed to develop educational interventions to improve personal knowledge of cardiovascular risks.

scholarly journals Unobtrusive Health Monitoring in Private Spaces: The Smart Home

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 864 ◽  
Author(s):  
Ju Wang ◽  
Nicolai Spicher ◽  
Joana M. Warnecke ◽  
Mostafa Haghi ◽  
Jonas Schwartze ◽  
...  
Keyword(s):  
Literature Review ◽  
Health Monitoring ◽  
Smart Home ◽  
State Of The Art ◽  
Home Health ◽  
Environmental Data ◽  
Behavioral Data ◽  
Sensor Technology ◽  
Current Sensor ◽  
Home Health Monitoring

With the advances in sensor technology, big data, and artificial intelligence, unobtrusive in-home health monitoring has been a research focus for decades. Following up our research on smart vehicles, within the framework of unobtrusive health monitoring in private spaces, this work attempts to provide a guide to current sensor technology for unobtrusive in-home monitoring by a literature review of the state of the art and to answer, in particular, the questions: (1) What types of sensors can be used for unobtrusive in-home health data acquisition? (2) Where should the sensors be placed? (3) What data can be monitored in a smart home? (4) How can the obtained data support the monitoring functions? We conducted a retrospective literature review and summarized the state-of-the-art research on leveraging sensor technology for unobtrusive in-home health monitoring. For structured analysis, we developed a four-category terminology (location, unobtrusive sensor, data, and monitoring functions). We acquired 912 unique articles from four relevant databases (ACM Digital Lib, IEEE Xplore, PubMed, and Scopus) and screened them for relevance, resulting in n=55 papers analyzed in a structured manner using the terminology. The results delivered 25 types of sensors (motion sensor, contact sensor, pressure sensor, electrical current sensor, etc.) that can be deployed within rooms, static facilities, or electric appliances in an ambient way. While behavioral data (e.g., presence (n=38), time spent on activities (n=18)) can be acquired effortlessly, physiological parameters (e.g., heart rate, respiratory rate) are measurable on a limited scale (n=5). Behavioral data contribute to functional monitoring. Emergency monitoring can be built up on behavioral and environmental data. Acquired physiological parameters allow reasonable monitoring of physiological functions to a limited extent. Environmental data and behavioral data also detect safety and security abnormalities. Social interaction monitoring relies mainly on direct monitoring of tools of communication (smartphone; computer). In summary, convincing proof of a clear effect of these monitoring functions on clinical outcome with a large sample size and long-term monitoring is still lacking.

Validation of Wearable Sensor Technology to Measure Social Proximity of Young Children With Autism Spectrum Disorders

2021 ◽  
pp. 108835762110282
Author(s):  
Sarah N. Douglas ◽  
Yan Shi ◽  
Saptarshi Das ◽  
Subir Biswas
Keyword(s):  
Autism Spectrum Disorders ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Sensor System ◽  
Sensor Data ◽  
Sensor Technology ◽  
Future Research ◽  
Social Proximity ◽  
Children With Asd ◽  
Spectrum Disorders

Children with autism spectrum disorders (ASD) struggle to develop appropriate social skills, which can lead to later social rejection, isolation, and mental health concerns. Educators play an important role in supporting and monitoring social skill development for children with ASD, but the tools used by educators are often tedious, lack suitable sensitivity, provide limited information to plan interventions, and are time-consuming. Therefore, we conducted a study to evaluate the use of a sensor system to measure social proximity between three children with ASD and their peers in an inclusive preschool setting. We compared video-coded data with sensor data using point-by-point agreement to measure the accuracy of the sensor system. Results suggest that the sensor system can adequately measure social proximity between children with ASD and their peers. The next steps for sensor system validation are discussed along with clinical and educational implications, limitations, and future research directions.

scholarly journals Physical monitoring and advice: absence of evidence is not evidence of absence

2015 ◽  
Vol 21 (2) ◽  
pp. 75-77
Author(s):  
Katharine Smith
Keyword(s):  
Mental Illness ◽  
Physical Health ◽  
Health Monitoring ◽  
Poor Quality ◽  
Future Research ◽  
Cost Benefits ◽  
Cochrane Reviews ◽  
Different Types ◽  
Physical Health Problems ◽  
General Physical

SummaryIndividuals with severe mental illness have increased rates of physical health problems and reduced life expectancy. As a vulnerable population, they have been identified as needing increased physical health monitoring and treatment. The first of two Cochrane reviews considered here assessed the evidence for the benefit of monitoring but found no studies that could be included. The second reviewed the evidence for provision of general physical healthcare advice. Although the results were suggestive of benefit, the evidence, where available, was of poor quality. These reviews highlight an important area for future research to evaluate the relative health and cost benefits of different types of intervention.

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