Health Monitoring
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Actuators ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 175
Author(s):  
Mohamed A. A. Ismail ◽  
Simon Wiedemann ◽  
Colin Bosch ◽  
Christoph Stuckmann

Electro-mechanical actuators (EMAs) are a primary actuation technology for unmanned aerial vehicles (UAVs). Intensive research has been conducted for designing and evaluating fault-tolerant EMAs for flight controls of UAVs to ensure their compliance with new airworthiness requirements for safe operation over civilian zones. The state-of-the-art research involves several fault-tolerant architectures for EMAs based on parallel electric motors or a single motor with internal fault-tolerant features. In this study, a fault-tolerant architecture is introduced, comprised of two serial electric motors driven by two isolated controllers and a health monitoring system. The procedures of developing various fault-tolerant features are discussed with a deep focus on designing health monitoring functions and evaluating their influence on the overall actuator stability and availability. This work has been conducted and evaluated based on operational data for ALAADy: a heavy gyrocopter-type UAV at DLR (German Aerospace Center).


Author(s):  
Vladimir Ulansky ◽  
Igor Machalin ◽  
Iryna Terentyeva

The article provides a methodology for assessing the trustworthiness of health monitoring the dismounted avionics systems with automated test equipment (ATE). The indicators include the probabilities of false-positive, false-negative, true-positive, and true-negative. For the first time, we introduced into consideration the instability of the source of stimulus signal (SSS), the random and systematic component of the measuring channel error, and the reliability characteristics of the systems themselves. We consider a specific case of an exponential distribution of permanent failures and intermittent faults and derive formulas for calculating the trustworthiness indicators. Numerical calculations illustrate how the probabilities of correct and incorrect decisions depend on accuracy parameters. We show that the probabilities of false-positive and false-negative increase much faster than the probabilities of true-positive and true-negative decrease when the standard deviation of stimulus signal increases. For a Very High-Frequency Omni-Directional Range (VOR) receiver, we demonstrate that even with a zero random error generated by the source of the stimulus signal, the probabilities of false-positive and false-negative are different from zero.


2021 ◽  
pp. 1-7
Author(s):  
Helen Anderson ◽  
Anna Kolliakou ◽  
Daniel Harwood ◽  
Nicola Funnell ◽  
Robert Stewart ◽  
...  

Aims and method To support safe prescribing of antipsychotics in dementia, antipsychotic monitoring forms were embedded into our electronic health records. We present a review of the data collected on these forms to assess prescribing and identify areas for improvement in our practice and processes. Data were extracted from the structured fields of antipsychotic initiation and review forms completed between 1 January 2018 and 31 January 2020. Results We identified gaps in practice where improvements could be made, mainly with regard to physical health monitoring (and particularly electrocardiograms, performed in only 50% of patients) and the low (less than 50%) recorded use of non-pharmacological interventions for behavioural and psychological symptoms of dementia. In addition, antipsychotic treatment was continued despite lack of benefit in almost 10% of reviews. Clinical implications We advocate for recommendations on physical health monitoring of people with dementia taking antipsychotics to be added to the National Institute for Health and Care Excellence guidance on dementia and the Prescribing Observatory for Mental Health (POMH-UK) national audit.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Yue Hou ◽  
Zhaoyu Li ◽  
Ziyu Wang ◽  
Hongyu Yu

AbstractHighly reliable signal recording with low electrode-skin impedance makes the microneedle array electrode (MAE) a promising candidate for biosignal sensing. However, when used in long-term health monitoring for some incidental diseases, flexible microneedles with perfectly skin-tight fit substrates lead to sweat accumulation inside, which will not only affect the signal output but also trigger some skin allergic reactions. In this paper, a flexible MAE on a Miura-ori structured substrate is proposed and fabricated with two-directional in-plane bendability. The results from the comparison tests show enhanced performance in terms of (1) the device reliability by resisting peeling off of the metal layer from the substrate during the operation and (2) air ventilation, achieved from the air-circulating channels, to remove sweat. Bio-signal recordings of electrocardiography (ECG), as well as electromyography (EMG) of the biceps brachii, in both static and dynamic states, are successfully demonstrated with superior accuracy and long-term stability, demonstrating the great potential in health monitoring applications.


Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 4948
Author(s):  
Lourdes S. M. Alwis ◽  
Kort Bremer ◽  
Bernhard Roth

The last decade has seen rapid developments in the areas of carbon fiber technology, additive manufacturing technology, sensor engineering, i.e., wearables, and new structural reinforcement techniques. These developments, although from different areas, have collectively paved way for concrete structures with non-corrosive reinforcement and in-built sensors. Therefore, the purpose of this effort is to bridge the gap between civil engineering and sensor engineering communities through an overview on the up-to-date technological advances in both sectors, with a special focus on textile reinforced concrete embedded with fiber optic sensors. The introduction section highlights the importance of reducing the carbon footprint resulting from the building industry and how this could be effectively achieved by the use of state-of-the-art reinforcement techniques. Added to these benefits would be the implementations on infrastructure monitoring for the safe operation of structures through their entire lifespan by utilizing sensors, specifically, fiber optic sensors. The paper presents an extensive description on fiber optic sensor engineering that enables the incorporation of sensors into the reinforcement mechanism of a structure at its manufacturing stage, enabling effective monitoring and a wider range of capabilities when compared to conventional means of structural health monitoring. In future, these developments, when combined with artificial intelligence concepts, will lead to distributed sensor networks for smart monitoring applications, particularly enabling such distributed networks to be implemented/embedded at their manufacturing stage.


Author(s):  
Sougata Karmakar

IOT is one of the flourishing fields in coming years and it has a vital role in the health care sector. IOT helps us to connect with people by collecting major parameters of the patients directly through some wearable devices transmitted to smartphones and laptops of the authorized person using the cloud server. We are using devices which gives flexible operations to both for the patients and also for healthcare professionals. IOT is slowly becoming a trend in recent times by improvement in the wireless sensor networks. We are fetching such parameters like body temperature, oxygen saturation percentage, heart rate by using NodeMCU WIFI module and cloud computing. Patients with serious health issues can be quickly identified and can be provide a rapid solution by this health monitoring system. And by using BLYNK mobile application we can have those measurements of the parameters from anywhere in the world.


Author(s):  
Mohammad Hanan Bhat

: Plant health monitoring has been a significant field of research since a very long time. The scope of this research work conducted lies in the vast domain of plant pathology with its applications extending in the field of agriculture production monitoring to forest health monitoring. It deals with the data collection techniques based on IOT, pre-processing and post-processing of Image dataset and identification of disease using deep learning model. Therefore, providing a multi-modal end-to-end approach for plant health monitoring. This paper reviews the various methods used for monitoring plant health remotely in a non-invasive manner. An end-to-end low cost framework has been proposed for monitoring plant health by using IOT based data collection methods and cloud computing for a single-point-of-contact for the data storage and processing. The cloud agent gateway connects the devices and collects the data from sensors to ensure a single source of truth. Further, the deep learning computational infrastructure provided by the public cloud infrastructure is exploited to train the image dataset and derive the plant health status


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