Snake Bite in South Asia: A Review

Snake bite is one of the most neglected public health issues in poor rural communities living in the tropics. Because of serious misreporting, the true worldwide burden of snake bite is not known. South Asia is the world's most heavily affected region, due to its high population density, widespread agricultural activities, numerous venomous snake species and lack of functional snake bite control programs. Despite increasing knowledge of snake venoms' composition and mode of action, good understanding of clinical features of envenoming and sufficient production of antivenom by Indian manufacturers, snake bite management remains unsatisfactory in this region. Field diagnostic tests for snake species identification do not exist and treatment mainly relies on the administration of antivenoms that do not cover all of the important venomous snakes of the region. Care-givers need better training and supervision, and national guidelines should be fed by evidence-based data generated by well-designed research studies. Poorly informed rural populations often apply inappropriate first-aid measures and vital time is lost before the victim is transported to a treatment centre, where cost of treatment can constitute an additional hurdle. The deficiency of snake bite management in South Asia is multi-causal and requires joint collaborative efforts from researchers, antivenom manufacturers, policy makers, public health authorities and international funders

The myasthenic patient in crisis: an update of the management in Neurointensive Care Unit

Myasthenia gravis (MG) is an autoimmune disorder affecting neuromuscular transmission leading to generalized or localized muscle weakness due most frequently to the presence of autoantibodies against acetylcholine receptors in the postsynaptic motor end-plate. Myasthenic crisis (MC) is a complication of MG characterized by worsening muscle weakness, resulting in respiratory failure that requires intubation and mechanical ventilation. It also includes postsurgical patients, in whom exacerbation of muscle weakness from MG causes a delay in extubation. MC is a very important, serious, and reversible neurological emergency that affects 20–30% of the myasthenic patients, usually within the first year of illness and maybe the debut form of the disease. Most patients have a predisposing factor that triggers the crisis, generally an infection of the respiratory tract. Immunoglobulins, plasma exchange, and steroids are the cornerstones of immunotherapy. Today with the modern neurocritical care, mortality rate of MC is less than 5%

2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings

Blockchain and Mobile Edge Computing (MEC) are newly emerging technologies with great potential to revolutionize healthcare. This paper proposes a new decentralized healthcare architecture for distributed Electronic Medical Records (EMRs) sharing among federated hospitals based on blockchain and MEC. Unlike the existing schemes that often rely on a third-party for healthcare management, we focus on a fully decentralized access control solution by using smart contracts that enable EMRs access verification at the edge of the network without requiring any central authority. Moreover, a decentralized interplanetary file system (IPFS) platform is also integrated with smart contracts over the MEC network, which significantly reduces data retrieval latency and enhances security for EMRs sharing. The experimental results and analysis show the superior performance of the proposed scheme over the existing ones in terms of reduced data retrieval latency, enhanced blockchain performance, and security guarantees

Integration of Blockchain and Cloud of Things: Architecture, Applications and Challenges

The blockchain technology is taking the world by storm. Blockchain with its decentralized, transparent and secure nature has emerged as a disruptive technology for the next generation of numerous industrial applications. One of them is Cloud of Things enabled by the combination of cloud computing and Internet of Things. In this context, blockchain provides innovative solutions to address challenges in Cloud of Things in terms of decentralization, data privacy and network security, while Cloud of Things offer elasticity and scalability functionalities to improve the efficiency of blockchain operations. Therefore, a novel paradigm of blockchain and Cloud of Things integration, called BCoT, has been widely regarded as a promising enabler for a wide range of application scenarios. In this article, we present a state-of-the-art review on the BCoT integration to provide general readers with an overview of the BCoT in various aspects, including background knowledge, motivation, and integrated architecture. Particularly, we also provide an in-depth survey of BCoT applications in different use-case domains such as smart healthcare, smart city, smart transportation and smart industry. Then, we review the recent BCoT developments with the emerging blockchain and cloud platforms, services, and research projects. Finally, some important research challenges and future directions are highlighted to spur further research in this promising area

BEdgeHealth: A Decentralized Architecture for Edge-Based IoMT Networks Using Blockchain

The healthcare industry has witnessed significant transformations in e-health services by using mobile-edge computing (MEC) and blockchain to facilitate healthcare operations. Many MEC-blockchain-based schemes have been proposed, but some critical technical challenges still remain, such as low Quality of Services (QoS), data privacy, and system security vulnerabilities. In this article, we propose a new decentralized health architecture, called BEdgeHealth that integrates MEC and blockchain for data offloading and data sharing in distributed hospital networks. First, a data offloading scheme is proposed where mobile devices can offload health data to a nearby MEC server for efficient computation with privacy awareness. Moreover, we design a data-sharing scheme, which enables data exchanges among healthcare users by leveraging blockchain and interplanetary file system. Particularly, a smart contract-based authentication mechanism is integrated with MEC to perform decentralized user access verification at the network edge without requiring any central authority. The real-world experiment results and evaluations demonstrate the effectiveness of the proposed BEdgeHealth architecture in terms of improved QoS with data privacy and security guarantees, compared to the existing schemes

BMEiCON 2017 - 10th Biomedical Engineering International Conference

© 2017 IEEE. The aim of this research is to improve the methodology for human limb attitude estimation using wearable sensors. The orientations of these limb segments are measured using inertial/magnetic sensor modules. Such sensor modules typically contain a triad of orthogonally mounted accelerometer and magnetometer. The accelerometer is used to measure the gravity vector that is relative to the coordinated frame of the sensor module. Magnetometer serve a similar function for a local magnetic vector. Based on these two observations, we can formulate a constrained nonlinear orientation estimation of the human upper kinematics, based on the Wahba problem formulation. Several algorithms had been proposed earlier for solving this problem but all those currently solutions focused on minimizing the lost function (or cost function) numerically. As a result, these methods led to errors owing to unexpected noise, internal and external impacts such as, drift, vibration, force changes, etc. Hence, to mitigate this issue and enhance the effect of the solutions in tackling Wahba problem, a reachable workspace is defined in this work in addition to the current research algorithms

Qualification of Wrist Functional Performance During Dart Thrower's Movement

Recently, numerous comprehensive studies have been concentrating on the intricate kinematics of the wrist joint functionality captured with dart thrower's movement. It is envisaged that the wrist capability in performing daily activities can be more accurately characterized or encapsulated in the dart thrower's movement. This study examines the characteristic function of wrist movements during dart-throwing motion using only gyroscopic data measured from inertial sensors. A multi-dimensional form of dart throwing trajectory is described using quaternion representation associated with distance metric to quantitatively validate the functional wrist performance between two cohorts; healthy controls and patients. Eight normal subjects and eight patients engaged in a series of clinical trials conducted after undergoing post-surgical reconstructive procedures of the wrist joint. The discriminative results in terms of silhouette clustering evaluation show that the use of distance metric values based quaternion trajectory is well-matched consistently with subjective expert assessments. Our proposed approach captures the relative motions underpinning the wrist joint instead of relying on the traditional measure based on the range of motion measure. Therefore, this paper proposes a reliable approach to dynamically capture the wrist functionality during dart thrower's movement; a movement envisaged to describe the ability to engage in daily life activities. These quantitative outcomes in terms of measurement consistency will provide insightful information in understanding the significant changes in wrist joint signatures associated with various scenarios

Sensing and characterization of the wrist using dart thrower's movement

The dart-throwing movement is engaged to capture wrist movements involved in numerous daily activities. This paper focuses on robust implementation in a wearable platform-based inertial sensors enhance opportunities for exploring day-to-day changes of wrist joint when performing dart-throwing motion. The kinematic characterization of the underlying movement is described in terms of time-series quaternions measured from gyroscope data. The distance metrics between these representations are used to compare quantitatively wrist kinematic performance against clinical observations. A clinical trial was conducted engaging five normal subjects and 10 patients undergoing a series of post-surgical rehabilitation programs. The approach classifies effectively the patients from normal subjects and alleviates the need for range of motion measurements of the wrist joint implying the quaternion trajectory associated with classical dynamic time warping as a useful kinematic description for dart thrower's movement in assessing and characterizing the wrist performance. Clustering and classification results confirm that this proposed method is well-correlated with clinical assessments based on high positive correlation coefficients. The primary objective of this paper is to enhance the uptake and promote the uses of wearable sensors in longer term monitoring scenarios particularly relevant to non-clinical environments