Early detection of Myocardial Infarction using WBAN

International audienceCardiovascular diseases are the leading cause of death in the world, and Myocardial Infarction (MI) is the most serious one among those diseases. Patient monitoring for an early detection of MI is important to alert medical assistance and increase the vital prognostic of patients. With the development of wearable sensor devices having wireless transmission capabilities, there is a need to develop real-time applications that are able to accurately detect MI non-invasively. In this paper, we propose a new approach for early detection of MI using wireless body area networks. The proposed approach analyzes the patient electrocardiogram (ECG) in real time and extracts from each ECG cycle the ST elevation which is a significant indicator of an upcoming MI. We use the sequential change point detection algorithm CUmulative SUM (CUSUM) to early detect any deviation in ST elevation time series, and to raise an alarm for healthcare professionals. The experimental results on the ECG of real patients show that our proposed approach can detect MI with low delay and high accuracy

A Mobile Healthcare Solution for Ambient Assisted Living Environments

Elderly people need regular healthcare services and, several times, are dependent of physicians’ personal attendance. This dependence raises several issues to elders, such as, the need to travel and mobility support. Ambient Assisted Living (AAL) and Mobile Health (m-Health) services and applications offer good healthcare solutions that can be used both on indoor and in mobility environments. This dissertation presents an ambient assisted living (AAL) solution for mobile environments. It includes elderly biofeedback monitoring using body sensors for data collection offering support for remote monitoring. The used sensors are attached to the human body (such as the electrocardiogram, blood pressure, and temperature). They collect data providing comfort, mobility, and guaranteeing efficiency and data confidentiality. Periodic collection of patients’ data is important to gather more accurate measurements and to avoid common risky situations, like a physical fall may be considered something natural in life span and it is more dangerous for senior people. One fall can out a life in extreme cases or cause fractures, injuries, but when it is early detected through an accelerometer, for example, it can avoid a tragic outcome. The presented proposal monitors elderly people, storing collected data in a personal computer, tablet, or smartphone through Bluetooth. This application allows an analysis of possible health condition warnings based on the input of supporting charts, and real-time bio-signals monitoring and is able to warn users and the caretakers. These mobile devices are also used to collect data, which allow data storage and its possible consultation in the future. The proposed system is evaluated, demonstrated and validated through a prototype and it is ready for use. The watch Texas ez430-Chronos, which is capable to store information for later analysis and the sensors Shimmer who allow the creation of a personalized application that it is capable of measuring biosignals of the patient in real time is described throughout this dissertation

Pragmatic Evaluation of Health Monitoring & Analysis Models from an Empirical Perspective

Implementing and deploying several linked modules that can conduct real-time analysis and recommendation of patient datasets is necessary for designing health monitoring and analysis models. These databases include, but are not limited to, blood test results, computer tomography (CT) scans, MRI scans, PET scans, and other imaging tests. A combination of signal processing and image processing methods are used to process them. These methods include data collection, pre-processing, feature extraction and selection, classification, and context-specific post-processing. Researchers have put forward a variety of machine learning (ML) and deep learning (DL) techniques to carry out these tasks, which help with the high-accuracy categorization of these datasets. However, the internal operational features and the quantitative and qualitative performance indicators of each of these models differ. These models also demonstrate various functional subtleties, contextual benefits, application-specific constraints, and deployment-specific future research directions. It is difficult for researchers to pinpoint models that perform well for their application-specific use cases because of the vast range of performance. In order to reduce this uncertainty, this paper discusses a review of several Health Monitoring & Analysis Models in terms of their internal operational features & performance measurements. Readers will be able to recognise models that are appropriate for their application-specific use cases based on this discussion. When compared to other models, it was shown that Convolutional Neural Networks (CNNs), Masked Region CNN (MRCNN), Recurrent NN (RNN), Q-Learning, and Reinforcement learning models had greater analytical performance. They are hence suitable for clinical use cases. These models' worse scaling performance is a result of their increased complexity and higher implementation costs. This paper compares evaluated models in terms of accuracy, computational latency, deployment complexity, scalability, and deployment cost metrics to analyse such scenarios. This comparison will help users choose the best models for their performance-specific use cases. In this article, a new Health Monitoring Metric (HMM), which integrates many performance indicators to identify the best-performing models under various real-time patient settings, is reviewed to make the process of model selection even easier for real-time scenarios

The era of nano-bionic: 2D materials for wearable and implantable body sensors

Nano-bionics have the potential of revolutionizing modern medicine. Among nano-bionic devices, body sensors allow to monitor in real-time the health of patients, to achieve personalized medicine, and even to restore or enhance human functions. The advent of two-dimensional (2D) materials is facilitating the manufacturing of miniaturized and ultrathin bioelectronics, that can be easily integrated in the human body. Their unique electronic properties allow to efficiently transduce physical and chemical stimuli into electric current. Their flexibility and nanometric thickness facilitate the adaption and adhesion to human body. The low opacity permits to obtain transparent devices. The good cellular adhesion and reduced cytotoxicity are advantageous for the integration of the devices in vivo. Herein we review the latest and more significant examples of 2D material-based sensors for health monitoring, describing their architectures, sensing mechanisms, advantages and, as well, the challenges and drawbacks that hampers their translation into commercial clinical devices

The era of nano-bionic: 2D materials for wearable and implantable body sensors

Nano-bionics have the potential of revolutionizing modern medicine. Among nano-bionic devices, body sensors allow to monitor in real-time the health of patients, to achieve personalized medicine, and even to restore or enhance human functions. The advent of two-dimensional (2D) materials is facilitating the manufacturing of miniaturized and ultrathin bioelectronics, that can be easily integrated in the human body. Their unique electronic properties allow to efficiently transduce physical and chemical stimuli into electric current. Their flexibility and nanometric thickness facilitate the adaption and adhesion to human body. The low opacity permits to obtain transparent devices. The good cellular adhesion and reduced cytotoxicity are advantageous for the integration of the devices in vivo. Herein we review the latest and more significant examples of 2D material-based sensors for health monitoring, describing their architectures, sensing mechanisms, advantages and, as well, the challenges and drawbacks that hampers their translation into commercial clinical devices

VCare: A Personal Emergency Response System to Promote Safe and Independent Living Among Elders Staying by Themselves in Community or Residential Settings

‘Population aging’ is a growing concern for most of us living in the twenty first century, primarily because many of us in the next few years will have a senior person to care for - spending money towards their healthcare expenditures AND/OR having to balance a full-time job with the responsibility of care-giving, travelling from another city to be with this elderly citizen who might be our parent, grand-parent or even community elders. As informal care-givers, if somehow we were able to monitor the day-to-day activities of our elderly dependents, and be alerted when wrong happens to them that would be of great help and lower the care-giving burden considerably. Information and Communication Technology (ICT) can certainly help in such a scenario, with tools and techniques that ensure safe living for the individual we are caring for, and save us from a lot of worry by providing us with anytime access into their lives or activities, and as a result check their functional state. However, we should be mindful of the tactics that could be adopted by harm causers to steal data stored in these products and try to curb the associated service costs. In short, we are in need of robust, cost-effective, useful, and secure solutions to help elders in our society to ‘age gracefully’. This work is a little step taken towards that direction. ‘Population aging’ is a growing concern for most of us living in the twenty first century, primarily because many of us in the next few years will have a senior person to care for - spending money towards their healthcare expenditures AND/OR having to balance a full-time job with the responsibility of care-giving, travelling from another city to be with this elderly citizen who might be our parent, grand-parent or even community elders. As informal care-givers, if somehow we were able to monitor the day-to-day activities of our elderly dependents, and be alerted when wrong happens to them that would be of great help and lower the care-giving burden considerably. Information and Communication Technology (ICT) can certainly help in such a scenario, with tools and techniques that ensure safe living for the individual we are caring for, and save us from a lot of worry by providing us with anytime access into their lives or activities, and as a result check their functional state. However, we should be mindful of the tactics that could be adopted by harm causers to steal data stored in these products and try to curb the associated service costs. In short, we are in need of robust, cost-effective, useful, and secure solutions to help elders in our society to ‘age gracefully’. This work is a little step taken towards that direction. Advisor: Tadeusz Wysock

A Wireless Emergency Telemedicine System for Patients Monitoring and Diagnosis

Recently, remote healthcare systems have received increasing attention in the last decade, explaining why intelligent systems with physiology signal monitoring for e-health care are an emerging area of development. Therefore, this study adopts a system which includes continuous collection and evaluation of multiple vital signs, long-term healthcare, and a cellular connection to a medical center in emergency case and it transfers all acquired raw data by the internet in normal case. The proposed system can continuously acquire four different physiological signs, for example, ECG, SpO2, temperature, and blood pressure and further relayed them to an intelligent data analysis scheme to diagnose abnormal pulses for exploring potential chronic diseases. The proposed system also has a friendly web-based interface for medical staff to observe immediate pulse signals for remote treatment. Once abnormal event happened or the request to real-time display vital signs is confirmed, all physiological signs will be immediately transmitted to remote medical server through both cellular networks and internet. Also data can be transmitted to a family member’s mobile phone or doctor’s phone through GPRS. A prototype of such system has been successfully developed and implemented, which will offer high standard of healthcare with a major reduction in cost for our society