scholarly journals Machine-Learning-Based Elderly Stroke Monitoring System Using Electroencephalography Vital Signals

2021 ◽  
Vol 11 (4) ◽  
pp. 1761
Author(s):  
Yoon-A Choi ◽  
Sejin Park ◽  
Jong-Arm Jun ◽  
Chee Meng Benjamin Ho ◽  
Cheol-Sig Pyo ◽  
...  

Stroke is the third highest cause of death worldwide after cancer and heart disease, and the number of stroke diseases due to aging is set to at least triple by 2030. As the top three causes of death worldwide are all related to chronic disease, the importance of healthcare is increasing even more. Models that can predict real-time health conditions and diseases using various healthcare services are attracting increasing attention. Most diagnosis and prediction methods of stroke for the elderly involve imaging techniques such as magnetic resonance imaging (MRI). It is difficult to rapidly and accurately diagnose and predict stroke diseases due to the long testing times and high costs associated with MRI. Thus, in this paper, we design and implement a health monitoring system that can predict the precursors of stroke diseases in the elderly in real time during daily walking. First, raw electroencephalography (EEG) data from six channels were preprocessed via Fast Fourier Transform (FFT). The raw EEG power values were then extracted from the raw spectra: alpha (α), beta (β), gamma (γ), delta (δ), and theta (θ) as well as the low β, high β, and θ to β ratio, respectively. The experiments in this paper confirm that the important features of EEG biometric signals alone during walking can accurately determine stroke precursors and occurrence in the elderly with more than 90% accuracy. Further, the Random Forest algorithm with quartiles and Z-score normalization validates the clinical significance and performance of the system proposed in this paper with a 92.51% stroke prediction accuracy. The proposed system can be implemented at a low cost, and it can be applied for early disease detection and prediction using the precursor symptoms of real-time stroke. Furthermore, it is expected that it will be able to detect other diseases such as cancer and heart disease in the future.

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Priyanka Kakria ◽  
N. K. Tripathi ◽  
Peerapong Kitipawang

Online telemedicine systems are useful due to the possibility of timely and efficient healthcare services. These systems are based on advanced wireless and wearable sensor technologies. The rapid growth in technology has remarkably enhanced the scope of remote health monitoring systems. In this paper, a real-time heart monitoring system is developed considering the cost, ease of application, accuracy, and data security. The system is conceptualized to provide an interface between the doctor and the patients for two-way communication. The main purpose of this study is to facilitate the remote cardiac patients in getting latest healthcare services which might not be possible otherwise due to low doctor-to-patient ratio. The developed monitoring system is then evaluated for 40 individuals (aged between 18 and 66 years) using wearable sensors while holding an Android device (i.e., smartphone under supervision of the experts). The performance analysis shows that the proposed system is reliable and helpful due to high speed. The analyses showed that the proposed system is convenient and reliable and ensures data security at low cost. In addition, the developed system is equipped to generate warning messages to the doctor and patient under critical circumstances.


2018 ◽  
Vol 20 (4) ◽  
pp. 498 ◽  
Author(s):  
Cosmin Caraiani ◽  
Yi Dong ◽  
Anthony G. Rudd ◽  
Christoph F. Dietrich

Even if imaging has developed considerably during the last decades there still exist several factors which limit its capacities. These factors can either limit the usage of a technique or degrade images making them difficult to interpret. Magnetic resonance imaging (MRI) has, as an absolute contraindication, the presence of metallic devices marked as “MRI unsafe” and metallic foreign bodies close to the eye or vital structures. Claustrophobia and artefacts reduce the application and performance of MRI in a significant proportion of patients. The major disadvantages of computed tomography(CT) are the exposure to ionizing radiation inducing malignancies especially in pediatric patients and the risk of contrast induced allergies and nephropathy. Ultrasound is a safe, easily available and low-cost imaging technique without significant side effects for the patient. Obesity or bloating can severely limit ultrasound capacities.This paper written by radiologists and clinicians, highlights the main reasons leading to inadequate imaging and points out solutions to avoid inaccurate diagnosis due to incomplete imaging or presence of artifacts.


2019 ◽  
Author(s):  
Jeba Anandh S ◽  
Anandharaj M ◽  
Aswinrajan J ◽  
Karankumar G ◽  
Karthik P

2020 ◽  
Vol 17 (3) ◽  
pp. 867-890
Author(s):  
Jun-Hee Choi ◽  
Hyun-Sug Cho

The gravimetric method, which is mainly used among particulate matter (PM) measurement methods, includes the disadvantages that it cannot measure PM in real time and it requires expensive equipment. To overcome these disadvantages, we have developed a light scattering type PM sensor that can be manufactured at low cost and can measure PM in real time. We have built a big data system that can systematically store and analyze the data collected through the developed sensor, as well as an environment where PM states can be monitored mobile in real time using such data. In addition, additional studies were conducted to analyze and correct the collected big data to overcome the problem of low accuracy, which is a disadvantage of the light scattering type PM sensor. We used a linear correction method and proceeded to adopt the most suitable value based on error and accuracy.


Author(s):  
L.P.S.S.K. Dayananda ◽  
A. Narmilan ◽  
P. Pirapuraj

Background: Weather monitoring is an important aspect of crop cultivation for reducing economic loss while increasing productivity. Weather is the combination of current meteorological components, such as temperature, wind direction and speed, amount and kind of precipitation, sunshine hours and so on. The weather defines a time span ranging from a few hours to several days. The periodic or continuous surveillance or the analysis of the status of the atmosphere and the climate, including parameters such as temperature, moisture, wind velocity and barometric pressure, is known as weather monitoring. Because of the increased usage of the internet, weather monitoring has been upgraded to smart weather monitoring. The Internet of Things (IoT) is one of the new technology that can help with many precision farming operations. Smart weather monitoring is one of the precision agriculture technologies that use sensors to monitor correct weather. The main objective of the research is to design a smart weather monitoring and real-time alert system to overcome the issue of monitoring weather conditions in agricultural farms in order for farmers to make better decisions. Methods: Different sensors were used in this study to detect temperature and humidity, pressure, rain, light intensity, CO2 level, wind speed and direction in an agricultural farm and real time clock sensor was used to measured real time weather data. The major component of this system was an Arduino Uno microcontroller and the system ran according to a program written in the Arduino Uno software. Result: This is a low-cost smart weather monitoring system. This system’s output unit were a liquid crystal display and a GSM900A module. The weather data was displayed on a liquid crystal display and the GSM900A module was used to send the data to a mobile phone. This smart weather station was used to monitor real-time weather conditions while sending weather information to the farmer’s mobile phone, allowing him to make better decisions to increase yield.


2018 ◽  
pp. 188-198 ◽  
Author(s):  
Uma Arun ◽  
Natarajan Sriraam

Today's healthcare technology provides promising solutions to cater to the needs of patients. The development of wearable physiological monitoring system has reached home-centric patients by ensuring faster healthcare services. The primary advantage of this system is activation of alarms to alert the specialist in a nearby hospital to attend to any sort of emergency. Specifically, cardiac-related problems need special attention when a 24-hour Holter monitors ECG signals and identifies the level of abnormalities under various circumstances. Although several brands of Holters exist in market, there is a huge demand for digitized Holter recorders. These recorders can simultaneously analyse cardiac signals in real time mode and store the data and reuse them for next 24 hours. As home-centric based wearable cardiac monitoring system gains much attention recently, there is a need to design and develop a cardiac monitoring system by establishing a trade-off between the required clinical diagnostic quality and cost. This research study highlights a comprehensive survey of various cardiac monitoring systems under wire, wireless and wearable modes. This provides an insight into the need of the hour in bringing a cost-effective wearable system. The study provides an insight of the technological aspects of the existing cardiac monitoring system and suggests a viable design suitable for developing countries.


Biosensors ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 29 ◽  
Author(s):  
Tam Nguyen ◽  
Jonathan Young ◽  
Amanda Rodriguez ◽  
Steven Zupancic ◽  
Donald Lie

Balance disorders present a significant healthcare burden due to the potential for hospitalization or complications for the patient, especially among the elderly population when considering intangible losses such as quality of life, morbidities, and mortalities. This work is a continuation of our earlier works where we now examine feature extraction methodology on Dynamic Gait Index (DGI) tests and machine learning classifiers to differentiate patients with balance problems versus normal subjects on an expanded cohort of 60 patients. All data was obtained using our custom designed low-cost wireless gait analysis sensor (WGAS) containing a basic inertial measurement unit (IMU) worn by each subject during the DGI tests. The raw gait data is wirelessly transmitted from the WGAS for real-time gait data collection and analysis. Here we demonstrate predictive classifiers that achieve high accuracy, sensitivity, and specificity in distinguishing abnormal from normal gaits. These results show that gait data collected from our very low-cost wearable wireless gait sensor can effectively differentiate patients with balance disorders from normal subjects in real-time using various classifiers. Our ultimate goal is to be able to use a remote sensor such as the WGAS to accurately stratify an individual’s risk for falls.


2013 ◽  
Vol 313-314 ◽  
pp. 1180-1183
Author(s):  
Qi Zhi Fang ◽  
Yong Zhe Ge ◽  
Hong Yu Xu

The elevator monitoring system of elevator is an integrated elevator management platform that can realize fault for alarm, rescuing trapped persons, daily management, quality evaluation and preventing hidden trouble by using C8051f060 MCU as the control core to sensor and collect the elevator operation data, with built-in TCP/IP transport protocol and with HuaWei GTM900C GPRS module to realize all kinds of data monitoring of the elevator, and the transmitting of the data to processing server through the network . This paper mainly introduces the formation of wireless monitoring network system and communication protocol construction, and especially analyzes the function and the system architecture of the wireless communication terminal in real-time monitoring. GPRS can not only satisfy the requirement of real-time elevator monitoring system, with low cost and high reliability but can also effectively avoid a variety of problems that are caused by transmitting the alarm data through cables . This system provides many valuable experiences for the development of unattended system, and it has a broad development prospects.


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