Sensing and Monitoring of Epileptical Seizure Under IoT Platform

2020 ◽  
pp. 201-223
Author(s):  
Akash Kumar Gupta ◽  
Chinmay Chakraborty ◽  
Bharat Gupta
Keyword(s):  
Health Service ◽  
Real Time ◽  
Neurological Disorder ◽  
Low Cost ◽  
Wearable Devices ◽  
Real Time Monitoring ◽  
Digital World ◽  
Eeg Data ◽  
Electroencephalogram Eeg ◽  
Health Field

Epilepsy is a disorder that affects the life of the patient. In this neurological disorder, patients may suffer from different types of seizures. From epileptic patients, we may acquire electroencephalogram (EEG) data using various kinds of sensors and transmit them through the cloud. In this chapter, the authors have discussed various platforms related to IoT-enabled cloud for sharing the information and to get quick response in form suggestion. Use of smartphone applications for real-time monitoring of patients and for other applications is presented here. Various wearable devices may provide huge benefits for taking care of seizures and patients. The authors proposed a system model based on IoT-enabled cloud for sharing the information with various sensors and other devices to make a proper judgment about seizures, which will be able to provide improved e-health service. With the increasing rate of improvement in both IoT and e-health field, it is now a challenge to upgrade ourselves and work with the digital world to provide low cost, accurate, and quick solutions.

scholarly journals Non-intrusive vital sign monitoring using an intelligent pillow based on a piezoelectric ceramic sensor

2020 ◽  
Vol 15 ◽  
pp. 155892502097726
Author(s):  
Wei Wang ◽  
Zhiqiang Pang ◽  
Ling Peng ◽  
Fei Hu
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Piezoelectric Ceramic ◽  
Low Cost ◽  
Body Movement ◽  
Vital Signs ◽  
High Heart Rate ◽  
Detection Accuracy ◽  
Processing Unit ◽  
Real Time Monitoring

Performing real-time monitoring for human vital signs during sleep at home is of vital importance to achieve timely detection and rescue. However, the existing smart equipment for monitoring human vital signs suffers the drawbacks of high complexity, high cost, and intrusiveness, or low accuracy. Thus, it is of great need to develop a simplified, nonintrusive, comfortable and low cost real-time monitoring system during sleep. In this study, a novel intelligent pillow was developed based on a low-cost piezoelectric ceramic sensor. It was manufactured by locating a smart system (consisting of a sensing unit i.e. a piezoelectric ceramic sensor, a data processing unit and a GPRS communication module) in the cavity of the pillow made of shape memory foam. The sampling frequency of the intelligent pillow was set at 1000 Hz to capture the signals more accurately, and vital signs including heart rate, respiratory rate and body movement were derived through series of well established algorithms, which were sent to the user’s app. Validation experimental results demonstrate that high heart-rate detection accuracy (i.e. 99.18%) was achieved in using the intelligent pillow. Besides, human tests were conducted by detecting vital signs of six elder participants at their home, and results showed that the detected vital signs may well predicate their health conditions. In addition, no contact discomfort was reported by the participants. With further studies in terms of validity of the intelligent pillow and large-scale human trials, the proposed intelligent pillow was expected to play an important role in daily sleep monitoring.

scholarly journals Simple and Low-Cost On-Package Sticker Sensor based on Litmus Paper for Real-Time Monitoring of Beef Freshness

2015 ◽  
Vol 47 (3) ◽  
pp. 236-251 ◽  
Author(s):  
Bambang Kuswandi ◽  
Fitria Damayanti ◽  
Jayus Jayus ◽  
Aminah Abdullah ◽  
Lee Yook Heng
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Real Time Monitoring ◽  
Litmus Paper

scholarly journals Prediction of Individual User’s Dynamic Ranges of EEG Features from Resting-State EEG Data for Evaluating Their Suitability for Passive Brain–Computer Interface Applications

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 988
Author(s):  
Ho-Seung Cha ◽  
Chang-Hee Han ◽  
Chang-Hwan Im
Keyword(s):  
Resting State ◽  
Brain Computer Interface ◽  
Low Cost ◽  
Mental States ◽  
Computer Interface ◽  
Practical Applications ◽  
Eeg Data ◽  
Brain States ◽  
Electroencephalogram Eeg ◽  
Eeg Features

With the recent development of low-cost wearable electroencephalogram (EEG) recording systems, passive brain–computer interface (pBCI) applications are being actively studied for a variety of application areas, such as education, entertainment, and healthcare. Various EEG features have been employed for the implementation of pBCI applications; however, it is frequently reported that some individuals have difficulty fully enjoying the pBCI applications because the dynamic ranges of their EEG features (i.e., its amplitude variability over time) were too small to be used in the practical applications. Conducting preliminary experiments to search for the individualized EEG features associated with different mental states can partly circumvent this issue; however, these time-consuming experiments were not necessary for the majority of users whose dynamic ranges of EEG features are large enough to be used for pBCI applications. In this study, we tried to predict an individual user’s dynamic ranges of the EEG features that are most widely employed for pBCI applications from resting-state EEG (RS-EEG), with the ultimate goal of identifying individuals who might need additional calibration to become suitable for the pBCI applications. We employed a machine learning-based regression model to predict the dynamic ranges of three widely used EEG features known to be associated with the brain states of valence, relaxation, and concentration. Our results showed that the dynamic ranges of EEG features could be predicted with normalized root mean squared errors of 0.2323, 0.1820, and 0.1562, respectively, demonstrating the possibility of predicting the dynamic ranges of the EEG features for pBCI applications using short resting EEG data.

scholarly journals Monitoring and sensing COVID-19 symptoms as a precaution using electronic wearable devices

2020 ◽  
Vol 16 (4) ◽  
pp. 341-350 ◽  
Author(s):  
Josephine M.S. ◽  
Lakshmanan L. ◽  
Resmi R. Nair ◽  
Visu P. ◽  
Ganesan R. ◽  
...  
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Mobile Apps ◽  
Low Cost ◽  
Wearable Devices ◽  
Point Of View ◽  
Diverse Range ◽  
Content Type ◽  
The Status ◽  
Medium Risk

Purpose The purpose fo this paper is to Monitor and sense the sysmptoms of COVID-19 as a preliminary measure using electronic wearable devices. This variability is sensed by electrocardiograms observed from a multi-parameter monitor and electronic wearable. This field of interest has evolved into a wide area of investigation with today’s advancement in technology of internet of things for immediate sensing and processing information about profound pain. A window span is estimated and reports of profound pain data are used for monitoring heart rate variability (HRV). A median heart rate is considered for comparisons with a diverse range of variable information obtained from sensors and monitors. Observations from healthy patients are introduced to identify how root mean square of difference between inter beat intervals, standard deviation of inter-beat intervals and mean heart rate value are normalized in HRV analysis. Design/methodology/approach The function of a human heart relates back to the autonomic nervous system, which organizes and maintains a healthy maneuver of inter connected organs. HRV has to be determined for analyzing and reporting the status of health, fitness, readiness and possibilities for recovery, and thus, a metric for deeming the presence of COVID-19. Identifying the variations in heart rate, monitoring and assessing profound pain levels are potential lives saving measures in medical industries. Findings Experiments are proposed to be done in electrical and thermal point of view and this composition will deliver profound pain levels ranging from 0 to 10. Real time detection of pain levels will assist the care takers to facilitate people in an aging population for a painless lifestyle. Originality/value The presented research has documented the stages of COVID-19, symptoms and a mechanism to monitor the progress of the disease through better parameters. Risk factors of the disease are carefully analyzed, compared with test results, and thus, concluded that considering the HRV can study better in the presence of ignorance and negligence. The same mechanism can be implemented along with a global positioning system (GPS) system to track the movement of patients during isolation periods. Despite the stringent control measurements for locking down all industries, the rate of affected people is still on the rise. To counter this, people have to be educated about the deadly effects of COVID-19 and foolproof systems should be in place to control the transmission from affected people to new people. Medications to suppress temperatures, will not be sufficient to alter the heart rate variations, and thus, the proposed mechanism implemented the same. The proposed study can be extended to be associated with Government mobile apps for regular and a consortium of single tracking. Measures can be taken to distribute the low-cost proposal to people for real time tracking and regular updates about high and medium risk patients.

scholarly journals Real Time Monitoring of Children, and Adults with Mental Disabilities Using a Low-Cost Non-Invasive Electronic Device

Micromachines ◽  
2017 ◽  
Vol 8 (10) ◽  
pp. 292
Author(s):  
Carlos Polanco ◽  
Ignacio Vazquez ◽  
Adrian Martinez-Rivas ◽  
Miguel Arias-Estrada ◽  
Thomas Buhse ◽  
...  
Keyword(s):  
Real Time ◽  
Electronic Device ◽  
Low Cost ◽  
Mental Disabilities ◽  
Real Time Monitoring ◽  
Non Invasive

scholarly journals Near real-time monitoring of flow velocity and direction in the floating ice tongue of the Shirase Glacier using low-cost GPS buoys

2013 ◽  
Vol 65 (2) ◽  
pp. 103-108 ◽  
Author(s):  
Yuichi Aoyama ◽  
Koichiro Doi ◽  
Kazuo Shibuya ◽  
Harumi Ohta ◽  
Iuko Tsuwa
Keyword(s):  
Flow Velocity ◽  
Real Time ◽  
Low Cost ◽  
Real Time Monitoring

scholarly journals Real time monitoring of alcoholic fermentation with low-cost amperometric biosensors

2011 ◽  
Vol 127 (2) ◽  
pp. 749-754 ◽  
Author(s):  
S. Piermarini ◽  
G. Volpe ◽  
M. Esti ◽  
M. Simonetti ◽  
G. Palleschi
Keyword(s):  
Real Time ◽  
Alcoholic Fermentation ◽  
Low Cost ◽  
Real Time Monitoring ◽  
Amperometric Biosensors

scholarly journals ZigBee-Based Telemetry System

2010 ◽  
Vol 7 (2) ◽  
pp. 32 ◽  
Author(s):  
L. Khriji ◽  
F. Touati ◽  
N. Hamza
Keyword(s):  
Real Time ◽  
Mobile Device ◽  
Low Cost ◽  
Base Station ◽  
The Body ◽  
Telemetry System ◽  
Real Time Monitoring ◽  
Digital Convergence ◽  
Machine Interface

 Nowadays, there is a significant improvement in technology regarding healthcare. Real-time monitoring systems improve the quality of life of patients as well as the performance of hospitals and healthcare centers. In this paper, we present an implementation of a designed framework of a telemetry system using ZigBee technology for automatic and real-time monitoring of Biomedical signals. These signals are collected and processed using 2-tiered subsystems. The first subsystem is the mobile device which is carried on the body and runs a number of biosensors. The second subsystem performs further processing by a local base station using the raw data which is transmitted on-request by the mobile device. The processed data as well as its analysis are then continuously monitored and diagnosed through a human-machine interface. The system should possess low power consumption, low cost and advanced configuration possibilities. This paper accelerates the digital convergence age through continual research and development of technologies related to healthcare. 

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