Using a real-time operating system for multitasking in Remote Patient Monitoring

2014 ◽  
Author(s):  
Michael Rockwood ◽  
Vilas Joshi ◽  
Kevin Sullivan ◽  
Rafik Goubran
Keyword(s):  
Operating System ◽  
Real Time ◽  
Patient Monitoring ◽  
Remote Patient Monitoring ◽  
Real Time Operating System ◽  
Remote Patient

Remote Patient Monitoring for Healthcare

2019 ◽  
pp. 163-179 ◽  
Author(s):  
Andrew Stranieri ◽  
Venki Balasubramanian
Keyword(s):  
Real Time ◽  
Data Analytics ◽  
Patient Monitoring ◽  
Wearable Sensors ◽  
Data Sets ◽  
Remote Patient Monitoring ◽  
Data Mining Algorithms ◽  
Real Time Analysis ◽  
Huge Data ◽  
Remote Patient

Remote patient monitoring involves the collection of data from wearable sensors that typically requires analysis in real time. The real-time analysis of data streaming continuously to a server challenges data mining algorithms that have mostly been developed for static data residing in central repositories. Remote patient monitoring also generates huge data sets that present storage and management problems. Although virtual records of every health event throughout an individual's lifespan known as the electronic health record are rapidly emerging, few electronic records accommodate data from continuous remote patient monitoring. These factors combine to make data analytics with continuous patient data very challenging. In this chapter, benefits for data analytics inherent in the use of standards for clinical concepts for remote patient monitoring is presented. The openEHR standard that describes the way in which concepts are used in clinical practice is well suited to be adopted as the standard required to record meta-data about remote monitoring. The claim is advanced that this is likely to facilitate meaningful real time analyses with big remote patient monitoring data. The point is made by drawing on a case study involving the transmission of patient vital sign data collected from wearable sensors in an Indian hospital.

Development of Wireless Transducer for Real-Time Remote Patient Monitoring

2016 ◽  
Vol 16 (12) ◽  
pp. 4669-4670 ◽  
Author(s):  
Yang Yang ◽  
Xi Zhu ◽  
Ke Ma ◽  
Roy B. V. B. Simorangkir ◽  
Nemai Chandra Karmakar ◽  
...  
Keyword(s):  
Real Time ◽  
Patient Monitoring ◽  
Remote Patient Monitoring ◽  
Remote Patient

scholarly journals REAL TIME HEALTH MONITORING SYSTEM OF REMOTE PATIENT USING ARM7

2012 ◽  
pp. 18-21
Author(s):  
RUBINA.A. SHAIKH
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Patient Monitoring ◽  
Critically Ill Patient ◽  
Applied Statistics ◽  
Remote Patient Monitoring ◽  
Health Monitoring System ◽  
Heart Attacks ◽  
Patient Monitoring System ◽  
Remote Patient

Care of critically ill patient, requires spontaneous & accurate decisions so that life-protecting & lifesaving therapy can be properly applied. Statistics reveal that every minute a human is losing his/her life across the globe. More close in India, everyday many lives are affected by heart attacks and more importantly because the patients did not get timely and proper help .This paper is based on monitoring of remote patients, after he is discharged from hospital. I have designed and developed a reliable, energy efficient remote patient monitoring system. It is able to send parameters of patient in real time. It enables the doctors to monitor patient’s parameters (temp, heartbeat, ECG) in real time. Here the parameters of patient are measured continuously (temp, heartbeat, ECG) and wirelessly transmitted using Zigbee.

An Intelligent Multi-Objective Framework of Pervasive Information Computing

2020 ◽  
pp. 456-469
Author(s):  
Basant Tiwari ◽  
Vivek Tiwari
Keyword(s):  
Real Time ◽  
Patient Monitoring ◽  
Healthcare Quality ◽  
Wearable Devices ◽  
Data Driven ◽  
Remote Patient Monitoring ◽  
Network Efficiency ◽  
Monitoring Technology ◽  
Elderly Individuals ◽  
Remote Patient

This article describes how electronic healthcare has been the key application of pervasive computing innovations to enhance healthcare quality and protect human lives. Specific patients of constant sicknesses and elderly individuals, by and large, may oblige continuous observing of their wellbeing status wherever they are. In this regard, remote patient monitoring technology plays the various important role through wearable devices to monitor patient's physiological figures. But, this must ensure some broad issues like, wearability, adaptability, interoperability, integration, security, and network efficiency. This article proposes a data-driven multi-layer architecture for pervasively remote patient monitoring that incorporates aforesaid issues. It enables the patient's care at the real time and supports anywhere and anytime requirement with using network infrastructure efficiently.

Remote Patient Monitoring for Healthcare

2022 ◽  
pp. 1054-1070
Author(s):  
Andrew Stranieri ◽  
Venki Balasubramanian
Keyword(s):  
Real Time ◽  
Data Analytics ◽  
Patient Monitoring ◽  
Wearable Sensors ◽  
Data Sets ◽  
Remote Patient Monitoring ◽  
Data Mining Algorithms ◽  
Real Time Analysis ◽  
Huge Data ◽  
Remote Patient

Remote patient monitoring involves the collection of data from wearable sensors that typically requires analysis in real time. The real-time analysis of data streaming continuously to a server challenges data mining algorithms that have mostly been developed for static data residing in central repositories. Remote patient monitoring also generates huge data sets that present storage and management problems. Although virtual records of every health event throughout an individual's lifespan known as the electronic health record are rapidly emerging, few electronic records accommodate data from continuous remote patient monitoring. These factors combine to make data analytics with continuous patient data very challenging. In this chapter, benefits for data analytics inherent in the use of standards for clinical concepts for remote patient monitoring is presented. The openEHR standard that describes the way in which concepts are used in clinical practice is well suited to be adopted as the standard required to record meta-data about remote monitoring. The claim is advanced that this is likely to facilitate meaningful real time analyses with big remote patient monitoring data. The point is made by drawing on a case study involving the transmission of patient vital sign data collected from wearable sensors in an Indian hospital.

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