IOT
Abstract
The increasing growth of Internet of Things (IOT) and its medical applications has enhanced the effectiveness in remote health monitoring systems of elderly patients who need long-term personal care. The focus of this paper is to build an Android platform based mobile application for the healthcare domain, which uses the idea of Internet of Things (IOT) and cloud computing. The logged data can be uploaded to the user’s private centralized cloud or a specific medical cloud, which keeps a record of all the monitored data and can be retrieved for analysis by the medical personnel. In this system, unique identification numbers for each patient will be created which will identify her/him in the health information database. This ID is then linked to all recordings of the patient’s vital data and saved in a database for further analysis and historical consultation. The system will also provide real-time patient monitoring of vital signs during their stay in an emergency and critical care unit in a hospital.
1.Introduction
Healthcare systems are one of the important key to the economy of any country and for the public health. Here, a system is proposed to implement a smart patient management, monitoring and tracking process using IOT that can be used in hospitals to automate and organize their information management. This system will also provide real-time patient monitoring of vital physiological parameters during patient’s stay in an emergency and critical care unit in a hospital. It also alerts hospital staff as soon as any abnormality is detected.
The system will provide a cost-effective means of increasing reliability, privacy and security in the management system of healthcare records. The low cost is a very interesting feature of the system. Recorded measurements of vital physiological parameters of the patients are presented in a compact user-friendly interface that can be monitored remotely by the doctors and medical personnel.
Nowadays, chronic illnesses, such as, stroke, heart disease, diabetes, cancer, chronic respiratory diseases are major causes of death, in many parts of the world. In this article, we propose a unique patient monitoring system for various medical conditions to minimize future recurrence of the same by alarming the doctor and caretaker on variation in risk factors of any prone disease. Data analytics and decision-making, based on the real-time health parameters of the patient, helps the doctor in systematic diagnosis followed by tailored restorative treatment of the disease. The proposed model uses classification algorithms for the best diagnosis and prediction of various physiological parameters of the patient.
The application provides the end user with visualization of their physiological parameters and access to data logging functionality in the background. PMS monitors the physiological parameters and informs the surgeon about the present status of the patient’s condition.
2. Implementation
Patient monitoring system is one of the biggest applications of IOT as media data transmission for measuring physiological parameters of patients in remote areas. We developed monitoring system that can be accessed by several users simultaneously via the internet network. Furthermore, the data can be accessed by the doctors and other medical personnel for the purpose of treatment or consultation. By using this application, patients with heart diseases can interact and consult with a cardiologist anytime and anywhere. Patient monitoring system measure physiological and biological condition either continuously or at regular interval over time.
The working of Patient monitoring system (PMS) includes quantitative evaluation of the crucial parameters of patients during critical periods of biological functions. Patient monitoring system generally monitors the physiological parameters and quickly informs the surgeon about the present status of the patient’s condition [3].With this system, the risk that surgery involves has been considerably reduced since it is possible to detect any complications before they prone dangerous as suitable measures can be taken in time, before the surgery takes place. Patient monitoring systems are one of the most essential diagnostic devices in the critical care units (CCUs) of hospitals, providing continuous display and interpretation of the patient’s physiological parameters.
The main feature of patient monitoring system is continuous observations or measurements of the patients’ physiological parameter and the function of life support equipment, for the purpose of guiding management decisions, including when to make therapeutic intervention of those interventions. Patient monitoring systems are capable of measuring physiological signs such as electrocardiogram (ECG), electromyogram (EMG), heart rate (HR), body temperature, arterial oxygen saturation (SpO2), blood pressure (BP) and respiration rate (RR).
A patient monitoring system not only alerts the doctors and medical staffs about potentially life-threatening events but also provide physiologic input data used to control directly connected life-support devices. In the second step, the patient information centre (PIC) helps the hospital authority in many ways. First, it generates audible alarms when permitted limits are exceeded. The second function of the patient information centre is to timely display all the data received from the PIC. By observing and analyzing these data, the authority can easily detect abnormalities and complications before they reach the critical stage. The central station’s third most important function is to keep record of all the physiological parameters of each and every patient.
3. Challenges faced with IOT
Patient monitoring and management in critical care environments such as intensive care units (ICUs) and operating rooms (ORs) involves a complex procedure involving multiple steps. The process starts with estimating the status of the patient, reacting to events that may be life threatening, and taking actions to bring the patient to a desired state. This complex process includes the interaction of learned physicians and nurses with diverse data ranging from clinical observations to laboratory results to online data which is provided by bedside medical equipment. Newly evolving monitoring devices provide health care professionals with unsurpassed amounts of information and related data to support and enhance the decision making process [2]. Ironically, rather than helping these professionals, the amount of information generated and the way the data is presented may overload their cognitive skills and lead to erroneous conclusions and inadequate actions. New solutions are needed to manage and process the continuous flow of information and provide efficient and reliable decision support tools.
Patient monitoring can be conceptually organized in four layers. The very first layer is comprised of the signal level which acquires and performs low-level processing of raw data. Secondly, the validation level, which removes data artifacts. The next layer includes the signal-to-symbol transform level, which maps detected features to symbols such as normal, low, or high. And lastly, the inference level, which relies on a computer representation of medical knowledge to derive possible diagnoses, explanations of events, predictions about future physiologic states, or to control actions. In addition to these four layers, medical decision support systems need all the related data interfaces to other clinical information systems as well as carefully designed user interfaces to facilitate quick and accurate situation assessment by care providers.
Any system which is developed for specific application are usually successful in their limited domain of expertise. However, the lessons and problem solving strategies learned in one domain are often difficult to generalize. Modern monitoring devices are highly capable of providing derived and computed information of the patient in addition to raw data. Heavily instrumented patients in critical and intensive care units frequently have up to 20 or even more medical devices monitoring them simultaneously producing up to 100 pieces of clinically relevant information based on the physiological and biological condition of the patient.
4. Features of IOT
Intelligent patient monitoring provides a number of systems to address problems faced by clinicians in critical care environments and makes their task simpler. These range from low-level signal analysis for detecting specific features in monitored signals to complete architectures for signal and data acquisition, processing, interpretation, and decision support unit. The instruments used are often stand-alone, and their interconnection requires developing dedicated software in-house, usually with substantial effort. Current bedside monitors typically provide instantaneous values for the monitored variables [1]. To complement this information, numerous algorithms have been proposed to detect features in the signals.
The main features of intelligent patient monitoring system include:
- Better access to healthcare
- Improved quality of care
- Peace of mind and daily assurance
- Improved support, education and feedback
5. Conclusions and Future Work
Patient Monitoring System using IOT strengthens the capabilities of doctors and medical authorities to track every patient’s vital physiological and biological parameters and determine their health condition. Patient monitoring systems are the most important diagnostic systems in the critical care units of any hospital, providing continuous display and interpretation of the patient’s vital health parameters. The patient monitoring requirements include periodic detection of routine vital physiological and biological parameters and transmission of alerting signals when vital parameters indicate any kind of threat or danger. PMS has resulted in more powerful bedside patient monitors capable of complex bio-signal processing and interpretation and it is usually equipped with some specialized communication interface.
References
[1] D. Fotiadis, A. Likas and V. Protopappas, “Intelligent Patient Monitoring”, Semanticscholar.org, 2020. Available: https://www.semanticscholar.org/paper/Intelligent-Patient-Monitoring-Fotiadis-Likas/0b6317ab5c1046bd7024784899a79990c92729f1.[Accessed on 29- Jan- 2020].
[2]”Knowledge-Based Systems for Intelligent Patient Monitoring and Management in Critical Care Environments | Electronics World”, Elektroarsenal.net, 2020. Available: http://elektroarsenal.net/knowledge-based-systems-for-intelligent-patient-monitoring-and-management-in-critical-care-environments.html.[Accessed: 29- Jan- 2020].
[3]”Intelligent patient monitoring and management systems: a review – IEEE Journals & Magazine”, Ieeexplore.ieee.org, 2020. Available: https://ieeexplore.ieee.org/abstract/document/248164/citations#citations.[ Accessed: 29- Jan- 2020].
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