IoT-Based Control System to Measure, Analyze, and Track Basic Vital Indicators in Patient Healthcare Monitoring System
Kamal UpretiPrashant VatsMustafizul HaqueAdheer A. GoyalSachin R. WankhedePrashant SinghMohammad Shabbir AlamMohammad Nasir
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Keywords:
Vital signs
Android application
Arduino
Remote patient monitoring
Patient monitoring has advanced over the years, from bed side monitors in the hospital, to wearable devices that can monitor patients and communicate their data remotely to medical servers over wireless networks. It is a process that involves monitoring major vital signs of a patient, to check if their health is normal or deteriorating within a period of time. In a remote situation, vital signs information, can help health care providers to easily send help to patients when their health is at immediate risk. The problem with this kind of remote monitoring system is that most times the patients must be within a specified location to either monitor their health or receive emergency help. This paper presents a potential solution in the form of a global vital sign monitoring system and consists of two components to demonstrate the functionality; a wearable wireless monitoring device that records the temperature and pulse rate of the patient wearing it and a web application, which allows the patient and the emergency response unit to interact together over cellular network.
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Patient vital signs monitoring is an important activity in medical field, the situation in real medical facility usually does not allow for continuous monitoring. In a medical facility such as hospital or health care center, the patients outnumbered the staffs which makes it difficult to focus on each patient at a time. This problem can decrease chance to efficiently and effectively detecting medical condition. In this paper, we propose a wireless vital signs monitoring system, where multiple patients can be monitored at the same time. The system consists of two parts: Sensor Device to detect and measure patient's vital signs and Monitor Device to present the sensors' measurement result. We use ZigBee protocol for data transmission between devices. We compare our system to previous work to showcase the advantages of our work. We present the performance results related with the ZigBee communication and the display of Graphical User Interface (GUI). The results show that the system is capable of carrying out vital sign monitoring in indoor scenario with interactive measurement display that can help monitor multiple patients simultaneously.
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Vital signs such as heart rate, oxygen saturation, and blood pressure are crucial information for healthcare workers to identify clinical deterioration of ward patients. Currently, medical devices monitor these vital signs and trigger alarms when the vital signs are not in the normal ranges based on predefined thresholds, which suggests the presence of clinical deterioration. However, such threshold-based approach is not robust for patient monitoring. This is because vital signs differ among patients due to human physiology and change across time based on the action performed by a patient. In this work, we want to tackle these problems by building adaptable action-aware vital models. These models can understand the changes in vital signs caused by patient's actions and can be adapted to the normal vital sign ranges of individual patients. Our experimental results show that general vital sign patterns for different actions exist and can be personalized to new patients. Additionally, we investigate the possibility of estimating the initial vital model for an unobserved action using models of observed actions for model personalization. The resulting adaptable action-aware vital models have the potential to improve patient monitoring by reducing false clinical alarms.
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Patient monitoring is the most important routine in hospitals. Patient Monitoring System (PMS) provides continuous presentation and interpretation of the patient's vital signs. However in a hospital wards scenario, standard patient monitoring requires a nurse to manually and periodically record the patient's vital signs. This paper presents the development of an automated PMS for hospital wards that integrates Zigbee Technology and CAN protocol. The system comprises two sections: the wireless section is the wearable device and the coordinator node while the wired section is the coordinator node connected to the base station node thru the CAN bus and a Central Monitoring Station (CMS) based on LabVIEW software. The key components of the wearable device are the GY-MAX30100 and Fever Click MAX30205. These development boards have achieved the acceptable limits in measuring vital signs such as heart rate (HR), oxygen saturation (SpO2) and body temperature in terms of relative error rate (RER) when compared to Pulse Oximeter MD300C1 and Digital Thermometer DT-111A that are both CE marked medical device. The evaluation of the wearable device and the coordinator node in sending and receiving vital signs data have shown a 100% reliability even in a line-of-sight (LOS) and non-line-of-sight (NLOS) condition for a distance of up to 40 meters. The average response time of the CMS in receiving data is 1.3 seconds and has detection for abnormal vital signs. The final simulation tested with four volunteers had successfully revealed an effective and a working system that can work in a multi-patient architecture.
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Electrical-based vital signs monitoring, especially the electrocardiogram (ECG) technique, has been investigated and applied in daily life. But this technique meets the limitations, e.g., the direct skin-contact, body hair shaving, the discomfort and inconvenience of the test subject. Recently, optical-based vital signs monitoring has been demonstrated to be a promising technique for realizing non-invasive monitoring. However, some of them exhibit the disadvantages of high cost and lacking compactness. We propose and demonstrate a non-invasive and continuous ballistocardiogram (BCG) based vital signs monitoring system, using a seven-core fiber interferometer (SCFI) sensor, which provided a more convenient, more compact, and less costly way to measure the vital signs. The results show that the measured HR and RR of the proposed sensor agree well with the commercial physiologic device. We recommend that the proposed sensor is promising for long-term and noninvasive measuring vital signs.
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Information communication technologies can support physicians for more effective and improved quality of diagnoses. A lot of available medical data from body sensors and advanced medical devices have to be preprocessed and analysed with efficient methods. We propose an enhancement of an existing ECG signal, e. g. from a wearable ECG device, with accelerometer data. The feasibility study aims to extract and recognise a patient's pose and activity from accelerometer data that is added to a standard ECG body sensor. The time-aligned ECG and accelerometer data are fused in order to add valuable information for the interpretation program. The proposed accelerometer data processing method provides information about patient activity, besides the ECG data. A physician or an interpretation program have further insight into whether the change in heart rate is caused by the irregular heartbeats or by the patient's movement activity. We have validated the proposed methodology on real measurements with ECG and accelerometer data.
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Vital signs monitoring technology is an important part of modern healthcare. With the continuous advancement of medical technology, the existing vital signs monitoring technology can no longer meet people's needs. Through the analysis of different application scenarios, it can be seen that the new vital signs monitoring technology presents a trend of non-sensory monitoring, long-term monitoring, bed monitoring, and early diagnosis. Remote vital signs monitoring using millimeter wave radar has the advantages of non-contact, continuous and high degree of freedom, and can be used to monitor the vital signs of special patients. However, the signal received by mm-wave radar are very sensitive to random body movements, which reduces the accuracy of heart rate and respiratory rate. To overcome this challenge, we propose a method based on chest mechanical motion modeling to remove random body movements.
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Nowadays, chronic heart failure (CHF) affects an ever-growing segment of population, and it is among the major causes of hospitalization for elderly citizens. The actual out-of-hospital treatment model, based on periodic visits, has a low capability to detect signs of destabilization and leads to a high re-hospitalization rate. To this aim, in this paper, a complete and integrated Information and Communication Technology system is described enabling the CHF patients to daily collect vital signs at home and automatically send them to the Hospital Information System, allowing the physicians to monitor their patients at distance and take timely actions in case of necessity. A minimum set of vital parameters has been identified, consisting of electrocardiogram, SpO2, blood pressure, and weight, measured through a pool of wireless, non-invasive biomedical sensors. A multi-channel front-end IC for cardiac sensor interfacing has been also developed. Sensor data acquisition and signal processing are in charge of an additional device, the home gateway. All signals are processed upon acquisition in order to assert if both punctual values and extracted trends lay in a safety zone established by thresholds. Per-patient personalized thresholds, required measurements and transmission policy are allowed. As proved by first medical tests, the proposed telemedicine platform represents a valid support to early detect the alterations in vital signs that precede the acute syndromes, allowing early home interventions thus reducing the number of subsequent hospitalizations.
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In this paper a conceptual method to diagnose and remotely monitor vital cardiac signs in patients is proposed. The proposed methodology utilizes technology with digital probing diagnostic tools and current wireless systems to monitor the health conditions of patients without direct physical intervention of physicians. The data could also be used to generate a medical history based assessment and risk algorithms.
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Traditionally, home care for chronically ill patients and the elderly requires periodic visits to the patient's home by doctors or healthcare personnel. During these visits, the visiting person usually records the patient's vital signs and takes decisions as to any change in treatment and address any issues that the patient may have. Patient monitoring systems have since changed this scenario by significantly reducing the number of home visits while not compromising on continuous monitoring. This paper describes the design and development of a patient monitoring systems capable of concurrent remote monitoring of 8 patient-worn sensors: Electroencephalogram (EEG), Electrocardiogram (ECG), temperature, airflow pressure, movement and chest expansion. These sensors provide vital signs useful for monitoring the health of chronically ill patients and alerts can be raised if certain specified signal levels fall above or below a preset threshold value. The data from all eight sensors are digitally transmitted to a PC or to a standalone network appliance which relays the data through an available internet connection to the remote monitoring client. Thus it provides a real-time rendering of the patient's health at a remote location.
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