An inexpensive and ultra-low power sensor node for wireless health monitoring system
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Increasing interests in remote monitoring of vital signs through telecommunication, especially with wireless and mobile communication have enabled a new generation of information system for healthcare applications. The system may include miniature sensor nodes embedded with wireless communications and a mobile computer delivering information to remote locations. In this paper, we introduced an inexpensive and ultra-low power system for measuring ECG and heart rate in contact and contact-less manners. Existing monitoring system uses gel or electrodes for measuring ECG signals. However, in this study, we used unique electric potential EPIC sensors from Plessey's and infrared sensors. The prototype is capable of monitoring both heart rate and ECG signals with a hibernation mode, which would require less power to transmit the data. Our developed prototype can be used to monitor premature infants as their skins are sensitive and current system uses patches or gel to collect biomedical signals. The proposed prototype for monitoring vital signs has been tested in our lab. The results show that it can achieve low power consumption though a hibernation mode.Keywords:
Continuous monitoring
Vital signs
Sensor node
Remote patient monitoring
Hibernation
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.
Vital signs
Remote patient monitoring
eHealth
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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.
Vital signs
Remote patient monitoring
Continuous monitoring
Graphical user interface
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Wireless transmission
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Vital signs
Continuous monitoring
Signs and symptoms
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Remote monitoring of vital signs is an important technique to ensure the health and life quality of a patient. A wearable monitoring system for low-cost and pervasive healthcare is proposed in this paper. The system, which comprises of wireless module, miniaturized electrocardiogram (ECG) sensor and photoplethysmogram (PPG), is able to measure and analyze physiological signs in real-time and with minimum disturbance on daily life. With Bluetooth communications, a phone is able to exchange data with the sensors deployed on body and display the ECG/PPG waveforms as well as the significant physiological variables including heart beat rate, oxygen saturation (SpO 2 ) and systolic blood pressure. The wearability of the system provides great convenience and continuous healthcare service to the user.
Vital signs
Photoplethysmogram
Remote patient monitoring
Continuous monitoring
Heart beat
Wearable Technology
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Many fatal traffic accidents caused by professional drivers are attributed not only to fatigue and stress, but also heart and cardiovascular disease. Heartbeat interval (HBI) is one of the primary vital signs that indicates a sudden change in a person's physical condition. In addition, blood pressure, particularly continuous blood pressure (BP), is highly correlated with cardiovascular disease. However, to our knowledge, there are no studies on monitoring a driver's HBI and continuous BP simultaneously. In this paper, we present a 60 GHz millimeter-wave vital signs sensor to monitor the driver's HBI and continuous BP in a non-contact manner. The driver's HBI and continuous BP were measured while driving and each measured vital sign was evaluated using correlation and Bland-Altman analysis.
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Heart beat
Continuous monitoring
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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.
Remote patient monitoring
NeuRFon
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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.
Vital signs
Remote patient monitoring
Interfacing
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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.
Vital signs
Remote patient monitoring
Patient data
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Sensor technology for monitoring vital signs is an important topic for various service applications, such as entertainment and personalization platforms and Internet of Things (IoT) systems, as well as traditional medical purposes, such as disease indication judgments and predictions. Vital signs for monitoring include respiration and heart rates, body temperature, blood pressure, oxygen saturation, electrocardiogram, blood glucose concentration, brain waves, etc. Gait and walking length can also be regarded as vital signs because they can indirectly indicate human activity and status. Sensing technologies include contact sensors such as electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmogram (PPG), non-contact sensors such as ballistocardiography (BCG), and invasive/non-invasive sensors for diagnoses of variations in blood characteristics or body fluids. Radar, vision, and infrared sensors can also be useful technologies for detecting vital signs from the movement of humans or organs. Signal processing, extraction, and analysis techniques are important in industrial applications along with hardware implementation techniques. Battery management and wireless power transmission technologies, the design and optimization of low-power circuits, and systems for continuous monitoring and data collection/transmission should also be considered with sensor technologies. In addition, machine-learning-based diagnostic technology can be used for extracting meaningful information from continuous monitoring data.
Vital signs
Photoplethysmogram
Continuous monitoring
Remote patient monitoring
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