ABSTRACT
In order to effectively treat respiratory diseases, a non-invasive positive pressure ventilator system is designed, the overall structure design of the system is proposed, and the hardware construction is completed. The breathing state of the patient is identified by the threshold triggering method of the flow rate of change, and the calculation of the flow rate of change is realized by the least squares method. At the same time, the breathing parameters are calculated in real time according to the flow-time and pressure-time characteristic curves. In addition, CMV, CPAP, BiPAP and PSV ventilation modes are also implemented. Finally, the parameter measurement accuracy and ventilation mode setting tests are carried out. The results show that the calculation of key breathing parameters provided by the system meets the relevant standards, and supports the stable output of 4 ventilation modes at the same time, provides breathing treatment for patients, and meets the basic functional requirements of the ventilator.
Subject(s)
Humans , Ventilators, Mechanical , RespirationABSTRACT
Atrial fibrillation is a common arrhythmia, and its diagnosis is interfered by many factors. In order to achieve applicability in diagnosis and improve the level of automatic analysis of atrial fibrillation to the level of experts, the automatic detection of atrial fibrillation is very important. This study proposes an automatic detection algorithm for atrial fibrillation based on BP neural network (back propagation network) and support vector machine (SVM). The electrocardiogram (ECG) segments in the MIT-BIH atrial fibrillation database are divided into 10, 32, 64, and 128 heartbeats, respectively, and the Lorentz value, Shannon entropy, K-S test value and exponential moving average value are calculated. These four characteristic parameters are used as the input of SVM and BP neural network for classification and testing, and the label given by experts in the MIT-BIH atrial fibrillation database is used as the reference output. Among them, the use of atrial fibrillation in the MIT-BIH database, the first 18 cases of data are used as the training set, and the last 7 cases of data are used as the test set. The results show that the accuracy rate of 92% is obtained in the classification of 10 heartbeats, and the accuracy rate of 98% is obtained in the latter three categories. The sensitivity and specificity are both above 97.7%, which has certain applicability. Further validation and improvement in clinical ECG data will be done in next study.
Subject(s)
Humans , Atrial Fibrillation/diagnosis , Support Vector Machine , Heart Rate , Algorithms , Neural Networks, Computer , ElectrocardiographyABSTRACT
To comprehensively evaluate the human body's respiratory, circular metabolism and other functions, and to diagnose lung disease, an accurate and reliable pulmonary function test (PFT) is developed. The system is divided into two parts:hardware and software. It realizes the collection of respiratory, pulse oxygen, carbon dioxide, oxygen and other signals, and draws flow-volume curve (FV curve), volume-time curve (VT curve), respiratory waveform, pulse wave, carbon dioxide and oxygen waveform in real time on the upper computer of the PFT system, and conducts signal processing and parameter calculation for each signal. The experimental results prove that the system is safe and reliable, it can accurately measure the basic functions of human body, and provide reliable parameters, and has good application prospects.
Subject(s)
Humans , Carbon Dioxide , Respiratory Function Tests , Oxygen , Heart RateABSTRACT
Oxygen therapy is an effective clinical method for the treatment of respiratory disorders, oxygen concentrator as a necessary medical auxiliary equipment in hospitals, its research and development has been a hot spot. The study reviewed the development history of the ventilator, introduced the two preparation technique of the oxygen generator pressure swing absorption (PSA) and vacuum pressure swing adsorption (VPSA), and analyzed the core technology development of the oxygen generator. In addition, the study compared some major brands of oxygen concentrators on the market and prospected the development trend of oxygen concentrators.
Subject(s)
Oxygen , Oxygen Inhalation Therapy , Hospitals , Ventilators, Mechanical , Equipment DesignABSTRACT
Ventricular fibrillation is the most common pathophysiological mechanism leading to cardiac arrest. If cardiac arrest can be rescued in time, the survival rate of patients can be greatly improved. Therefore, rapid and accurate identification of ventricular fibrillation is extremely important. This paper proposes an automatic detection algorithm for ventricular fibrillation based on random forest and BP (back propagation) neural network. Pass the ECG signal through a 6 s moving window, calculate 6 kinds of characteristic parameters according to the time-frequency domain information of the signal, use these 6 kinds of characteristic parameters as the input of the classifier, carry out classification and test, and give the authoritative experts in the database. A total of 44 cases of related data were used to evaluate the method. The results show that using the ten-fold cross-validation method, the accuracy of classification of ventricular fibrillation in the CU database (Creighton University Ventricular Tachyarrhythmia Database) and the AHA database (the American Heart Association Database) has reached 96.38% and 99.45%, which has certain applicability.
ABSTRACT
Fetal ECG monitoring is a routine clinical detection method that can reflect the changes of fetal heart in utero in real time. At present, most of the clinical fetal heart rate detection adopts the ultrasonic Doppler method, which is technically difficult and highly specialized in operation and expensive. This study introduces a fetal ECG detection system based on the maternal abdominal electrode method. The weak fetal ECG changes are sensed through the maternal abdominal electrode, and the mixed ECG signal is obtained through the corresponding amplification and filtering circuit. Finally, the obtained signal is passed through WiFi, transmitted to the host computer. The host computer uses the adaptive filtering algorithm to estimate the fetal ECG signal. The system has strong feasibility, low operation expertise, low cost, and is more convenient.
ABSTRACT
Breathing is of great significance in the monitoring of patients with obstructive sleep apnea hypopnea syndrome, perioperative monitoring and intensive care. In this study, a respiratory monitoring and verification system based on optical capacitance product pulse wave (PPG) is designed, which can synchronously collect human PPG signals. Through algorithm processing, the characteristic parameters of PPG signal are calculated, and the respiratory signal and respiratory frequency can be extracted in real time. In order to verify the accuracy of extracting respiratory signal and respiratory rate by the algorithm, the system adds the nasal airflow respiratory signal acquisition module to synchronously collect the nasal airflow respiratory signal as the standard signal for comparison and verification. Finally, the root mean square error between the respiratory rate extracted by the algorithm from the pulse wave and the standard respiratory rate is only 1.05 times/min.
Subject(s)
Humans , Algorithms , Electrocardiography , Heart Rate , Photoplethysmography , Respiration , Respiratory Rate , Signal Processing, Computer-Assisted , Sleep Apnea, ObstructiveABSTRACT
Body temperature is an important physiological parameter of the human body and is used in medicine to reflect the physiological state and health status of the human body. At present, the commonly used clinical thermometers on the market are mainly divided into contact and non-contact types. Most of them are used for rapid body temperature measurement, and it is not easy to monitor body temperature changes in real time. This article introduces a new wearable wireless body temperature monitoring system based on NTC, which senses through NTC. The temperature changes are amplified and filtered, zeroed, and calibrated, and then the temperature data is uploaded to the mobile phone APP via Bluetooth in real time to achieve real-time accurate measurement of body temperature.
Subject(s)
Humans , Body Temperature , Cell Phone , Monitoring, Physiologic , Temperature , Wearable Electronic Devices , Wireless TechnologyABSTRACT
This study introduces a portable multi-channel EEG signal acquisition system. The system is mainly composed of EEG electrode connector, signal conditioning circuit, EEG acquisition part, main control MCU and power supply part. The low-power EEG acquisition front-end ADS1299 and STM32 are used to form the signal acquisition and data communication part. The collected EEG signal can be transmitted to the PC for real-time display. After relevant tests, the system has small volume, low power consumption, high signal-to-noise ratio, and meets the requirements of portable wearable medical devices.
Subject(s)
Electric Power Supplies , Electrodes , Electroencephalography , Signal Processing, Computer-Assisted , Signal-To-Noise RatioABSTRACT
Body temperature is an essential physiological parameter. Conducting non-contact, fast and accurate measurement of temperature is increasing important under the background of COVID-19. The study introduces an infrared temperature measurement system based on the thermopile infrared temperature sensor ZTP-135SR. Extracting original temperature date of sensor, post-amplification and filter processing have been performed to ensure accuracy of the system. In addition, the temperature data of environmental compensation which obtained by polynomial fitting is added to the system to further improve measurement accuracy.
Subject(s)
Humans , Algorithms , Body Temperature , COVID-19 , Temperature , ThermometersABSTRACT
Ventilator is an indispensable emergency medical equipment in hospitals. The global outbreak of the coronavirus disease 2019 (COVID-19) has highlighted the importance of the ventilator, which has attracted the attention and research on ventilators of all countries in the world. This article reviews the development history of the ventilator, briefly introduces the main air circuit structure and working principle of the ventilator, and then deeply analyzes the key technologies of this device. In addition, it compares some major brands of ventilators from several aspects in the market. Finally, the development trend and perspective of ventilators are presented.
Subject(s)
Humans , COVID-19 , Equipment Design , Home Care Services , Respiration, Artificial , SARS-CoV-2 , Ventilators, MechanicalABSTRACT
The ECG signal is susceptible to interference from the external environment during the acquisition process, affecting the analysis and processing of the ECG signal. After the traditional soft-hard threshold function is processed, there is a defect that the signal quality is not high and the continuity at the threshold is poor. An improved threshold function wavelet denoising is proposed, which has better regulation and continuity, and effectively solves the shortcomings of traditional soft and hard threshold functions. The Matlab simulation is carried out through a large amount of data, and various processing methods are compared. The results show that the improved threshold function can improve the denoising effect and is superior to the traditional soft and hard threshold denoising.
Subject(s)
Algorithms , Computer Simulation , Electrocardiography , Signal Processing, Computer-Assisted , Wavelet AnalysisABSTRACT
Oxygen saturation and respiratory signals are important physiological signals of human body, respiratory monitoring plays an important role in clinical and daily life. A system was established to extract respiratory signals from photoplethysmography in this study. Including the collection of pulse wave signal, the extraction of respiratory signal, and the calculation of respiratory rate and pulse rate transmitted from the slave computer to the host computer in real time.
Subject(s)
Humans , Heart Rate , Monitoring, Physiologic , Photoplethysmography , Respiratory Rate , Signal Processing, Computer-AssistedABSTRACT
In order to solve the problem of wide input range of photocurrent, aiming at the shortage of existing pulse signal acquisition system, an adaptive pulse signal acquisition system based on ADS125H02 is designed, which has high collection accuracy, low noise, anti-interference, wide input range, high integration, etc. The measurement range of the system can reach ±10 V, and the accuracy is 0.009 μV. Experimental tests show that the design of the system can extract weak pulse signals, and has good practicality.
Subject(s)
Heart RateABSTRACT
The bioelectrical impedance measurement is a detection technique that uses the electrical characteristics and changes in human tissues and organs to detect biomedical information related to human physiological and pathological conditions. This article makes a comprehensive introduction from the aspects of impedance cardiography, electrical impedance respiratory monitoring, electrical impedance tomography, electrical impedance gastric dynamics detection technique, contact impedance and so on, as well as comprehensively introduces the progress and application status of bioelectrical impedance measurement methods.
Subject(s)
Humans , Electric Impedance , Monitoring, Physiologic , TomographyABSTRACT
General anesthesia is an essential part of surgery to ensure the safety of patients. Electroencephalogram (EEG) has been widely used in anesthesia depth monitoring for abundant information and the ability of reflecting the brain activity. The paper proposes a method which combines wavelet transform and artificial neural network (ANN) to assess the depth of anesthesia. Discrete wavelet transform was used to decompose the EEG signal, and the approximation coefficients and detail coefficients were used to calculate the 9 characteristic parameters. Kruskal-Wallis statistical test was made to these characteristic parameters, and the test showed that the parameters were statistically significant for the differences of the four levels of anesthesia: awake, light anesthesia, moderate anesthesia and deep anesthesia (
Subject(s)
Humans , Algorithms , Anesthesia, General , Electroencephalography , Neural Networks, Computer , Wavelet AnalysisABSTRACT
This paper designs a bluetooth-based low-power multi-parameter monitoring system. The system is mainly composed of ECG signal acquisition, respiratory signal acquisition, body temperature acquisition, bluetooth 4.0 transmission module and Android mobile phone APP display. The system collects the corresponding physiological signals through various collection parts, and can realize the monitoring of three physiological signals of electrocardiogram, respiration and body temperature. The Android mobile APP can display ECG, respiratory waveform and temperature data in real time. The system is small in size and low in power consumption, and has a good application prospect in portable and wearable medical applications.
Subject(s)
Humans , Body Temperature , Cell Phone , Electrocardiography , Mobile Applications , Monitoring, Physiologic/instrumentation , Respiratory RateABSTRACT
This paper describes how to develop a practical new type of atherosclerosis detection device, which can realize real-time measurement and analysis of human atherosclerosis. According to the mechanism of human atherosclerosis, the design objectives of the system are formulated to determine the construction of the platform. The system calculates the pulse wave velocity by measuring the pulse wave of human fingers and toes, adds four blood pressure measurements to the system design, calculates the ankle-brachial index, and comprehensively measures and analyses the degree of human arteriosclerosis.
Subject(s)
Humans , Ankle , Atherosclerosis , Blood Flow Velocity , Blood Pressure , Brachial Artery , Pulse Wave AnalysisABSTRACT
This study describes the development of a wireless and wearable ECG monitoring system with ultra-low power consumption. The system is mainly composed of a connection part of an ECG electrode sticker, an electrocardiogram collecting part, a data storage part, a Bluetooth main control unit, a charging module, a voltage regulator and a lithium battery. The low-power ECG acquisition chip ADS1292R and the ultra-low-power Bluetooth microcontroller nRF51822 together constitute the ECG signal acquisition and wireless data communication part. The collected ECG signals can be sent to the mobile APP through the Bluetooth function provided by the MCU, and can completly display and analysis to achieve low power system. After testing, the system power consumption is only (3.7 V×2.87 mA)10.619 mW, and if it is optimized, it can further reduce power consumption, therefore, the system design can have good applicability.
Subject(s)
Electric Power Supplies , Electrocardiography , Equipment Design , Monitoring, Physiologic/instrumentation , Signal Processing, Computer-Assisted , Wearable Electronic Devices , Wireless TechnologyABSTRACT
This study designs an intermittent pneumatic pressurization device with STM32 series single chip as the core. The working state of the air pump and the plurality of air chambers is controlled by the IO port of the single chip microcomputer, and the circulating inflation of the plurality of air bags is realized. The pressure monitoring system consists of a silicon piezoresistive pressure sensor, a high-precision operational amplifier and a 12-bit AD converter which monitors the gas pressure of each gas path in real time to ensure the safety of the equipment. The system is easy to operate, simple in function, and has strong practicability.