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1.
Chinese Journal of Medical Instrumentation ; (6): 294-297, 2023.
Article in Chinese | WPRIM | ID: wpr-982231

ABSTRACT

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 Design
2.
Chinese Journal of Medical Instrumentation ; (6): 404-407, 2022.
Article in Chinese | WPRIM | ID: wpr-939756

ABSTRACT

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 Ratio
3.
Chinese Journal of Medical Instrumentation ; (6): 368-372, 2022.
Article in Chinese | WPRIM | ID: wpr-939749

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, Obstructive
4.
Chinese Journal of Medical Instrumentation ; (6): 160-163, 2022.
Article in Chinese | WPRIM | ID: wpr-928879

ABSTRACT

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 , Thermometers
5.
Journal of Biomedical Engineering ; (6): 838-847, 2021.
Article in Chinese | WPRIM | ID: wpr-921821

ABSTRACT

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 Analysis
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