In the past 20 years,near infrared spectrum technology has been widely used in human body monitoring due to its non-invasive and real-time characteristics.Oxygen,as the main metabolic substance of the human body,is consumed the most in brain tissue.In order to prevent complications caused by a decrease in brain tissue oxygen during treatment,the patient's brain tissue blood oxygen saturation needs to be monitored in real time.Currently,most of the clinically used non-invasive cerebral blood oxygen detection equipments use dual wavelengths.Other substances on the detection path will cause errors in the measurement results.Therefore,this article proposes a three-wavelength method based on the basic principle of non-invasive monitoring of cerebral blood oxygen using near-infrared spectrum.The brain tissue oxygen saturation monitoring method of detecting light sources was initially verified through the built system,laying the foundation for subsequent system engineering.

A wireless wearable sleep monitoring system based on EEG signals is developed.The collected EEG signals are wirelessly sent to the PC or mobile phone Bluetooth APP for real-time display.The system is small in size,low in power consumption,and light in weight.It can be worn on the patient's forehead and is comfortable.It can be applied to home sleep monitoring scenarios and has good application value.The key performance indicators of the system are compared with the industry-related medical device measurement standards,and the measurement results are better than the special standards.

The concentration of end-tidal carbon dioxide is one of the important indicators for evaluating whether the human respiratory system is normal.Accurately detecting of end-tidal carbon dioxide is of great significance in clinical practice.With the continuous promotion of the localization of end-tidal carbon dioxide monitoring technology,its application in clinical practice in China has become increasingly widespread in recent years.The study is based on the non-dispersive infrared method and comprehensively elaborates on the detection principle,gas sampling methods,key technologies,and technological progress of end-tidal carbon dioxide detection technology.It comprehensively introduces the current development status of this technology and provides reference for application promotion and further improvement.

Pulse rate and blood oxygen levels are crucial physiological parameters that reflect physiological and pathological information within the human body.The system designs a wireless pulse wave monitoring system utilizing a flexible reflective probe and the AFE4490,which is capable of monitoring pulse wave and blood oxygen levels on the human forehead.The system is predominantly based on a reflective flexible probe,the AFE4490,a power supply module,a control microcontroller unit(MCU),and a Wi-Fi module.Post-processing by a slave computer,the collected pulse wave data is wirelessly transmitted to a smartphone.The real-time pulse waveform,pulse rate,and blood oxygen levels are displayed on an application.Following relevant tests and verifications,the system can accurately detect pulse wave signals,meet the requirements for wearable technology,and possesses significant market application potential.

Sleep disordered breathing(SDB)is a common sleep disorder with an increasing prevalence.The current gold standard for diagnosing SDB is polysomnography(PSG),but existing PSG techniques have some limitations,such as long manual interpretation times,a lack of data quality control,and insufficient monitoring of gas metabolism and hemodynamics.Therefore,there is an urgent need in China's sleep clinical applications to develop a new intelligent PSG system with data quality control,gas metabolism assessment,and hemodynamic monitoring capabilities.The new system,in terms of hardware,detects traditional parameters like nasal airflow,blood oxygen levels,electrocardiography(ECG),electroencephalography(EEG),electromyography(EMG),electrooculogram(EOG),and includes additional modules for gas metabolism assessment via end-tidal CO2 and O2 concentration,and hemodynamic function assessment through impedance cardiography.On the software side,deep learning methods are being employed to develop intelligent data quality control and diagnostic techniques.The goal is to provide detailed sleep quality assessments that effectively assist doctors in evaluating the sleep quality of SDB patients.

ECG signals and sleep monitoring parameters complement each other and can be used for qualitative diagnosis of sleep apnea syndrome and cardio-related diseases.However,due to the limitations of the instrument volume and the detection environment,it is often challenging to integrate these two functions in practical applications.In this paper,a 12-lead dynamic electrocardiograph integrated with sleep monitoring is designed.The system's volume is reduced by combining the integrated ECG simulation front end with a miniature sensor.The system achieves the extraction,conditioning,and calculation of 12-lead ECG signals and sleep-related parameters and writes the data to a memory card in real time,which offers convenience for users and doctors in the diagnostic process.

Cardiopulmonary exercise testing(CPET)refers to a method of measuring various indicators of the human body under gradually increasing exercise loads to objectively evaluate cardiopulmonary reserve function and exercise endurance.Currently,CPET detection systems primarily measure subjects'ECG,respiratory flow,oxygen(O2),and carbon dioxide(CO2)parameters.This paper introduces a non-invasive multi-parameter exercise cardiopulmonary function evaluation system that incorporates impedance cardiography monitoring.The system integrates impedance cardiography monitoring with conventional CPET detection parameters and detects changes in the hemodynamic parameters of the body during exercise,aiding in the evaluation of exercise capacity.Additionally,the system features a portable design with Wi-Fi wireless transmission,which enhances its applicability.

To address the issue of the difficulty in implementing non-invasive continuous blood pressure measurement technology in China,this study developed a high-performance synchronous electrocardiogram(ECG)and photoplethysmography(PPG)signal acquisition system.A PC-based human-computer interaction software platform was constructed,and continuous blood pressure measurement-related algorithms were integrated.Multiple feature parameters such as pulse wave transit time based on synchronous ECG and PPG signals were extracted,enabling non-invasive continuous blood pressure measurement.To verify the measurement accuracy of the system,tests and comparative verifications were carried out.The results demonstrated that the system could meet the requirements of relevant standards and have good application value.

A cerebral oximeter based on 3-wavelength spatially resolved spectroscopy and the modified Lambert-Beer law is proposed.A platform for monitoring the regional cerebral oxygen saturation(rSO2)is established,and the system reliability is verified through spectral stability and background noise test.Eighteen volunteers are recruited to participate in the controlled hypoxia test for exploring the trend of rSO2 with the sequence of stepped hypoxia platform and discussing the relationship between rSO2 and arterial blood oxygen saturation.The results show that the established system can effectively monitor rSO2 and meet the measurement requirements.During the controlled hypoxia sequence,as the fraction of inspired oxygen decreases,rSO2 shows a downward trend,and the individual rSO2 has a high correlation with arterial blood oxygen saturation.

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.
Humans ; Ventilators, Mechanical ; Respiration