In order to obtain comprehensive brain activity information conveniently in real time, this study designs a portable EEG and blood oxygen synchronous acquisition system for real-time monitoring of brain functional activities. The EEG electrodes filter and amplify the detected EEG signals, and send them to the microprocessor via Bluetooth to analyze the EEG data; the photoelectric probe converts the optical signals into electrical signals, which are amplified and separated, filtered, and AD converted, calculates the brain's oxygenation and blood-red protein (ΔHbO
Brain ; Electrodes ; Electroencephalography ; Oxygen

In this study, a surface electromyography (sEMG) and blood oxygen signal real-time monitoring system is designed to explore the changes of physiological signals during muscle fatigue, so as to detect muscle fatigue. The analysis method of sEMG and the principle of blood oxygen detection are respectively introduced, and the system scheme is expounded. The hardware part of the system takes STM32 as the core. Conditioning module composition; blood oxygen signal acquisition is based on near infrared spectroscopy (NIRS), specifically including light source, light source driving, photoelectric conversion, signal conditioning and other modules. The system software part is based on the real-time uC/OS-III software system. The characteristic parameters of sEMG were extracted by isometric contraction local muscle fatigue experiment; the relative changes of oxyhemoglobin (HbO₂) and deoxyhemoglobin (Hb) were calculated in the forearm blocking experiment, thereby verifying that the system collects two signals effectiveness.
Muscle, Skeletal ; Oxygen ; Electromyography ; Muscle Fatigue/physiology* ; Computers

Cervical cancer is a common female malignant tumor. It has been increasing and rejuvenating in recent years. Early screening of cervical cancer is an effective control method to block cancer. In this study, a diffuse reflectance spectrum detection and analysis system based on LabWindows development software and MariaDB database was developed, which can acquire and save the spectral data to the database. The method of a neural network model based on spectral database was built to distinguish the cervical tissue and the normal tissue. The nude mouse tumor model test and human volunteer test were performed respectively, which verified that the system can distinguish between normal tissue and tumor tissue, and can be applied to the screening of cervical precancerous lesions.
Animals ; Female ; Humans ; Mice ; Mice, Nude ; Neural Networks (Computer) ; Spectrum Analysis ; Uterine Cervical Neoplasms ; diagnostic imaging