Respiratory Function Monitor Based on Surface Diaphragm Electromyography

To design a respiratory function monitoring system with surface diaphragm electromyography that can be used to monitor respiratory function in the home or with medical agents. Based on the STM32F411VET6 microcontroller system, two electrodes were used to detect the surface EMG signals. Additional two circular disposable Ag/AgCl electrodes were applied for the output of high-frequency excitation and the input of ECG and bio-impedance signals. The hardware system included a diaphragm EMG detection circuit, ECG detection circuit, bio-impedance detection circuit, constant current source excitation circuit, and microcontroller. The analog signals were digitalized by theA/D mode of theMCU, and the digitalized signals were stored in a secure digitalmemory card through the secure digital input and output protocol. After the system design, the system was validated by acquiring signals from 10 patients with mechanical ventilation due to respiratory dysfunction and 10 healthy adults. Fifteen respiratory function-related parameters were calculated and compared between groups. The signal-to-noise ratio of the signal collected by the system was > 10 dB, the common mode rejection ratio was > 80 dB. Compared with healthy adults, inhalation time, exhalation time, tidal volume, peak-to-peak value of the bio-impedance signal, variation of bio-impedance signal in one second, diaphragmatic EMG low-band power (LF, 20-40 Hz), diaphragmatic EMG high-band power (HF, 150-250 Hz), the ratio between high-band power and low-band power., diaphragmatic electromyography area, diaphragmatic electromyography peak-to-peak, and cardiopulmonary coupling coefficient were significantly lower (P < 0.05), but heart rate was significantly higher in mechanically ventilated patients (P < 0.05). In addition, there were no significant differences in respiratory rate, diaphragmatic electromyography time, and inhalation and exhalation ratio between the two groups. The designed respiratory function monitoring system was demonstrated to be reliable. It can be used for continuously and non-invasively monitoring respiratory function in real time.