Using the Lomb periodogram for non-contact estimation of respiration rates

Real-time Respiration Measurement during Sleep Using a Microwave Sensor

Non-contact continuous respiratory monitoring during sleep is of high usability to early disease detection and daily health monitoring. This study introduces a novel microwave sensor prototype for real-time respiration measurement. The antennas of the sensor are placed below the bed sheet, and function by transmitting a series of microwave signals to detect the inhale-exhale body motions while breathing. Compared to other remote wireless monitors, our sensor is less interfered by environmental noises as well as without direct contact with the body. The received I/Q signals are merged into one output and process to detect the frequency of breathing. The performance is evaluated using overnight sleep data and compared with ground-truth data measured by standard PSG airflow sensor. Result achieves high detection rate of 98.88% with mean squared error (MSE) of 1.23 over 420 one-minute recordings. In addition, the sensor is able to detect respiration accurately regardless of a person's sleep position. We demonstrate that our microwave sensor is robust and usable for real-time respiratory monitoring.

Feasibility Study of a Giant Magneto-Resistance Based Respiration Rate Monitor

This paper reports a simple and reliable electronic technique for the estimation of respiration rate (RR). Giant Magneto-Resistance (GMR) based sensors are employed to extract a plethysmograph signal from the subject. This signal is filtered and processed further through simple signal processing stages to obtain RR indication. The feasibility of the system has been studied on a prototype built and associated experimentation on 20 volunteers. The developed system provided clean plethysmographic signals, whose relevant features are shown to possess a relation with RR. Test results shows that the worst-case error in RR estimation of the system is merely 2 breaths per minute. Further, the capability of the system for detecting breathing cessations is studied and results reported. The system can be extended to function as a heart-rate (HR) monitor. Some basic results which proves the working and accuracy of system as a HR estimator is also given in the paper. The proposed system can be used for effective estimation of the above two vital signs in clinics, automotives, wearable devices, etc.

Breathing sensor selection during movement

A pressure sensor array placed below a mattress can be used to estimate the breathing effort signal unobtrusively. When multiple breathing effort sensor outputs are available, there is sometimes a need to choose the sensor with the best approximation of the actual breathing effort. Previous work with pressure sensor arrays placed on top of or under mattresses used for respiration rate and breathing signal estimation have used either the amplitude or the power spectrum to choose the most representative sensor. These methods are both useful when the subject is still; however, pressure sensor signals also contain movement. We propose and test a spectral ratio method for selection in the presence of movement. The spectral ratio method is good at finding strong breathing signals and at discriminating movement signals from strong breathing signals. This method provides a mean correlation to respiration bands that is 4% higher than the next best method during small movements and 14% higher during larger movements.