Cardiac arrhythmia alarm from optical interferometric signals during resting or sleeping for early intervention

Optical fiber sensor for wearable and accurate human respiratory monitoring

Accurate respiratory monitoring is of great significance in assessing and analyzing physical health, and preventing respiratory diseases. The recently emerged wearable respiratory sensors are confronted with the challenges such as complex fabrication processes, limited accuracy, and stringent wearing requirements. An optical fiber sensor for accurate human respiratory monitoring is proposed and experimentally verified. The sensor head is composed of a piece of seven core fiber sandwiched between two single-mode fibers by two fiber bitapers, which is embedded in a textile sheet and freely worn on the upper body. An efficient signal demodulation system is set up to acquire the respiratory signal, while Fourier transform (FFT) and short-time Fourier transform (STFT) methods are used to analyze the measured signal. Six volunteers are invited to perform the respiratory experiment, and the experimental results demonstrate that the sensor can accurately detect and distinguish respiratory signals under different humans, different states (normal, slow, fast), different body parts (abdomen, chest, back), different postures (standing, sitting, lying), and irregular respiration. The Pearson correlation coefficient of the sensor is higher than 0.9, which is consistent with commercial respiratory sensor. Meanwhile, the instability of the sensor is 0.003 Hz for the same volunteer in 6 months. The sensor has the advantages of high sensitivity, good stability and wearing comfort, showing good potential in healthcare applications.

Monitoring and Synchronization of Cardiac and Respiratory Traces in Magnetic Resonance Imaging: A Review

Synchronization of human vital signs, namely the cardiac cycle and respiratory excursions, is necessary during magnetic resonance imaging of the cardiovascular system and the abdominal cavity to achieve optimal image quality with minimized artifacts. This review summarizes techniques currently available in clinical practice, as well as methods under development, outlines the benefits and disadvantages of each approach, and offers some unique solutions for consideration.

Sleep Monitoring Based on a Tri-Axial Accelerometer and a Pressure Sensor

Sleep disorders are a common affliction for many people even though sleep is one of the most important factors in maintaining good physiological and emotional health. Numerous researchers have proposed various approaches to monitor sleep, such as polysomnography and actigraphy. However, such approaches are costly and often require overnight treatment in clinics. With this in mind, the research presented here has emerged from the question: "Can data be easily collected and analyzed without causing discomfort to patients?" Therefore, the aim of this study is to provide a novel monitoring system for quantifying sleep quality. The data acquisition system is equipped with multimodal sensors, including a three-axis accelerometer and a pressure sensor. To identify sleep quality based on measured data, a novel algorithm, which uses numerous physiological parameters, was proposed. Such parameters include non-REM sleep time, the number of apneic episodes, and sleep durations for dominant poses. To assess the effectiveness of the proposed system, three participants were enrolled in this experimental study for a duration of 20 days. From the experimental results, it can be seen that the proposed monitoring system is effective for quantifying sleep quality.