Real-time Respiration Research Articles

소형화된 1.6 GHz 단일 채널 도플러 센서를 이용한 실시간 호흡 및 심장 박동 감지기

본 논문에서는 사람의 생체 신호를 감지하기 위해 1.6 GHz 단일 채널 도플러 센서와 아날로그 및 디지털 신호 처리부로 구성되어 있는 실시간 호흡 및 심장 박동 감지기를 개발하였다. 도플러 센서의 RF Front End는 발진기, 믹서, 저잡음 증폭기, 브랜치-라인 하이브리드, 그리고 패치 안테나로 구성되어 있다. 센서에 사용된 브랜치-라인 하이브리드는 기존의 하이브리드에 비해 40 % 정도 크기를 줄이면서도 상당히 유사한 성능을 가지도록 인공 전송 선로(artificial transmission line)를 사용하였다. 아날로그 신호처리부는 2차 Sallen-Key 능동 필터를 사용하여 제작되었고 디지털 신호 처리부는 LabVIEW를 사용하여 컴퓨터상에서 구현되었다. 개발된 시스템은 최대 50 cm 거리에서 사람의 호흡과 심장 박동을 측정함으로써 성능을 검증하였다. This paper presents a real-time respiration and heartbeat detector comprised of a 1.6 GHz single-channel Doppler sensor and analog/digital signal processing block for remote vital sign detection. The RF front end of the Doppler sensor consists of an oscillator, mixer, low noise amplifier, branch-line hybrid and patch antenna. We apply artificial transmission lines(ATLs) to the branch-line hybrid, which leads to a size reduction of 40 % in the hybrid, while its performance is very comparable to that of a conventional hybrid. The analog signal conditioning block is implemented using second order Sallen-Key active filters and the digital signal processing block is realized with a LabVIEW program on a computer. The respiration and heartbeat detection is demonstrated at a distance of 50 cm using the developed system.

Real-time respiration monitoring using the radiotherapy treatment beam and four-dimensional computed tomography (4DCT)—a conceptual study

Real-time knowledge of intra-fraction motion, such as respiration, is essential for four-dimensional (4D) radiotherapy. Surrogate-based and internal-fiducial-based methods may suffer from one or many drawbacks such as false correlation, being invasive, delivering extra patient radiation, and requiring complicated hardware and software development and implementation. In this paper we develop a simple non-surrogate, non-invasive method to monitor respiratory motion during radiotherapy treatments in real time. This method directly utilizes the treatment beam and thus imposes no additional radiation to the patient. The method requires a pre-treatment 4DCT and a real-time detector system. The method combines off-line processes with on-line processes. The off-line processes include 4DCT imaging and pre-calculating detector signals at each phase of the 4DCT based on the planned fluence map and the detector response function. The on-line processes include measuring detector signal from the treatment beam, and correlating the measured detector signal with the pre-calculated signals. The respiration phase is determined as the position of peak correlation. We tested our method with extensive simulations based on a TomoTherapy machine and a 4DCT of a lung cancer patient. Three types of simulations were implemented to mimic the clinical situations. Each type of simulation used three different TomoTherapy delivery sinograms, each with 800 to 1000 projections, as input fluences. Three arbitrary breathing patterns were simulated and two dose levels, 2 Gy/fraction and 2 cGy/fraction, were used for simulations to study the robustness of this method against detector quantum noise. The algorithm was used to determine the breathing phases and this result was compared with the simulated breathing patterns. For the 2 Gy/fraction simulations, the respiration phases were accurately determined within one phase error in real time for most projections of the treatment, except for a few projections at the start and end of the treatment in which beam intensities were extremely low. At 2 cGy/fraction dose level, the method can still determine the respiration phase very well with less than 10% of projections having more than two phases (∼1 s) error. This technique can also be applied in other delivery systems such as orthogonal x-ray systems, although in those cases it would entail the delivery of additional non-treatment radiation.

Bioartificial liver process monitoring and control systems with integrated systems capability.

Monitoring and control of a bioartificial liver (BAL) support system have the potential to allow for maximization of device bioactivity and protection of both patient and device from untoward consequences of a complex hemoperfused fluidic process, such as coagulation, leakage, or decreased metabolic output. In this work, an integrated embedded systems controller and associated experimental platform were developed to allow for simultaneous monitoring and control of the physical environment of the BAL support system to ensure optimal and sustained hepatic metabolic function and to allow for simplified recording of experimental data. The user interface and core embedded system kernel were developed with rapid prototyping software tools and allowed for operation of easily modified user interface panels. BAL environment monitoring consisted of real-time recording of ambient and reactor temperatures, reactor inlet pressure, the presence of bubbles in the prereactor inlet tubing, and aqueous oxygen tension. Environmental parameters under direct real-time control included reactor inlet flow rate, ambient temperature, and adaptive control of flow rate in response to changes in either inlet pressure or outlet oxygen tension. Use of embedded system integration techniques will facilitate subsequent BAL studies that are dependent on scale-up of reactor size and number, fluidic complexity, and the degree of parallelism such as large animal studies and, ultimately, human clinical studies. In addition, further studies of the effects of flow rate, shear, oxygenation and metabolic substrate on real-time cellular respiration can be pursued with the use of real-time ruthenium oxymetry, as described in this article.