Article

Automated Closed Loop Control of Inspired Oxygen Concentration

Division of Neonatology, Department of Pediatrics, University of Miami Miller School of Medicine, Miami, Florida.
Respiratory care (Impact Factor: 1.84). 01/2013; 58(1):151-61. DOI: 10.4187/respcare.01955
Source: PubMed

ABSTRACT Oxygen therapy is extensively used in premature infants and adults with respiratory insufficiency. In the premature infant the goal during manual control of the F(IO(2)) is to maintain adequate oxygenation and to minimize the exposure to hypoxemia, hyperoxemia, and oxygen. However, this is frequently not achieved during routine care, which increases the risks of associated side effects affecting the eye, lungs, and central nervous system. In the adult the primary goal is to avoid hypoxemia, but conventional methods of oxygen supplementation may fall short during periods of increased demand. On the other hand, there are growing concerns related to unnecessarily high F(IO(2)) levels that increase the exposure to hyperoxemia and excessive oxygen use in settings where resources are limited. Systems for automated closed loop control of F(IO(2)) have been developed for use in neonates and adults. This paper will give an overview of the rationale for the development of these systems, present the evidence, and discuss important advantages and limitations.

1 Follower
 · 
111 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Architectures capable of using an algorithm to modify actuation based on measured signals are often called "closed-loop" systems. While such systems are traditionally thought to rely on algorithms residing in device firmware, these may also reside outside the device in a host processor located physically nearby, or on a cloud-based architecture. In order to serve the potentially broad array of data processing modalities, we have developed an application programming interface (API). The API enables access to the sensing and stimulation capabilities of an implantable bi-directional neural interface. Systems using the API on different hardware/software platforms could measure neural signals, process signals in real-time, and modulate stimulation parameters using a variety of algorithms. This flexibility allows increased algorithm access and enables rapid prototyping for potentially improved technology solutions. The system performance was characterized using a signal generator to input square wave pulses to a Simulink model via the API. Closed-loop stimulation latencies of around 600ms were achieved. I. NEED FOR PROTOTYPING SYSTEMS FOR CLOSED-LOOP NEUROMODULATION Neurostimulation is used to treat a variety of neurological diseases such as Parkinson's disease, essential tremor, urinary incontinence, and chronic pain. To function properly, these technologies require both accurate hardware placement (e.g., placing leads in the correct nervous system location) as well as therapy parameter setting optimization (e.g. electrode selection, stimulation amplitude, pulse width, and frequency). Selection of optimal parameters is largely an empirical process that may involve multiple, time-consuming device programming sessions spread apart by weeks or months. Outside of these sessions, the ability to make stimulation parameter adjustments is generally limited.
    IEEE EMBS Neural Engineering, San Diego, CA, USA; 11/2013
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Architectures capable of using an algorithm to modify actuation based on measured signals are often called “closed-loop” systems. While such systems are traditionally thought to rely on algorithms residing in device firmware, these may also reside outside the device in a host processor located physically nearby, or on a cloud-based architecture. In order to serve the potentially broad array of data processing modalities, we have developed an application programming interface (API). The API enables access to the sensing and stimulation capabilities of an implantable bi-directional neural interface. Systems using the API on different hardware/software platforms could measure neural signals, process signals in realtime, and modulate stimulation parameters using a variety of algorithms. This flexibility allows increased algorithm access and enables rapid prototyping for potentially improved technology solutions. The system performance was characterized using a signal generator to input square wave pulses to a Simulink model via the API. Closed-loop stimulation latencies of around 600ms were achieved.
    Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on; 01/2013
  • [Show abstract] [Hide abstract]
    ABSTRACT: Randomized controlled trials evaluating low-target oxygen saturation (SpO2:85% to 89%) vs high-target SpO2 (91% to 95%) have shown variable results regarding mortality and morbidity in extremely preterm infants. Because of the variation inherent to the accuracy of pulse oximeters, the unspecified location of probe placement, the intrinsic relationship between SpO2 and arterial oxygen saturation (SaO2) and between SaO2 and partial pressure of oxygen (PaO2) (differences in oxygen dissociation curves for fetal and adult hemoglobin), the two comparison groups could have been more similar than dissimilar. The SpO2 values were in the target range for a shorter period of time than intended due to practical and methodological constraints. So the studies did not truly compare 'target SpO2 ranges'. In spite of this overlap, some of the studies did find signficant differences in mortality prior to discharge, necrotizing enterocolitis and severe retinopathy of prematurity. These differences could potentially be secondary to time spent beyond the target range (SpO2 <85 or >95%) and could be avoided with an intermediate but wider target SpO2 range (87% to 93%). In conclusion, significant uncertainty persists about the desired target range of SpO2 in extremely preterm infants. Further studies should focus on studying newer methods of assessing oxygenation and strategies to limit hypoxemia (<85% SpO2) and hyperoxemia (>95% SpO2).Journal of Perinatology advance online publication, 30 October 2014; doi:10.1038/jp.2014.199.
    Journal of perinatology: official journal of the California Perinatal Association 10/2014; DOI:10.1038/jp.2014.199 · 2.35 Impact Factor