A new non-invasive approach for monitoring respiratory movements of sleeping subjects

Hernandez, Luis Radford; Waag, Barbara J.; Hsiao, Hsien Sheng; Neelon, Virginia J.

doi:10.1088/0967-3334/16/3/003

Cited by 20 publications

(15 citation statements)

References 7 publications

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“…However, similarly to PNT, a close fitting face mask is required to interface the instrument and the patient, which can be excessively intrusive. 17,18 Regarding the early mentioned limitations, great efforts have been straightly employed to develop [19][20][21] and evaluate 22-24 respiratory monitoring systems toward detect abnormalities in breathing during sleep. Accordingly, Hernandez et al 19 detected the respiratory movements of the subjects using a system based on a pressure transducer which measures the changes in air pressure inside an inflatable mattress on which the subject sleeps.…”

Section: A Traditional Sleep Respiratory Monitoring Technology and Mmentioning

confidence: 99%

“…17,18 Regarding the early mentioned limitations, great efforts have been straightly employed to develop [19][20][21] and evaluate 22-24 respiratory monitoring systems toward detect abnormalities in breathing during sleep. Accordingly, Hernandez et al 19 detected the respiratory movements of the subjects using a system based on a pressure transducer which measures the changes in air pressure inside an inflatable mattress on which the subject sleeps. Using a charge coupled device camera associated with a PC equipped with a high speed image processor, Nakajim et al 20 developed a system able to evaluate the respiratory rate of a sleeping subject without any physical contact.…”

Section: A Traditional Sleep Respiratory Monitoring Technology and Mmentioning

confidence: 99%

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Respiratory monitoring system based on the nasal pressure technique for the analysis of sleep breathing disorders: Reduction of static and dynamic errors, and comparisons with thermistors and pneumotachographs

Júnior

Melo

2004

Review of Scientific Instruments

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Thermally sensitive devices—thermistors—have usually been used to monitor sleep-breathing disorders. However, because of their long time constant, these devices are not able to provide a good characterization of fast events, like hypopneas. Nasal pressure recording technique (NPR) has recently been suggested to quantify airflow during sleep. It is claimed that the short time constants of the devices used to implement this technique would allow an accurate analysis of fast abnormal respiratory events. However, these devices present errors associated with nonlinearities and acoustic resonance that could reduce the diagnostic value of the NPR. Moreover, in spite of the high scientific and clinical potential, there is no detailed description of a complete instrumentation system to implement this promising technique in sleep studies. In this context, the purpose of this work was twofold: (1) describe the development of a flexible NPR device and (2) evaluate the performance of this device when compared to pneumotachographs (PNTs) and thermistors. After the design details are described, the system static accuracy is evaluated by a comparative analysis with a PNT. This analysis revealed a significant reduction (p<0.001) of the static error when system nonlinearities were reduced. The dynamic performance of the NPR system was investigated by frequency response analysis and time constant evaluations and the results showed that the developed device response was as good as PNT and around 100 times faster (τ=5,3 ms) than thermistors (τ=512 ms). Experimental results obtained in simulated clinical conditions and in a patient are presented as examples, and confirmed the good features achieved in engineering tests. These results are in close agreement with physiological fundamentals, supplying substantial evidence that the improved dynamic and static characteristics of this device can contribute to a more accurate implementation of medical research projects and to improve the diagnoses of sleep-breathing disorders.

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Section: A Traditional Sleep Respiratory Monitoring Technology and Mmentioning

confidence: 99%

Section: A Traditional Sleep Respiratory Monitoring Technology and Mmentioning

confidence: 99%

Respiratory monitoring system based on the nasal pressure technique for the analysis of sleep breathing disorders: Reduction of static and dynamic errors, and comparisons with thermistors and pneumotachographs

Júnior

Melo

2004

Review of Scientific Instruments

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“…Due to the physical and cognitive impairments of those elderly, they have to lie in the bed most of their time. Besides monitoring of various physiological parameters continuously [1,2], it is important to monitor presence, activities and interactions of bedridden elderly in and around the bed.…”

Section: Introductionmentioning

confidence: 99%

Evaluation and analysis of multimodal sensors for developing in and around the bed patient monitoring system

Aung

Foo

Huang

et al. 2010

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology

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Due to the decline in physical and cognitive abilities, many frail elderly may have to lie in the bed most of their time. It is not feasible to monitor them continuously through manual observations alone. This issue can be resolved by embedding a set of multimodal sensors into the bed and providing automated activity recognition intelligence. But it is important to design and develop such multimodal sensing intelligence system desirable to the demands made by the clinicians. This paper presents the comparison and evaluation of different sensing bed configurations to observe different granularities of patient's contexts and activities in and around the bed. Based on the achievements and lessons learned from the experimental analysis, we propose improved sensing bed hardware and software systems to meet the real needs of in and around the bed patient monitoring.

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“…There were numerous BCG researches with various types of measurement system. One of the these unconstrained measurement BCG systems are presented Hernandez et al (1995) [2], Chow et al (2000) [3] and Watanabe and Watanabe (2004) [4] used an air mattress system under the body as a sensor for respiration movements. The heart beat movements add pressure to the air mattress, which changes the air pressure in the mattress.…”

Section: Introductionmentioning

confidence: 99%

Automatic ballistocardiogram (BCG) beat detection using a template matching approach

Shin

Choi

Lim

et al. 2008

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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This paper suggests a beat detection method for ballistocardiogram (BCG) from an unconstrained cardiac signal monitoring devices. A fiducial peak point of BCG is an I-J-K complex which corresponds with ventricle contraction and Electrocardiogram (ECG) QRS complex. The goal of the method is extraction of J peak without ECG synchronization. The detection method is based on a "template matching" rule evaluated using a correlation function in a local moving-window procedure. The total beat detection algorithm operates in two stages, template definition stage and beat detection stage with defined template in previous stage. In the first stage, the BCG template is constructed by the expert with an empirical analysis of BCG signal and measurement device. In the second stage, the correlation function calculates an accuracy of template with BCG signal using a local moving-window. The data analysis has been performed on the subjects tested at Seoul National University Hospital Sleep Medicine Center and presents 95.16% of sensitivity and 94.76% of positive predictivity value for the J peak detection.

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A new non-invasive approach for monitoring respiratory movements of sleeping subjects

Cited by 20 publications

References 7 publications

Respiratory monitoring system based on the nasal pressure technique for the analysis of sleep breathing disorders: Reduction of static and dynamic errors, and comparisons with thermistors and pneumotachographs

Respiratory monitoring system based on the nasal pressure technique for the analysis of sleep breathing disorders: Reduction of static and dynamic errors, and comparisons with thermistors and pneumotachographs

Evaluation and analysis of multimodal sensors for developing in and around the bed patient monitoring system

Automatic ballistocardiogram (BCG) beat detection using a template matching approach

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