Sleep Apnea Detection Using an Adaptive Fuzzy Logic Based Screening System

Morsy, Ahmed; Al-Ashmouny, K. M.

doi:10.1109/iembs.2005.1615891

Cited by 21 publications

(12 citation statements)

References 19 publications

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“…In the literature there are similar proposals that generate the same information. 2,4,5,22,23,32,33 Our algorithms are capable of identifying apneas, hypopneas, desaturations, thoracic and abdominal movement limitations and snoring in the polysomnogram. 25 For the study presented in this paper, they were only used to identify apneas, hypopneas and desaturations.…”

Section: Indexes Generationmentioning

confidence: 99%

An Evaluation of Indexes as Support Tools in the Diagnosis of Sleep Apnea

et al. 2012

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This article evaluates several indexes as support tools to diagnose patients with Sleep Apnea-Hypopnea Syndrome (SAHS). Some of these indexes, such as the Apnea-Hypopnea Index, have been standardized and studied in depth in the literature. Other indexes are used extensively in the reports that commercial polysomnographs generate. However, they have not been studied in detail and clinicians have no standardized guidelines for interpreting them. Examples are the mean and maximum duration of apneas and hypopneas. Finally, several novel indexes proposed by the authors are also evaluated. To evaluate the indexes, we have used a database of 274 patients who have undergone a polysomnographic test. Several feature selection techniques were used to assess the capability of each index to discriminate between healthy and SAHS patients. The capability of the indexes for diagnosing the patients was analyzed by using decision trees which were trained using each index individually, and all the indexes together. Our results suggest that some indexes which are often present in the reports of commercial polysomnographs provide little or no information. On the other hand, other indexes that are usually not considered have a great capability to discern between SAHS and control patients.

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Section: Indexes Generationmentioning

confidence: 99%

An Evaluation of Indexes as Support Tools in the Diagnosis of Sleep Apnea

et al. 2012

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“…In the literature there are several proposals to identify these events [1], [4], [5], [8], [9]. We have used algorithms that we previously developed for this purpose (see Figure 1).…”

Section: A Features Derived From the Pathological Eventsmentioning

confidence: 99%

Is the average duration of apneas, hypopneas and desaturations useful in the diagnosis of SAHS?

Otero

Félix

Presedo

et al. 2011

2011 IEEE 7th International Symposium on Intelligent Signal Processing

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Sleep Apnea-Hypopnea Syndrome (SAHS) is usually diagnosed by polysomnography, a test that consists of the registration of a wide range of physiological parameters while the patient is asleep. The commercial monitoring devices used in the polysomnography generate a report summarizing the test. Some of the information presented to the clinicians in these reports, such as the Apnea-Hypopnea Index, has been the target of comprehensive clinical studies, and there are detailed clinical guidelines to interpret it. However, these reports also contain other data such as mean and maximum values of the descriptors of various pathological events recorded in the polysomnogram; e.g., the mean and maximum duration of the apneas, hypopneas and desaturations that the patient has experienced. These features have not been studied in the literature. Therefore, guidelines for their interpretation do not exist.This paper attempts to evaluate the usefulness of this information in the diagnosis of SAHS. It also tries to provide guidelines for clinicians on how to interpret it. To this end, we have calculated these features for 210 patients who underwent polysomnographic testing, and we have analyzed their capability to discriminate between healthy and SAHS patients, as well as to stratify the patients according to their severity. Our results suggest that most of them have little or no utility for diagnosing SAHS patients. Therefore, they could be omitted from the reports without significant loss of information.

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“…However, it is expensive, inconvenient, time-consuming, and labor intensive. We have previously reported a system suitable for detection and classification of SA using only three breathing signals: nasal airflow, thorax movement, and abdomen movement [6]. We have also presented a comparative study between Alice ® 4 Sleep Diagnostic System (Respironics, Inc., Pittsburgh, PA, USA) and our fuzzy logic based system for automatic detection and classification.…”

Section: Introductionmentioning

confidence: 99%

FPGA-based Sleep Apnea Screening Device for Home Monitoring

Al-ashmouny¹,

Hamed²,

Morsy³

2006

2006 International Conference of the IEEE Engineering in Medicine and Biology Society

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We present the hardware design of an FPGAbased portable device for home screening of sleep apnea syndromes. The device is simple to use, inexpensive, and uses only three signals, namely the nasal air flow and the thorax and abdomen effort signals. The device hardware stores data of overnight sleep on a Secure Digital card. At the clinic, the sleep specialist reads in the stored data and uses an algorithm for the detection and classification of sleep apnea. The device is fairly low-cost and may help spread the ability to diagnose more cases of sleep apnea. Most sleep apnea cases currently go undiagnosed because of cost and practicality limitations of overnight polysomnography at sleep labs.

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Sleep Apnea Detection Using an Adaptive Fuzzy Logic Based Screening System

Cited by 21 publications

References 19 publications

An Evaluation of Indexes as Support Tools in the Diagnosis of Sleep Apnea

An Evaluation of Indexes as Support Tools in the Diagnosis of Sleep Apnea

Is the average duration of apneas, hypopneas and desaturations useful in the diagnosis of SAHS?

FPGA-based Sleep Apnea Screening Device for Home Monitoring

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