T/CSRS 004-2023 Active Group standards

T/CSRS 004-2023 Objective evaluation system and technical standards for objective evaluation of sleep-disordered breathing airway sound monitoring

T/CSRS 004-2023 Objective evaluation system and technical standards for objective evaluation of sleep-disordered breathing airway sound monitoring

Publish Date: 2023-08-18 Implement Date: 2024-01-01 For services related to genuine standard inquiry, procurement, translation, and other related services in China, please Contact Us
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Basic Information

Standard Code: T/CSRS 004-2023
Standard Type: Group standards
Standard Status: Active
is_force_gb: no
CCS Name: -
ICS Name: Integrated medical science and healthcare devices
Publish Date: 2023-08-18
Implement Date: 2024-01-01

Scope

Scope: This standard specifies the necessary conditions and detection methods for airway acoustic monitoring of sleep-disordered breathing, as well as the objective evaluation system and recommended technical standards for airway acoustic monitoring of sleep-disordered breathing. This standard is only applicable to airway acoustic monitoring of sleep-disordered breathing. Main technical content: Obstructive sleep apnea is one of the most common sleep disorders, which seriously endangers patients' health. Polysomnography is the gold standard for diagnosing sleep apnea, but it is expensive and cumbersome to operate. Therefore, audio-based sleep apnea monitoring systems are widely used. However, most audio-based systems have two major drawbacks: on the one hand, ignoring the awake segment leads to a dilution effect; on the other hand, it is unable to monitor mild breathing, resulting in an overestimation of the apnea index. This standard extracts snoring and neck pulse sounds from the patient's tracheal sound signal for the diagnosis of sleep apnea, can calculate the apnea-hypopnea index (AHI) to analyze the severity, and effectively improve the accuracy of diagnosis based solely on snoring. Research content: 1. Build a model of the upper airway vocalization mechanism and explore the impact of different types of sleep-disordered breathing on upper airway sounds based on respiratory dynamics; 2. Study the acquisition of physiological information from upper airway bone conduction sounds, with a focus on signal separation algorithms based on bone conduction sounds to improve the efficiency of obtaining upper airway physiological information; 3. Deeply explore the characteristics of upper airway physiological information and establish an effective mapping between upper airway physiological information and different types of sleep-disordered breathing to improve the accuracy of sleep-disordered breathing assessment. Research plan: 1. Use the model of upper a

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