T/CPAM 002-2020 Active Group standards

T/CPAM 002-2020 Sleep monitoring signal machine analysis and interpretation specification

T/CPAM 002-2020 Sleep monitoring signal machine analysis and interpretation specification

Publish Date: 2021-03-12 Implement Date: 2021-03-12 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/CPAM 002-2020
Standard Type: Group standards
Standard Status: Active
is_force_gb: no
CCS Name: Mechanical Integration
ICS Name: Integrated medical equipment
Publish Date: 2021-03-12
Implement Date: 2021-03-12

Scope

Scope: "This standard specifies the manual analysis standards, data collection norms, data analysis norms, and testing and evaluation indicators for sleep pattern machine analysis and interpretation of polysomnography (PSG) products." This standard applies to the machine analysis and interpretation of physiological signals collected by sleep monitoring products for individuals aged 14 years and above. Main technical content: This specification focuses on the machine analysis and interpretation of physiological signal data collected by sleep respiration monitoring products, and stipulates the norms for manual analysis and interpretation, data collection, data analysis applied to artificial intelligence, and testing and evaluation. The main content is as follows: (1) The norms for manual analysis and interpretation stipulate the technical and interpretation norms for sleep data such as electroencephalograms, respiration, and awakening. (2) The data collection norms stipulate the standards for data collection and electrode installation. (3) The data analysis norms applied to artificial intelligence stipulate the evaluation of raw data, the data requirements for artificial intelligence training and analysis, and the output mode of results. (4) The testing and evaluation norms stipulate the evaluation indicators for sleep stages, the identification of sleep respiration events such as respiratory events and awakening, and the evaluation of the effectiveness of these identifications.

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