Chinese Academy of Sciences

Shenzhen Institutes of Advanced Technology

Fen Miao

Ye Li

Shuqiang Wang

Xiaomao Fan

Yunpeng Cai

Yiqian Lu

Senrong You

Guobao Wu

Chitang Zhang

Furu Xiang

An infrared image sequence-based sleep quality evaluation system and method. The method comprises: obtaining a plurality of respiratory infrared image sequences to be evaluated, one respiratory infrared image sequence comprising a plurality of respiratory infrared image frames to be evaluated; performing sleep quality evaluation on each respiratory infrared image sequence in the plurality of respiratory infrared image sequences by means of a classifier to obtain a sleep quality evaluation result corresponding to each respiratory infrared image sequence; and counting the number of different sleep quality evaluation results according to the sleep quality evaluation results respectively corresponding to the plurality of respiratory infrared image sequences, and determining the sleep quality evaluation result with the largest number as a sleep quality evaluation result of a user. Contactless sleep monitoring can be carried out on a user, monitoring costs are reduced at the same time, and evaluation accuracy of sleep quality is improved.

Infrared image sequence-based sleep quality evaluation system and method comprising performing evaluation by a classifier and counting the sleep quality evaluation results to determine the largest number to judge good or poor sleep quality

The present disclosure provides a GPU-based parallel electrocardiogram signal analysis method, comprising: performing a filtering process of electrocardiogram signals through a long interval artifact removal and a short interval artifact removal; performing a QRS detection of the filtering-processed electrocardiogram signals through an R-wave position extraction, a QRS complex start and end positions extraction and a QRS complex width extraction; performing an abnormal waveform classification of the QRS-detected electrocardiogram signals through template creation; wherein at least one of the long interval artifact removal, the short interval artifact removal, the R-wave position extraction, the QRS complex width extraction and the creation template is performed by a multiple threads at a GPU device side in parallel, any thread being read through its unique index number to process corresponding data. By executing one or more steps of the electrocardiogram signal analysis at GPU in parallel, the present disclosure increases the analysis speed of the electrocardiogram signals.

GPU-based parallel electrocardiogram signal analysis method, computer readable storage medium and device

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Guangdong, China

Fen Miao