LEARNING SLEEP STAGES FROM RADIO SIGNALS

A method for tracking a sleep stage of a subject takes as input a sequence of observations sensed over an observation time period. The sequence of observation values is processed to yield a corresponding sequence of encoded observations using a first artificial neural network (ANN) and the sequence...

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Bibliographic Details
Main Authors ZHAO MINGMIN, JAAKKOLA TOMMI S, YUE SHICHAO, KATABI DINA
Format Patent
LanguageChinese
English
Published 29.11.2019
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Summary:A method for tracking a sleep stage of a subject takes as input a sequence of observations sensed over an observation time period. The sequence of observation values is processed to yield a corresponding sequence of encoded observations using a first artificial neural network (ANN) and the sequence of encoded observation values is processed to yield a sequence of sleep stage indicators using a second artificial network. Each observation may correspond to an interval of the observation period (e.g., at least 30 seconds). The first ANN may be configured to reduce information representing a source of the sequence of observations in the encoded observations. 用于跟踪受试者的睡眠阶段的方法采用在观测时间段内感测的观测结果序列作为输入。使用第一人工神经网络(ANN)来处理观测值序列以产生相应的编码观测结果序列,并且使用第二人工神经网络来处理编码观测值序列以产生睡眠阶段指标序列。各观测结果可以对应于观测时间段的间隔,例如至少30秒。第一ANN可被配置为减少编码观测结果中表示观测结果序列的源的信息。
Bibliography:Application Number: CN201880021763