Remote monitoring of infant’s breathing motions using a smartphone to prevent crib death

Abstract

Crib death can be burdensome for new parents as it has no prior markers and cannot be predicted. Currently available devices for monitoring signs of crib death are quite expensive and thus are not available for everyone. The intention of this thesis was to develop an iOS application which could be used to monitor breathing movements of a sleeping infant and would be available for everyone with a smartphone. The used device was an iPhone 6s. The application utilizes the Doppler method by outputting 18 000 Hz audio and recording the reflected signals. The frequency of the input audio is analyzed to detect possible frequency shifts. These shifts in frequency are interpreted as movement by the algorithm. If no movement is detected in 20 seconds, the application will start alerting parents. By utilizing the developed application, this research aims to analyze the adequacy of using a smartphone in medical monitoring and producing, recording and processing high frequency audio. Also the applicability of using high frequency audio in monitoring infant’s breathing motions and detect signs of crib death are investigated. Experimentation was done initially by recording different scenarios such as turning in bed or moving body parts to ensure the application is able to detect movements. Further recordings were made by simulating infant’s breathing motions by shallow and fast breathing and the application was optimized based on the results. Eventually the application was validated by monitoring a 11 days old baby successfully.