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Video-based actigraphy is a non-contact technology that measures body movement through video recordings, commonly expressed as activity count. It has been widely used to assess infant sleep. One validated method for video-based actigraphy is the three-dimensional recursive search (3DRS). However, its sleep-wake classification performance in preterm infants is only moderately satisfactory, necessitating methods to improve it. This paper proposes an enhanced approach to compute activity count for video-based actigraphy in evaluating sleep patterns in preterm infants. The proposed technique involves applying exponentially weighted moving average (EWMA) to continuous activity count to reduce abrupt variations and false detection of wakefulness. Additionally, the 3DRS protocol we previously utilized is proprietary, limiting its accessibility to the public and its widespread adoption. To overcome this limitation, we have investigated the efficacy of an open-source algorithm known as background subtraction (BS), which, in our previous work, has demonstrated superior performance in body motion detection in preterm infants. To evaluate the performance of the proposed method, a dataset consisting of video recordings from five hospitalized preterm infants was used. The activity counts obtained from 3DRS, and BS were compared in terms of their ability to classify sleep and wake states using a linear discriminant classifier. The results obtained through leave-one-patient-out cross-validation revealed a significant improvement in the classification of sleep and wake states in preterm infants for both methods when the EWMA were applied to the activity counts. The mean Cohen's kappa coefficients were found to be 0.58 for 3DRS and 0.51 for BS. Despite BS exhibited comparatively lower performance than 3DRS, it can still be considered a viable alternative for acquiring video-based actigraphy data in the assessment of sleep of preterm infants.
Originele taal-2Engels
Titel2023 IEEE International Conference on E-health Networking, Application & Services, Healthcom
UitgeverijInstitute of Electrical and Electronics Engineers
Aantal pagina's5
ISBN van elektronische versie979-8-3503-0230-1
StatusGepubliceerd - 25 mrt. 2024
EvenementIEEE International Conference on E-health Networking, Application & Services, IEEE Healthcom 2023 - Chongqing, China
Duur: 15 dec. 202317 dec. 2023


CongresIEEE International Conference on E-health Networking, Application & Services, IEEE Healthcom 2023


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