A Vision-Based Infant Respiratory Frequency Detection System

Fang, Chiung‐Yao; Hsieh, Hsin-Hung; Chen, Sei-Wang

doi:10.1109/dicta.2015.7371224

Cited by 13 publications

(11 citation statements)

References 21 publications

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“…Motion characterization Cuppens et al 2010Dogra et al 2012Ntonfo et al 2012Orlandi et al 2015 Classification Feed Forward Neural Networks Karayiannis et al 2005b, 2006 Support Vector Machine Stahl et al 2012Rahmati et al 2014 Logistic regression Adde et al 2009Adde et al , 2010 Respiration estimation Villarroel et al 2014Cattani et al 2014Fang et al 2015Koolen et al 2015Brieva 2017Antognoli 2018Alinovi 2018 Heart rate estimation Aarts et al 2013Villarroel et al 2014Sikdar et al 2015van Gastel et al 2018 Face analysis…”

Section: For Video Processingmentioning

confidence: 99%

See 1 more Smart Citation

Video and audio processing in paediatrics: a review

Cabon¹,

Porée²,

Simon³

et al. 2019

Physiol. Meas.

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Objective: Video and sound acquisition and processing technologies have seen great improvements in recent decades, with many applications in the biomedical area. The aim of this paper is to review the overall state of the art of advances within these topics in paediatrics and to evaluate their potential application for monitoring in the neonatal intensive care unit (NICU). Approach: For this purpose, more than 150 papers dealing with video and audio processing were reviewed. For both topics, clinical applications are described according to the considered cohorts—full-term newborns, infants and toddlers or preterm newborns. Then, processing methods are presented, in terms of data acquisition, feature extraction and characterization. Main results: The paper first focuses on the exploitation of video recordings; these began to be automatically processed in the 2000s and we show that they have mainly been used to characterize infant motion. Other applications, including respiration and heart rate estimation and facial analysis, are also presented. Audio processing is then reviewed, with a focus on the analysis of crying. The first studies in this field focused on induced-pain cries and the newest ones deal with spontaneous cries; the analyses are mainly based on frequency features. Then, some papers dealing with non-cry signals are also discussed. Significance: Finally, we show that even if recent improvements in digital video and signal processing allow for increased automation of processing, the context of the NICU makes a fully automated analysis of long recordings problematic. A few proposals for overcoming some of the limitations are given.

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Section: For Video Processingmentioning

confidence: 99%

“…Respiratory signals were then obtained from the frame by frame evolution of the intensity of automatically selected pixels in the accumulative sum. The method showed good results in 46 video sequences (Fang et al, 2015).…”

mentioning

confidence: 92%

Video and audio processing in paediatrics: a review

Cabon¹,

Porée²,

Simon³

et al. 2019

Physiol. Meas.

View full text Add to dashboard Cite

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“…The studies that focus on this problem adapt two particular techniques. On the one hand, there are works that propose non-invasive monitoring [ 46 , 47 , 48 , 49 , 50 ] and use different methodologies for this purpose. The authors of [ 46 ] analyzed the images taken by a camera installed on the baby’s crib in order to detect breathing movements.…”

Section: Previous Workmentioning

confidence: 99%

“…On the one hand, there are works that propose non-invasive monitoring [ 46 , 47 , 48 , 49 , 50 ] and use different methodologies for this purpose. The authors of [ 46 ] analyzed the images taken by a camera installed on the baby’s crib in order to detect breathing movements. The authors of [ 47 ] proposed the analysis of acoustic signals produced by the neonate; they were registered by a microphone installed in its cradle.…”

Section: Previous Workmentioning

confidence: 99%

A Context-Aware Indoor Air Quality System for Sudden Infant Death Syndrome Prevention

Iglesia

Paz

González

et al. 2018

Sensors

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Context-aware monitoring systems designed for e-Health solutions and ambient assisted living (AAL) play an important role in today’s personalized health-care services. The majority of these systems are intended for the monitoring of patients’ vital signs by means of bio-sensors. At present, there are very few systems that monitor environmental conditions and air quality in the homes of users. A home’s environmental conditions can have a significant influence on the state of the health of its residents. Monitoring the environment is the key to preventing possible diseases caused by conditions that do not favor health. This paper presents a context-aware system that monitors air quality to prevent a specific health problem at home. The aim of this system is to reduce the incidence of the Sudden Infant Death Syndrome, which is triggered mainly by environmental factors. In the conducted case study, the system monitored the state of the neonate and the quality of air while it was asleep. The designed proposal is characterized by its low cost and non-intrusive nature. The results are promising.

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“…During the last decades, several features extracted from audio or video data have been proven to be relevant indicators of newborn conditions regarding a large scope of clinical situations [10]. Hence, Black and White (BW) cameras were used for motion analyses in order to detect cerebral palsy [11] or neonatal seizures [12] but also to estimate physiological signals such as cardiac pulse [13] or respiratory [14] rates. The last two points were also investigated with color cameras [15,16,17].…”

Section: Introductionmentioning

confidence: 99%

Voxyvi: A system for long-term audio and video acquisitions in neonatal intensive care units

Cabon

Porée

Cuffel³

et al. 2021

Early Human Development

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Background: In the European Union, 300 000 newborn babies are born prematurely every year.Their care is ensured in Neonatal Intensive Care Units (NICU) where vital signs are constantly monitored. In addition, other descriptors such as motion, facial and vocal activities have been shown to be essential to assess neurobehavioral development.Aim: In the scope of the European project Digi-NewB, we aimed to develop and evaluate a new audio-video device designed to non-invasively acquire multi-modal data (audio, video and thermal images) , while fitting the wide variety of bedding environment in NICU.Methods: Firstly, a multimodal system and associated software and guidelines to collect data in neonatal intensive care unit were proposed. Secondly, methods for post-evaluation of the acquisition phase were developed, including the study of clinician feedback and a qualitative analysis of the data. Results:The deployment of 19 acquisition devices in six French hospitals allowed to record more than 500 newborns of different gestational and postmenstrual ages. After the acquisition phase, clinical feedback was mostly positive. In addition, quality of more than 300 recordings was inspected and showed that 77% of the data is exploitable. In depth , the percentage of sole presence of the newborn was estimated at 62% within recordings.Conclusions: This study demonstrates that audio-video acquisitions are feasible on a large scale in real life in NICU. The experience also allowed us to make a clear observation of the requirements and challenges that will have to be overcome in order to set up audio-video monitoring methods.

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A Vision-Based Infant Respiratory Frequency Detection System

Cited by 13 publications

References 21 publications

Video and audio processing in paediatrics: a review

Video and audio processing in paediatrics: a review

A Context-Aware Indoor Air Quality System for Sudden Infant Death Syndrome Prevention

Voxyvi: A system for long-term audio and video acquisitions in neonatal intensive care units

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