Paper Info
Title
Monitoring Sucking Abilities in Newborns: Design and Validation on Adult Of a Wearable System for Non-Invasive Deglutition Detection.
Abstract
Nutritive Sucking (NS) is one of the earliest motor activity performed by infants, strictly related to both neurological and motor development of newborns. The main components of NS are sucking, respiration and deglutition. Despite its recognized importance, current clinical practice lacks quantitative tools for the assessment of NS. This work aims to identify a non-invasive objective method to assess deglutition. In details, we propose a new sensor fusion approach to merge both inertial and acoustic data in order to estimate deglutition time. The algorithm uses two classification criteria: one is based on signal intensity thresholding and the other on the evaluation of Waveform Dimension Trajectory (WDT). Our preliminary results on 9 healthy adult volunteers show that the sensor fusion of audio and IMU signals provides a high precision (0.93) and a good recall (0.72). Moreover, the algorithm has a good accuracy (0.84) and high specificity (0.95).
Year
DOI
Venue
2018
10.1109/EMBC.2018.8513381
EMBC
Field
DocType
Volume
Computer vision,Swallowing,Pattern recognition,Wearable computer,Accelerometer,Motor skill,Computer science,Sensor fusion,Inertial measurement unit,Artificial intelligence,Thresholding,Statistical classification
Conference
2018
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Micaela Del Fabbro Arcopinto100.34
Jacopo Tosi200.34
Domenico Formica38826.60
Fabrizio Taffoni45813.31