Quantitative classification of pediatric swallowing through accelerometry
1 Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
2 Bloorview Research Institute, , 150 Kilgour Road, Toronto, Ontario, Canada
3 Department of Paediatrics, North York General Hospital, 4001 Leslie St. Toronto, Ontario, Canada
4 Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA
Journal of NeuroEngineering and Rehabilitation 2012, 9:34 doi:10.1186/1743-0003-9-34Published: 9 June 2012
Dysphagia or swallowing disorder negatively impacts a child’s health and development. The gold standard of dysphagia detection is videofluoroscopy which exposes the child to ionizing radiation, and requires specialized clinical expertise and expensive institutionally-based equipment, precluding day-to-day and repeated assessment of fluctuating swallowing function. Swallowing accelerometry is the non-invasive measurement of cervical vibrations during swallowing and may provide a portable and cost-effective bedside alternative. In particular, dual-axis swallowing accelerometry has demonstrated screening potential in older persons with neurogenic dysphagia, but the technique has not been evaluated in the pediatric population.
In this study, dual-axis accelerometric signals were collected simultaneous to videofluoroscopic records from 29 pediatric participants (age 6.8 ± 4.8 years; 20 males) previously diagnosed with neurogenic dysphagia. Participants swallowed 3-5 sips of barium-coated boluses of different consistencies (normally, from thick puree to thin liquid) by spoon or bottle. Videofluoroscopic records were reviewed retrospectively by a clinical expert to extract swallow timings and ratings. The dual-axis acceleration signals corresponding to each identified swallow were pre-processed, segmented and trimmed prior to feature extraction from time, frequency, time-frequency and information theoretic domains. Feature space dimensionality was reduced via principal components.
Using 8-fold cross-validation, 16-17 dimensions and a support vector machine classifier with an RBF kernel, an adjusted accuracy of 89.6% ± 0.9 was achieved for the discrimination between swallows with and with out airway entry.
Our results suggest that dual-axis accelerometry has merit in the non-invasive detection of unsafe swallows in children and deserves further consideration as a pediatric medical device.