Abstract
Early and accurate dysphagia diagnosis is essential for reducing the risk of associated co-morbidities and mortalities. Barriers to current evaluation methods may alter the effectiveness of identifying at-risk patients. Costs, invasiveness, reduced accessibility, variable reliability, and time-consuming measures limit screening and instrumental assessments.
This study uses the widely available iPhone to investigate the feasibility of a simple non-contact and non-invasive dysphagia screening tool. Video recordings of the anterior and lateral neck were captured simultaneously with a videofluoroscopy in dysphagic patients. Videos were analysed using a sub-pixel image registration algorithm (phase-based Savitzly-Golay gradient correlation (P-SG-GC)) to determine skin displacements over regions of interest related to the hyoid bone and larynx. Impairment severity was assessed by the Penetration Aspiration Scale (PAS), Residue Severity Ratings (Eisenhuber et al., 2002) and the Normalised Residue Ratio Scale (NRRS). Biomechanical swallowing parameters of hyolaryngeal displacement and velocity were also measured.
Directional skin displacements of the lateral neck were moderate to strongly correlated with scores on the PAS (rs=0.5-0.74, p=0.02-0.06), NRRS (rs=0.42-0.51, p=0.01-0.04), and residue severity scores (rs=0.33-0.45, p=0.01-0.04). A relationship between skin displacements and hyolaryngeal movements could not be concluded. Interrater reliability was excellent for hyolaryngeal measures, PAS and residue severity scores (ICC=0.96-1.00).
This is the first study to explore the potential for smartphone technology to indirectly indicate post swallowing residual, aspiration and penetration using image registration methods.
Future studies will focus on including other swallowing parameters associated with penetration-aspiration and residue with the incorporation of surface electromyography to provide insight into muscle activations that may be associated with skin displacements. Utilisation of a smart phone provides translatability to mHealth, remote potential and a greater chance of detecting dysphagia and reducing the risk of negative health impacts.