Method and device for swallowing impairment detection

Abstract

Disclosed herein is a method and apparatus for swallowing impairment detection, whereby cervical accelerometry and nasal airflow data is acquired as a candidate executes one or more swallowing events. Upon feature extraction and classification, vibrational and airflow data acquired in respect of each swallowing event is classified as indicative of one of normal or possibly impaired swallowing. Computer-readable media comprising statements and instructions for implementation by a processing device are also described in facilitating swallowing impairment detection respective to candidate swallowing events.

What is claimed is: 
     
         1 . A device for use in identifying a possible swallowing impairment in a candidate during execution of a swallowing event, the device comprising:
 an accelerometer to be positioned in a region of the candidate's throat and configured to acquire vibrational data representative of the swallowing event;   a nasal airflow monitor to be positioned in a region of the candidate's nostrils and configured to acquire airflow data representative of the swallowing event;   a processing module operatively coupled to said accelerometer and nasal airflow monitor for processing said vibrational data and said airflow data to extract from each one thereof one or more features representative of the swallowing event, and classify said vibrational data and airflow data as indicative of one of normal swallowing and possibly impaired swallowing based on said extracted features.   
     
     
         2 . The device of  claim 1 , the possible swallowing impairment comprising at least one of a swallowing safety impairment and a swallowing efficiency impairment. 
     
     
         3 . The device of  claim 1 , said accelerometer comprising a dual-axis accelerometer configured to acquire axis-specific data, said processing module for processing said axis-specific data to extract from each axis one or more features respective thereto representative of the swallowing event. 
     
     
         4 . The device of  claim 3 , wherein said features extracted from said axis-specific data comprise distinct axis-specific features. 
     
     
         5 . The device of  claim 3 , said dual-axis accelerometer configured for alignment along an anterior-posterior axis (A-P) and a superior-inferior axis (S-I) of the candidate's throat. 
     
     
         6 . The device of  claim 1 , wherein said extracted features comprise at least one vibrational data feature distinct from at least one airflow data feature. 
     
     
         7 . The device of  claim 1 , said processing module configured to classify the swallowing event by comparing said extracted features with preset classification criteria defined by features previously extracted and classified from a known training data set. 
     
     
         8 . The device of  claim 8 , wherein said extracted features are classified as a function of a distance of said extracted features from said classification criteria. 
     
     
         9 . The device of  claim 8 , wherein said extracted features are classified via discriminant analysis using one of Mahalanobis distances and Euclidian distances. 
     
     
         10 . The device of  claim 1 , said processing module comprising a feature extraction module for extracting said one or more features from each of said vibrational data and said airflow data, a feature reduction module for identifying, based on preset feature reduction parameters, predominant components of said extracted features, and a classifier configured to classify said vibrational data and said airflow data based on said extracted features and said predominant components thereof. 
     
     
         11 . The device of  claim 1 , for identifying the possible swallowing impairment during execution of multiple successive swallowing events, said processing module configured to classify vibrational data and airflow data acquired in respect of each of said successive swallowing events as indicative of one of normal swallowing and possibly impaired swallowing. 
     
     
         12 . The device of  claim 11 , further comprising an event segmentation module for automatically segmenting vibrational data and airflow data acquired in respect of each of said successive events for independent processing and classification. 
     
     
         13 . The device of  claim 11 , further comprising a user interface for selectively segmenting vibrational data and airflow data acquired in respect of each of said successive events for independent processing and classification. 
     
     
         14 . The device of  claim 11 , further comprising an output, said processing module further configured to process said vibrational and airflow data acquired in respect of each of said successive events, and output results thereof in accordance with a preset swallowing impairment assessment protocol. 
     
     
         15 . The device of  claim 1 , wherein at least one of said extracted features comprises a value derived from at least one signal wavelet decomposition level. 
     
     
         16 . The device of  claim 15 , wherein said value comprises at least one of an energy and an energy ratio associated with said level, or one or more segments thereof. 
     
     
         17 . A computer readable-medium having statements and instructions stored thereon for implementation by a processor to automatically process input vibrational data and airflow data representative of a candidate swallowing event in identifying a possible swallowing impairment, by:
 extracting one or more preset features representative of the swallowing event for each of the vibrational data and airflow data;   comparing said extracted features with preset classification criteria defined as a function of said preset features; and   outputting, based on said comparing, classification of said vibrational data and airflow data as indicative of one of normal swallowing and possibly impaired swallowing.   
     
     
         18 . The computer readable-medium of  claim 17 , said possibly impaired swallowing comprising one or more of unsafe swallowing and inefficient swallowing. 
     
     
         19 . The computer readable-medium of  claim 17 , said possibly impaired swallowing comprising identification of substantial post-swallow residual material in one or more of valleculae and pyriform sinuses. 
     
     
         20 . The computer readable-medium of  claim 17 , the vibrational data comprising dual-axis accelerometry data representative of the swallowing event, said extracting comprising extracting one or more features for each axis of said axis-specific data. 
     
     
         21 . The computer readable-medium of  claim 17 , said comparing comprising calculating a distance of said extracted features from said classification criteria and selecting a most likely classification as a function of said distance. 
     
     
         22 . The computer readable-medium of  claim 21 , said calculating comprising performing a linear discriminant analysis of said extracted features using at least one of Euclidian and Mahalanobis distances. 
     
     
         23 . The computer readable-medium of  claim 17 , the vibrational data and airflow data representative of successive swallowing events, further comprising statements and instructions for automatically segmenting the vibrational data and airflow data into event-specific data, and repeating said extracting and classifying for each said event-specific data. 
     
     
         24 . A method for identifying a possible swallowing impairment in a candidate via execution of one or more preset swallowing events, comprising:
 recording vibrational data and airflow data representative of the one or more swallowing events;   extracting one or more swallowing-event specific features for each of the vibrational data and airflow data; and   classifying said extracted features as indicative of one of normal swallowing and possibly impaired swallowing.   
     
     
         25 . The method of  claim 24 , comprising, for execution of two or more preset swallowing events, selectively recording said vibrational data and airflow data for each event independently to provide event-specific data, and implementing said extracting and classifying on said event-specific data for each of said events. 
     
     
         26 . The method of  claim 24 , comprising, for execution of two or more preset swallowing events, successively recording said vibrational data and airflow data for each of said events, and further comprising automatically segmenting said successively recorded data to provide event-specific data, and implementing said extracting and classifying on said event-specific data for each of said events. 
     
     
         27 . The method of  claim 24 , the swallowing impairment comprising at least one of penetration, aspiration, unsafe swallowing, inefficient swallowing, and post-swallow residue material in one or more of valleculae and pyriform sinuses.