This exploratory study confirms that dual-axis accelerometry and nasal airflow signals can be used to discriminate healthy and abnormal swallows from patients with dysphagia. The fact that features from all signal channels contributed discriminatory information suggests that multi-sensor fusion is promising in abnormal swallow detection.
Anthropometric and Demographic Correlates of Dual-Axis Swallowing Accelerometry Signal Characteristics: A Canonical Correlation Analysis
Abstract Swallowing accelerometry has been proposed as a potential minimally invasive tool for collecting assessment information about swallowing. The first step toward using sounds and signals for dysphagia detection involves characterizing the healthy swallow. The purpose of this article is to explore systematic variations in swallowing accelerometry signals that can be attributed to demographic factors (such as participant gender and age) and anthropometric factors (such as weight and height). Data from 50 healthy participants (25 women and 25 men), ranging in age from 18 to 80 years and with approximately equal distribution across four age groups (18-35, 36-50, 51-65, 66 and older) were analyzed. Anthropometric and demographic variables of interest included participant age, gender, weight, height, body fat percent, neck circumference, and mandibular length. Dual-axis (superior-inferior and anterior-posterior) swallowing accelerometry signals were obtained for five saliva and five water swallows per participant. Several swallowing signal characteristics were derived for each swallowing task, including variance, amplitude distribution skewness, amplitude distribution kurtosis, signal memory, total signal energy, peak energy scale, and peak amplitude. Canonical correlation analysis was performed between the anthropometric/demographic variables and swallowing signal characteristics. No significant linear relationships were identified for saliva swallows or for superior-inferior axis accelerometry signals on water swallows. In the anterior-posterior axis, signal amplitude distribution kurtosis and signal memory were significantly correlated with age (r = 0.52, P = 0.047). These findings suggest that swallowing accelerometry signals may have task-specific associations with demographic (but not anthropometric) factors. Given the limited sample size, our results should be interpreted with caution and replication studies with larger sample sizes are warranted.