Neck-worn Sensor System for Automated Swallow Frequency Detection
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Solution Overview
Problem
Current dysphagia screening methods for acute stroke patients lack validity, specificity, and cost-effectiveness, failing to provide an effective tool for early identification, which is crucial for reducing morbidity and mortality.
Innovation Solution
A system comprising a patient interface that adheres to the neck, wirelessly transmitting swallow data to a computing device for analysis, which automatically determines swallow frequency and identifies dysphagia likelihood using sensors and algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If clinical screening protocols are used for dysphagia identification, then early detection is attempted, but the methods lack validity, specificity, and cost-effectiveness
Solution Approach 1:
The patent replaces manual clinical screening protocols with an automated electronic system that uses sensors (accelerometers, microphones) to detect swallow events. This substitution of mechanical/manual assessment with electronic detection improves measurement precision and reliability by providing objective, quantifiable data rather than subjective clinical judgment.
Solution Approach 2:
The patent introduces a computing device as an intermediary between the patient and the clinician. The device processes sensor data, applies algorithms to identify swallow events, and provides automated analysis, thereby mediating the detection process to improve both accuracy and reliability while reducing direct clinician involvement in the measurement itself.
2Extent of automation
If automated sensor-based systems are implemented, then measurement precision and automation are improved, but device complexity increases
Solution Approach 1:
The patent divides the monitoring system into separate functional modules: a patient interface with sensors that collects data, a wireless communication component that transmits data, and a computing device that analyzes data. This segmentation allows each component to be optimized independently and simplifies the overall system architecture by distributing functions across multiple independent units.
Solution Approach 2:
The computing device serves as an intermediary that handles the complex data processing and algorithmic analysis, thereby keeping the patient interface relatively simple. The intermediary processes raw sensor signals into meaningful swallow event detections, isolating the complexity from the patient-facing components.
3Measurement precision
If multiple sensors and algorithms are used to improve detection accuracy, then measurement precision increases, but cost and device complexity increase
Solution Approach 1:
The patent employs sensors with multiple functions: accelerometers detect both swallow events and patient movement, while microphones capture both swallow sounds and ambient noise. The system processes multiple data types (acceleration, acoustic, video) through unified algorithms, allowing a single system architecture to handle various detection modalities without requiring separate dedicated hardware for each function.
Solution Approach 2:
The patent changes the parameters being measured from simple presence/absence detection to multi-dimensional analysis including acceleration magnitude, frequency, direction, acoustic characteristics, and temporal patterns. By analyzing multiple parameters simultaneously, the system achieves higher precision using standard off-the-shelf sensors rather than requiring specialized expensive equipment.
Data Source
AI summary
Patient swallow frequency is automatically determined by collecting patient data, analyzing the patient data to automatically identify swallow events, and automatically calculating the swallow frequency based upon the identified swallow events. In some cases, the patient data is collected by a patient interface that wirelessly transmits the data to a computing device for analysis.