Motion Sensor Breathing Pattern Analysis for Clinical Prediction
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Solution Overview
Problem
Current methods for monitoring chronic diseases are inadequate in detecting early clinical symptoms and predicting physiological events, such as asthma attacks or heart conditions, due to limitations in accurately analyzing breathing and heartbeat patterns without invasive measures.
Innovation Solution
A non-contact monitoring system using motion sensors and electronic signal processing to analyze breathing patterns, identifying double-movement-respiration-cycle events, which indicate the use of accessory muscles and potential respiratory distress, and predicting clinical conditions like elevated heart rate or respiratory distress.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If non-contact measurement methods are used to monitor breathing and heartbeat patterns, then patient comfort and ease of operation are improved, but measurement precision and reliability deteriorate due to inability to directly contact the patient's body
Solution Approach 1:
The patent uses an intermediary substance (such as a sensor pad or contactless sensor array) that mediates between the monitoring system and the patient's body. This intermediary enables non-contact or minimal-contact measurement of breathing and heartbeat patterns while maintaining sufficient measurement precision through the intermediary medium.
Solution Approach 2:
The patent replaces direct mechanical contact-based measurement systems with non-contact measurement systems (such as optical, acoustic, or electromagnetic sensors). This substitution maintains patient comfort while achieving measurement precision through alternative physical principles that do not require direct body contact.
2Reliability
If early detection of clinical symptoms is achieved through advanced monitoring, then preventive treatment effectiveness is improved, but device complexity and cost increase
Solution Approach 1:
The patent segments the monitoring system into multiple independent functional modules (e.g., separate sensors for breathing and heartbeat, distinct processing units for different physiological parameters). This segmentation enables early detection of clinical symptoms through specialized modules while keeping the overall system complexity manageable through modular architecture.
Solution Approach 2:
The patent designs a multi-functional monitoring system that can detect multiple clinical symptoms and physiological parameters using a unified platform. This universality improves early detection reliability across different conditions while avoiding the need for multiple separate devices, thereby controlling overall system complexity.
3Measurement precision
If invasive monitoring measures are used to accurately analyze breathing and heartbeat patterns, then measurement precision is improved, but patient comfort and ease of operation worsen
Solution Approach 1:
The patent substitutes invasive mechanical monitoring systems with non-invasive measurement systems that use optical, acoustic, or electromagnetic fields to analyze breathing and heartbeat patterns. This replacement maintains measurement precision through sophisticated sensor technology while dramatically improving patient comfort by eliminating invasive procedures.
Solution Approach 2:
The patent changes the measurement parameters from direct mechanical contact (pressure, force) to indirect physical field interactions (optical intensity, acoustic frequency, electromagnetic signals). This parameter change enables accurate physiological analysis without invasive contact, improving patient comfort while maintaining measurement precision through the transformed measurement approach.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables early prediction of clinical events, allowing for timely preventive treatment, reducing medication dosage, and lowering mortality and morbidity by detecting subtle changes in breathing and heartbeat patterns without contacting the patient.
Implementation Method 1
a motion sensor configured to sense motion of a patient
Data Source
AI summary
Apparatus and methods are provided for use with a subject who is undergoing respiration. A motion sensor senses motion of a subject. A breathing pattern analysis unit analyzes components of the sensed motion that result from the subject's respiration. The breathing pattern analysis unit includes double-movement-respiration-cycle-pattern-identification functionality that designates respiration cycles as being double-movement-respiration-cycles (DMRC's) by determining that the cycles define two subcycles. Double-movement-respiration-cycle-event-identification functionality of the breathing pattern analysis unit identifies a DMRC event by detecting that the subject has undergone a plurality of DMRC's. An output is generated that is indicative of the subject having used accessory muscles in breathing, in response to identification of the double-movement-respiration-cycle event. Other embodiments are also described.