Pulse Transit Time Monitoring for Fall Risk Prediction
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Solution Overview
Problem
Current medical devices lack an effective method to predict the likelihood of a patient falling based on cardiovascular metrics, particularly during transitions like sitting to standing, which can indicate changes in blood pressure and stability.
Innovation Solution
A medical system that monitors pulse transit time (PTT) before and after a Sit-to-Stand transition, using implanted or external devices to calculate differences and compare them to baseline values, determining the likelihood of falling and facilitating adjustments in treatment through remote communication for medical intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If PTT is measured during Sit-to-Stand transition to predict falling likelihood, then patient safety and treatment guidance are improved, but device complexity and measurement requirements increase
Solution Approach 1:
The IMD is designed to perform multiple functions: traditional cardiac monitoring and therapy delivery, plus the new function of measuring PTT during Sit-to-Stand transitions to predict falling risk. This multi-functionality allows the same device to provide both cardiac care and fall prevention guidance without requiring separate specialized equipment.
Solution Approach 2:
The system utilizes the patient's own physiological signals (ECG-based PTT measurements) already captured during routine cardiac monitoring to assess falling risk. The IMD automatically detects Sit-to-Stand transitions and performs PTT measurements without requiring external equipment or additional patient actions beyond normal daily activities.
2Measurement precision
If PTT measurements are taken during Sit-to-Stand transition to assess blood pressure changes, then measurement precision for stability assessment is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The system performs preliminary detection of Sit-to-Stand transitions using accelerometer data before initiating PTT measurements. This preliminary action ensures that the device is ready to capture PTT data at the optimal moment during the transition when blood pressure changes are most pronounced, improving measurement precision while automating the detection process to reduce complexity.
Solution Approach 2:
The system continuously monitors PTT measurements during Sit-to-Stand transitions and provides feedback about falling risk to clinicians and patients. This feedback loop allows for real-time assessment of blood pressure changes and enables timely interventions, while the automated nature of the feedback system reduces the manual measurement burden.
Data Source
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AI summary
An example medical device system and method includes accelerometer circuitry configured to generate at least one signal, a memory, and processing circuitry coupled to the accelerometer circuitry and the memory. The processing circuitry is configured to determine a first plurality of pulse transit times (PTTs), determine, based on the at least one accelerometer signal, a Sit-to-Stand transition, determine, based on the Sit-to-Stand transition occurring, a second plurality of PTTs after the Sit-to-Stand transition, and determine a likelihood that a person, such as a patient, may fall based on the first plurality of PTTs and the second plurality of PTTs.