Motion-Sensor Seizure Detection for Closed-Loop Vagus Nerve Stimulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Epileptic seizures often occur with little warning, leading to undesirable sequelae, and existing vagus nerve stimulation methods are either open-loop or require user intervention, lacking true closed-loop automation for timely seizure mitigation.
Innovation Solution
A system with a motion sensor and processing circuit determines heart rate and uses a subject-specific classifier to detect imminent seizures, applying closed-loop vagus nerve stimulation automatically based on calculated heart rate and respiration patterns, employing machine-learning algorithms and parametric models to personalize seizure detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If open-loop vagus nerve stimulation is used, then the device is simple to operate, but it cannot provide timely seizure mitigation
Solution Approach 1:
The patent implements closed-loop feedback by continuously monitoring heart rate and respiration rate via motion sensors, comparing these measurements against subject-specific thresholds, and automatically triggering vagus nerve stimulation when seizure indicators are detected. This feedback mechanism transforms the open-loop system into a responsive closed-loop system that provides timely seizure mitigation while maintaining operational simplicity through automated decision-making algorithms.
2Extent of automation
If user intervention is required for vagus nerve stimulation, then the system is easier to manufacture, but it lacks true closed-loop automation
Solution Approach 1:
The system employs self-service automation by enabling subjects to programmatically configure their own seizure detection thresholds and stimulation parameters using mobile applications. This self-programming capability allows the system to adapt to individual seizure patterns without requiring complex factory programming or manual clinical configuration, thereby achieving high automation levels while maintaining ease of manufacture through standardized hardware platforms.
3Measurement precision
If subject-specific classification is implemented, then seizure detection accuracy is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary action by pre-programming subject-specific seizure detection thresholds and classification parameters before deployment. During operation, the system simply compares real-time sensor measurements against these pre-established criteria using straightforward comparison logic rather than complex real-time classification algorithms. This approach achieves high detection accuracy through personalized thresholds while maintaining computational simplicity and low device complexity.
Data Source
AI summary
A system and method for seizure detection and vagus nerve stimulation. In some embodiments, a system includes a motion sensor configured to be secured to a subject, and a processing circuit. The processing circuit may be configure to determine a calculated heart rate of the subject based on a signal from the motion sensor, and to determine whether a seizure is imminent or occurring, based on the calculated heart rate and on a subject-specific classifier.