Wearable ECG Notification Selection by Emergency Level
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Solution Overview
Problem
Existing methods for determining and notifying anomalies from electrocardiogram data using wearable devices do not consider the individual's condition, leading to inappropriate notifications.
Innovation Solution
A method that detects anomalies from electrocardiogram data, determines the level of emergency based on the anomaly, and selects appropriate responses to notify the individual or a third party based on the level of emergency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If notification destination is set in advance based on anomaly degree, then notification can be transmitted automatically, but the notification may not be appropriate for the individual's condition
Solution Approach 1:
The notification system dynamically adjusts the notification destination and content based on real-time analysis of multiple parameters including anomaly degree, individual condition, and circumstances. Instead of static pre-set destinations, the system selects from multiple possible destinations (personal device, family, medical institution) based on current situation, making the notification process adaptive and context-aware.
Solution Approach 2:
The system changes multiple parameters simultaneously to determine appropriate notification: anomaly degree level, individual condition state, circumstance factors, and resulting notification destination selection. By monitoring and responding to changes in these parameters, the system ensures notifications are appropriate to the specific situation rather than using fixed pre-set destinations.
2Productivity
If wearable device measures electrocardiogram continuously, then anomaly detection capability is improved, but the type of electrocardiogram that can be measured is limited
Solution Approach 1:
The notification system is designed to handle multiple types of electrocardiogram data and anomaly degrees through a unified processing framework. The system can process various ECG measurement types from wearable devices and adapt its analysis accordingly, making the system versatile rather than limited to single ECG type.
Solution Approach 2:
The system adjusts its analysis parameters and evaluation criteria based on the type of electrocardiogram data received. Different ECG measurement types trigger different analysis protocols and anomaly detection thresholds, allowing the system to maintain high detection capability across multiple ECG types rather than being restricted to one format.
Data Source
AI summary
A notification apparatus of the present invention includes: a detecting unit that detects a degree of anomaly of a person from electrocardiogram data of the person measured with a wearable device; a determining unit that determines a level of emergency of an anomaly of the person based on the degree of anomaly; a selecting unit that selects, from among response data representing a content of a response to be notified to the person or to a third party set in advance, the response data in accordance with the level of emergency; and a notifying unit that provides a notification corresponding to the selected response data. The notification apparatus of the present invention can support user's decision-making, for example.