Wearable Biometric Monitoring with Anomaly Detection
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Solution Overview
Problem
Current medical monitoring systems are bulky, costly, and limited in their ability to provide ongoing, real-time monitoring of multiple biometric variables, especially for patients in non-hospital settings, and consumer devices lack the reliability and quality standards of professional equipment.
Innovation Solution
A system and method for dynamic biometric detection and response that includes a wearable device with sensors for heart rate, blood pressure, blood oxygen, and glucose monitoring, using GPS and IMU to track location and motion, and advanced machine-learning algorithms to detect anomalies and generate alerts, enabling real-time remote health screening and monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If professional hospital equipment is used for medical monitoring, then measurement precision and reliability are improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent combines multiple biometric sensors (heart rate, blood pressure, blood glucose, temperature) into a single wearable device that also includes GPS and IMU capabilities. This integration allows professional-grade monitoring functions to be consolidated into one unit, reducing the need for multiple separate equipment pieces while maintaining measurement precision.
Solution Approach 2:
The wearable device performs multiple functions including biometric monitoring, location tracking, motion sensing, and anomaly detection. By making the device universal and multi-functional, it replaces several specialized hospital equipment pieces, thereby reducing overall device complexity and infrastructure requirements while maintaining professional monitoring capabilities.
2Reliability
If professional monitoring equipment is deployed, then reliability of medical data is improved, but ease of operation and accessibility worsen
Solution Approach 1:
The system automatically collects biometric data without requiring manual intervention from medical staff. Sensors continuously monitor vital signs, GPS tracks location, and IMU detects motion, with data automatically transmitted and analyzed. This self-service capability eliminates the need for trained operators to manually operate complex equipment, making the system accessible to patients in non-hospital settings.
Solution Approach 2:
The patent replaces manual mechanical monitoring systems with automated electronic sensors and wireless communication. The wearable device automatically measures biometric parameters and transmits data via wireless communication, eliminating the need for physical connection and manual data collection, thereby improving ease of operation while maintaining reliability.
3Measurement precision
If multiple biometric variables are monitored simultaneously, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent integrates multiple biometric sensors (heart rate, blood pressure, blood glucose, temperature) into a single wearable device that also includes GPS and IMU capabilities. This integration allows professional-grade monitoring functions to be consolidated into one unit, reducing the need for multiple separate equipment pieces while maintaining measurement precision.
4Measurement precision
If continuous real-time monitoring is implemented, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system performs continuous monitoring of biometric parameters but transmits data periodically or event-driven rather than continuously. The processor analyzes data locally and only communicates when anomalies are detected or at scheduled intervals, reducing energy consumption while maintaining real-time monitoring precision through continuous sensing.
Solution Approach 2:
The system continuously monitors biometric data and provides immediate feedback when anomalies are detected. The processor compares real-time measurements against established thresholds and triggers alerts or notifications only when necessary, allowing continuous monitoring with reduced energy consumption by avoiding constant data transmission and processing of normal readings.
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
This solution provides accurate, real-time remote health monitoring, recognizes harmful drug side-effects, and reduces healthcare costs by enabling continuous, multi-variable biometric tracking in a wearable and user-friendly format, enhancing patient care and reducing the need for extensive medical infrastructure.
Implementation Method 1
The processor may be able to sense one or more satellite signals within the GPS; detect the travel time of the signal; calculate the distance between the processor and at least one satellite; and calculate the user location based upon this distance
Implementation Method 2
retrieving the user's blood oxygen level from a pulse oximeter blood oxygen sensor
Implementation Method 3
retrieving the user's pulse from an optical heart sensor
Data Source
AI summary
Systems and methods of dynamic biometric detection and response are provided for the purpose of establishing baseline health status while conveying real-time drug prescription usages and reactions from baseline data. The dynamic monitoring system may be embedded within a wristband, ring, vest, and/or waistband in wireless communication with a computing device or server. Each wearable device may employ interchangeable and embedded sensors to detect inertia movements; 360-imaging fall detections; and a variety of body-emitting vital signs. The system may include a processor operable to sense user location, motion, activity, and biomarkers for the purpose of detecting the user's behavior pattern, wherein an enhanced machine-learning algorithm is used to identify repetitive actions within the user's behavior pattern; and, based upon this pattern, the system is able to detect one or more anomalies for the purpose of generating an anomaly alert for third party notification and quantitative analysis at a server.