Wearable Biometric Classification via Sensor Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wearable devices and fitness trackers face challenges in accurately classifying a user's physiological state due to errors and interference from factors like movement and environmental conditions, limiting their ability to detect stress levels, potential illnesses, or injuries during physical activity.
Innovation Solution
A mobile, portable communication system equipped with sensors for biometric data acquisition, a classification module, and internal memory, which processes a combination of biometric and movement data to classify the user's physiological state, using machine learning algorithms to recognize generic states and adjust for external influencing factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors are used to measure biometric data, then physiological state monitoring is enabled, but measurement precision deteriorates due to errors and disturbances from movement and environmental conditions
Solution Approach 1:
The patent combines multiple sensors (pressure sensor for pulse/blood pressure, temperature sensor for body temperature, motion sensor for movement detection) to monitor physiological state. By merging data from multiple sensors, the system compensates for individual sensor errors and disturbances, improving overall measurement precision while maintaining comprehensive monitoring capability
Solution Approach 2:
The system uses motion sensor data to detect movement and provides feedback to adjust or filter biometric measurements accordingly. This feedback mechanism allows the system to compensate for measurement errors caused by movement, maintaining measurement precision during physical activity
2Reliability
If multiple sensors are combined to improve measurement accuracy, then reliability improves, but device complexity increases
Solution Approach 1:
The mobile communication system is designed as a multi-functional device that not only monitors physiological state but also communicates data to healthcare professionals and provides alerts. This universal approach consolidates multiple functions into a single device, managing complexity while improving reliability through integrated sensor fusion and data processing
3Reliability
If real-time processing of biometric data is implemented, then user safety is improved through early detection, but energy consumption increases
Solution Approach 1:
The system implements periodic monitoring and processing of biometric data rather than continuous processing. It periodically evaluates physiological parameters and compares them against threshold values, enabling real-time safety monitoring while reducing energy consumption by processing data at intervals rather than continuously
Data Source
Figure 1
Figure 2
Figure 3a~3b
AI summary
An electronic system for classifying a user's physiological state, the system comprising a mobile, portable communication system (100) which includes at least one sensor for acquiring data (500), a classification module (200), a processor (130), and internal memory (120). The data (500) comprise the user's biometric data. The classification module (200) is trained to recognize a plurality of generic states of a plurality of physiological parameters using training datasets from a user cohort, the classification module (200) being executed by the processor (130) of the communication system (100).The system performs the following steps: • Acquiring the data (500) by the at least one sensor, • Inputting the data (500) into the classification module (200), • Generating a classification result (600) from the data (500) by the classification module (200), • Storing the classification result (600) in the memory (120) of the communication system (100), wherein the classification result (600) comprises a current health profile of the user, the health profile comprising a classification of the user's physiological state with respect to the majority of generic states of the majority of physiological parameters.