Event Prediction System Using Body Movement Data Analysis
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Solution Overview
Problem
Existing sensor systems, such as those described in JP 2017-484, are primarily designed for air conditioning control and health monitoring, lacking the capability to predict events related to a subject's condition, such as illness or injury, beyond current health assessments.
Innovation Solution
An event prediction system that includes an acquisition unit for body movement data and a symptom detection unit, which analyzes past data to predict the onset of specific events like illness or injury, utilizing acceleration calculation and presence detection to identify changes in behavior and movement patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an activity sensor is designed for air conditioning control and current health monitoring, then air conditioning control and basic health assessment are achieved, but the capability to predict future events related to subject's condition is lacking
Solution Approach 1:
The activity sensor is enhanced to perform multiple functions: it continues to provide air conditioning control and current health monitoring while adding event prediction capability. The sensor system integrates diverse analysis functions that process body movement data to detect current activity levels and predict future health events, making a single device serve multiple purposes without requiring separate specialized equipment
2Reliability
If body movement data is analyzed using only current activity volume, then air conditioning control is effective, but early detection of event symptoms before they occur is not possible
Solution Approach 1:
The system performs preliminary analysis of body movement data by examining historical patterns and trends before actual events occur. It detects subtle changes in movement characteristics over time and uses these preliminary findings to predict potential health events, enabling early intervention before symptoms fully manifest
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor body movement data, compare it against historical patterns, and adjust predictions based on detected trends. The analysis unit uses feedback from ongoing measurements to refine event prediction accuracy, creating a closed-loop system that improves detection capability over time
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
Enables early detection of event symptoms, allowing for proactive care and intervention before the event occurs, improving monitoring and care management in environments like nursing facilities.
Implementation Method 1
a Doppler sensor (measuring unit), a distance sensor, and a processor. The processor calculates the volume of activity of a subject, falling within the sensing range of the sensor (air-conditioned space), based on the amplitude and/or frequency of a detection signal of the Doppler sensor
Data Source
AI summary
An event prediction system according to an aspect includes an acquisition unit and a symptom detection unit. The acquisition unit acquires body movement data about a subject's body movement from a measuring device that outputs the body movement data. The symptom detection unit makes, based on a subset, acquired during a past reference period, of the body movement data, a decision about whether or not there are any symptoms of an onset of a particular event related to the subject.