Effective Mobility Scoring via Acceleration Data Analysis
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Solution Overview
Problem
Current pain measurement techniques rely on subjective self-reporting, which is inaccurate and fails to capture the dynamics of day-to-day pain intensity, making it challenging to assess chronic pain effectively in patients.
Innovation Solution
A system that uses acceleration data from wearable sensors to objectively calculate an effective mobility score, which is then used to quantify pain intensity by determining the weighted sum of time spent in various activity states, providing an objective and passive measurement of pain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If subjective self-reporting is used for pain measurement, then the measurement process is simple and easy to implement, but the accuracy and objectivity of pain assessment deteriorates
Solution Approach 1:
The patent replaces the subjective psychological reporting mechanism with an objective physical measurement system using accelerometers and gyroscopes to capture movement data. This substitution transforms pain assessment from a subjective self-report to an objective biomechanical measurement, resolving the contradiction between ease of operation and measurement precision.
Solution Approach 2:
The patent introduces movement data as an intermediary variable that indirectly reflects pain intensity. Instead of directly measuring the subjective sensation of pain, the system uses accelerometry and gyroscopy data as a mediator to infer pain levels, achieving objective measurement while maintaining operational simplicity.
2Loss of time
If subjective self-reporting is used for pain measurement, then the measurement process is quick and simple, but the ability to capture dynamics of day-to-day pain intensity deteriorates
Solution Approach 1:
The patent implements continuous passive monitoring of movement data over extended periods, capturing the dynamic nature of pain throughout daily activities. The system continuously collects accelerometry and gyroscopy data without interrupting the patient's normal routine, enabling reliable detection of pain fluctuations over time while minimizing time loss.
Solution Approach 2:
The system performs automatic analysis of movement data without requiring active patient participation or time investment. The wearable device and processing system autonomously capture, analyze, and interpret movement patterns to assess pain dynamics, eliminating the time burden on patients while maintaining measurement reliability.
3Measurement precision
If objective measurement using acceleration data is implemented, then the accuracy and objectivity of pain assessment is improved, but the device complexity and processing requirements increase
Solution Approach 1:
The patent utilizes accelerometers and gyroscopes that are already standard components in common wearable devices like smartphones and smartwatches. By leveraging these existing multi-functional sensors, the system achieves objective pain measurement without requiring specialized or complex hardware, thus improving measurement precision while minimizing device complexity.
Solution Approach 2:
The system processes and analyzes movement data patterns that replicate the information content of subjective pain reporting. By creating an objective copy of pain assessment through biomechanical data analysis, the system achieves high measurement precision using standard sensor technologies rather than complex specialized equipment.
4Reliability
If continuous monitoring of activity states is performed, then the capture of pain dynamics is improved, but the data processing load and computational requirements increase
Solution Approach 1:
The patent applies selective processing where only specific movement patterns and activity states relevant to pain assessment are analyzed in detail. The system identifies and focuses computational resources on critical transitions between activity states that indicate pain changes, rather than processing all raw data uniformly, thus improving reliability while reducing energy consumption.
Solution Approach 2:
The continuous monitoring data is segmented into discrete activity states and time windows for analysis. By dividing the continuous stream of accelerometry and gyroscopy data into manageable segments representing distinct activity states, the system efficiently captures pain dynamics while reducing overall computational energy requirements through localized processing.
Data Source
AI summary
A method, computer system, and a computer program product for effective mobility scoring is provided. The present invention may include receiving an acceleration data associated with a user. The present invention may also include determining a respective activity state of a plurality of activity states for the user based on the received acceleration data. The present invention may also include recording an amount of time spent in a respective activity state of a plurality of activity states. The present invention may further include determining an effective mobility score of the user for a specified time-window based on calculating a weighted sum of time spent in the plurality of activity states.