Smartwatch Shoulder Proprioceptive Analysis
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Solution Overview
Problem
Current methods for assessing and quantifying shoulder joint motion are qualitative and lack precision, making it difficult to measure and characterize shoulder functionality, especially in rehabilitation and surgical contexts, and existing wearable technologies struggle to accurately track range of motion in ball and socket joints like the shoulder.
Innovation Solution
A system and method utilizing a smartwatch with inertial sensors to continuously monitor and quantify shoulder movements, processing data through hardware processors to extract feature parameters and apply a rule-based engine algorithm for classification and performance scoring, including normalization, peak detection, and angle estimation to determine range of motion and motion types like flexion, extension, and abduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If qualitative approach with goniometry and visual estimation is used for shoulder assessment, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent replaces manual goniometry and visual estimation with an automated wearable sensor system that uses inertial measurement units (IMUs) to objectively measure shoulder range of motion. The system captures motion data through accelerometers and gyroscopes, processing signals to determine joint angles and movement characteristics without requiring manual goniometric measurement techniques.
Solution Approach 2:
The wearable sensor system enables self-service measurement by continuously monitoring shoulder motion during natural activities without requiring clinician intervention for each measurement. The system autonomously captures, processes, and analyzes motion data, providing objective measurements that reflect actual functional performance during daily tasks.
2Measurement precision
If automated portable wireless sensor system is used to measure range of motion, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The wearable sensor system is designed with multi-functionality to measure range of motion across multiple joints and movement planes using a single integrated platform. The system can assess shoulder, elbow, wrist, hip, knee, and ankle joints simultaneously, providing comprehensive motion analysis without requiring separate specialized devices for each joint.
Solution Approach 2:
The system processes sensor data by transforming raw signals into meaningful motion parameters through signal processing algorithms. It converts accelerometer and gyroscope readings into joint angles, velocities, and range of motion measurements, changing the parameter representation from raw sensor data to clinically relevant motion characteristics.
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
Provides objective and accurate measurements of shoulder joint motion, enhancing clinical assessments and rehabilitation protocols by offering precise range of motion analysis and performance metrics, improving the management of shoulder-related conditions and surgical outcomes.
Implementation Method 1
utilizing a smartwatch with inertial sensors to continuously monitor and quantify shoulder movements
Data Source
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AI summary
This disclosure relates generally to a system and method for shoulder proprioceptive analysis of the person. The present disclosure monitors the shoulder joint motion by quantitative measure of range of motion (ROM,) and kinesthesia of shoulder using a smart watch, thereby assessing the limit of active motion and the ability to passively reposition the arm in space. The present disclosure estimates the ROM, velocity, quality of joint movement, direction of hand movement using the sensor data captured by the smart watch. Further, the present disclosure provides a performance metrics of the shoulder function by comparing the shoulder motion before and after a prosthesis procedure. The present disclosure implements a rule engine-based approach classifying the shoulder/arm movement which includes flexion, extension, abduction, and adduction, internal and external rotation.