Motion Capture Sensor System with Multi-Range Accelerometer Fusion

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Solution Overview

Problem

Existing motion capture systems are limited by accuracy, power usage, limited functionality, and communication capabilities, and are not adaptable for use with multiple pieces of equipment or clothing, lacking integration with mobile devices for data mining and remote monitoring applications.

Innovation Solution

A wireless motion capture sensor system that captures orientation, position, velocity, acceleration, proximity, and strain data, with customizable sensor personalities for specific equipment or clothing, enabling advanced calibration, power efficiency, and communication protocols for local or remote data transfer, and integrating with mobile devices for data mining and remote monitoring.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a single accelerometer is used for motion capture, then device simplicity is maintained, but measurement accuracy and reliability are limited due to restricted measurement range

Engineering Contradiction:
Improveacceleration measurement accuracyVSAvoidsensor system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent combines multiple accelerometers with different measurement ranges into a single sensor system. A first accelerometer with a first measurement range and a second accelerometer with a second measurement range are integrated to measure acceleration across a combined, extended range. The system fuses data from both sensors to achieve high accuracy throughout the full measurement range, resolving the contradiction between measurement precision and device complexity by merging multiple sensing elements into a unified system.

Inventive Principle:
Principle #5Merging (Combining)

2Adaptability or versatility

If multiple sensors with different measurement ranges are combined, then measurement accuracy and extended range are improved, but device complexity increases

Engineering Contradiction:
Improvemeasurement range coverageVSAvoidsensor integration complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent creates a universal sensor system that can handle multiple measurement ranges and types of motion through a single integrated platform. The system incorporates both a first accelerometer for lower-range measurements and a second accelerometer for higher-range measurements, allowing the same device to accurately capture diverse motion patterns from subtle movements to extreme accelerations. This multi-functional design enables the sensor system to adapt to various application requirements without requiring separate dedicated sensors.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent introduces a processor as an intermediary element that receives and fuses data from multiple accelerometers. The processor coordinates the outputs of the first and second accelerometers, combining their measurements into a unified acceleration profile. This intermediary component manages the complexity of integrating multiple sensors with different characteristics, handling data fusion, calibration, and coordination to produce accurate measurements across the extended measurement range.

Inventive Principle:
Principle #24Intermediary (Mediator)

3Measurement precision

If high sampling rates are used for accurate motion capture, then measurement precision is improved, but power consumption increases

Engineering Contradiction:
Improvemotion data accuracyVSAvoidsensor power consumption
Core Design Contradiction:
Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent implements dynamic sampling strategies where the sampling rate is adjusted based on the actual motion characteristics being captured. During periods of high acceleration or rapid motion changes, the system increases sampling rates to maintain measurement precision. During periods of low or steady-state motion, the system reduces sampling rates to conserve power. This dynamic adaptation allows the sensor system to maintain high measurement accuracy when needed while significantly reducing power consumption during normal operation.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The patent changes operational parameters such as sampling rate and measurement range based on detected motion conditions. The system monitors acceleration levels and adjusts its measurement parameters accordingly - using high sampling rates and extended measurement ranges only when significant motion is detected, and switching to lower power modes during periods of minimal activity. This parameter adaptation resolves the contradiction between measurement precision and power consumption by optimizing the balance between these competing requirements in real-time.

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP3513356B1Motion capture system that combines sensors with different measurement ranges
Publication Date: 2023.04.26 BLAST MOTION INC
  • EP3513356B1 patent drawingFigure 1
  • EP3513356B1 patent drawingFigure 1A
  • EP3513356B1 patent drawingFigure 1B

AI summary

Motion capture system with a motion capture element that uses two or more sensors to measure a single physical quantity, for example to obtain both wide measurement range and high measurement precision. For example, a system may combine a low-range, high precision accelerometer having a range of -24g to +24g with a high-range accelerometer having a range of -400g to +400g. Data from the multiple sensors is transmitted to a computer that combines the individual sensor estimates into a single estimate for the physical quantity. Various methods may be used to combine individual estimates into a combined estimate, including for example weighting individual estimates by the inverse of the measurement variance of each sensor. Data may be extrapolated beyond the measurement range of a low-range sensor, using polynomial curves for example, and combined with data from a high-range sensor to form a combined estimate.