On-body UWB and IMU Sensor System for Gesture Recognition
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Solution Overview
Problem
Conventional gesture recognition systems face limitations due to the position of the user within the camera's field of view and require expensive equipment with slow data processing rates, making them inefficient for real-time visual body signal classification, especially in noisy environments.
Innovation Solution
A system using ultrawide-band (UWB) communication devices and inertial measurement units (IMUs) to capture distance measurements and body orientation, which are then processed using machine learning algorithms to classify visual body signals, enabling real-time and accurate recognition of gestures in various environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional visual detection systems using camera images are employed, then gesture recognition can be achieved, but the system performance is limited by user position within camera field of view and requires expensive equipment with slow data processing rates
Solution Approach 1:
The patent replaces the mechanical/optical camera-based visual detection system with a wireless sensor system using UWB transceivers and IMUs. This substitution eliminates the need for complex camera equipment and centralized processing, achieving more accurate and real-time gesture recognition through distributed on-body sensors that directly measure distance and orientation changes.
Solution Approach 2:
The patent introduces wireless communication (UWB) as an intermediary to transmit sensor data from multiple on-body devices to an external listener. This intermediary enables real-time data collection and processing without requiring expensive camera equipment, solving the contradiction between measurement precision and device complexity.
2Productivity
If visual detection systems are used, then body signals can be recognized, but the data processing rate is slow and cannot achieve real-time classification
Solution Approach 1:
The patent performs preliminary actions by continuously collecting and pre-processing sensor data from multiple on-body devices in real-time. The system maintains a continuous stream of distance and orientation measurements, ready for immediate classification when a gesture occurs, thereby achieving high processing rates and minimal response time.
Solution Approach 2:
The replacement of camera-based visual processing with wireless sensor data processing enables real-time classification. The sensor system generates data at higher rates with lower processing requirements, eliminating the slow processing bottleneck inherent in conventional visual systems.
3Measurement precision
If on-body UWB sensors are used to capture distance measurements, then accurate pose determination can be achieved, but energy consumption increases
Solution Approach 1:
The patent implements periodic measurement cycles where UWB sensors transmit and receive distance measurements at optimized intervals. Instead of continuous operation, sensors perform measurements periodically, reducing energy consumption while maintaining sufficient measurement accuracy for gesture recognition through the accumulated time-series data.
Solution Approach 2:
The system uses a moderate number of sensors (six UWB transceivers) placed at key body locations rather than comprehensive coverage. This partial sensing approach achieves sufficient measurement precision for pose determination while limiting energy consumption by avoiding excessive sensor deployment.
4Reliability
If multiple on-body sensors are deployed to capture comprehensive body signals, then gesture classification accuracy improves, but system complexity and data processing burden increase
Solution Approach 1:
The patent segments the gesture recognition system into multiple independent on-body sensor units, each capturing local distance and orientation data. This segmentation distributes the sensing function across several simple devices rather than requiring one complex centralized system, improving reliability through redundancy while managing complexity through modular design.
Solution Approach 2:
The patent employs multi-functional sensor nodes that simultaneously perform distance measurement (UWB), orientation sensing (IMU), and data transmission (wireless communication). This universality reduces overall system complexity by consolidating multiple functions into single sensor units, achieving reliable gesture classification without proportional increases in system complexity.
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
The system provides accurate and efficient classification of visual body signals, overcoming the limitations of conventional systems by using low-energy UWB communication and IMU data to determine pose and gestures, suitable for applications in sports, construction, and transportation.
Implementation Method 1
The communication, e.g., as ultrawide-band (UWB), may include time-of-flight (TOF) or other timing-associated information from which distance measurements can be derived.
Implementation Method 2
The exemplary system and method may employ a number of wireless distance measurement sensors (e.g., 6 sensors), e.g., configured with ultrawide-band (UWB) transceivers, and additionally configured with inertial sensors to measure body location signals and finger location signals.
Data Source
AI summary
An exemplary system and method are disclosed for capturing visual body signals using distance measurements among different parts of the body and for providing classification for them. The exemplary system and method can be employed to generate the classification and provide a second source of communication of the classification to supplement the visual cues provided by such body motion or positioning.