Smart Garment with Distributed Sensor Nodes for Kinematic Tracking
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Solution Overview
Problem
Conventional full-body bio-mechanical measurement systems using cameras and rigidly affixed sensors are restrictive, prone to failure when sensors move out of position, and limited in capturing complex movements, making them unsuitable for dynamic environments like athletic maneuvers or field operations.
Innovation Solution
A smart garment with distributed sensors and processor nodes that collect and process real-time data to derive body kinematics and physical state information, allowing for adaptive control of actuators and feedback systems, even if some sensors or processors are lost or displaced.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If rigidly affixed sensors are used, then measurement precision is improved, but device complexity and ease of operation worsen due to restrictive equipment and precise placement requirements
Solution Approach 1:
The system divides the measurement function into multiple distributed sensor nodes embedded throughout the garment, with each node containing its own processor. This segmentation allows the system to maintain measurement precision through distributed sensing while reducing overall device complexity by localizing processing functions at each node rather than requiring a centralized complex system.
Solution Approach 2:
Each sensor node is equipped with its own processor that autonomously processes local sensor data and determines local surface shape information. This self-service capability at each node eliminates the need for complex centralized control and precise manual placement, as each node independently performs its measurement function.
2Measurement precision
If sensors are precisely affixed, then measurement precision is improved, but reliability worsens when sensors move out of position
Solution Approach 1:
The system transitions from static, fixed sensor placement to a dynamic distributed network of sensor nodes embedded in the garment. Each node continuously determines local surface shape and exchanges information with neighbors, allowing the system to adapt to movement and maintain reliability even when individual sensors shift position during athletic maneuvers or field operations.
Solution Approach 2:
The system changes the operational parameter from fixed sensor positions to mobile sensor nodes that continuously update their local surface shape measurements. This parameter change allows the system to maintain measurement accuracy through real-time adaptation rather than relying on precise initial placement, thereby improving reliability during dynamic activities.
3Device complexity
If static camera positions are used, then device complexity is reduced, but adaptability worsens due to limited field of view and restrictions on movements
Solution Approach 1:
The system segments the measurement field into multiple local zones, each monitored by distributed sensor nodes embedded throughout the garment. This segmentation allows the system to capture complex movements and behaviors across the entire body without requiring complex centralized camera systems, thereby maintaining simplicity while improving adaptability to various athletic maneuvers and field operations.
4Adaptability or versatility
If distributed sensors are used, then adaptability and robustness are improved, but device complexity increases due to multiple sensor nodes and data processing requirements
Solution Approach 1:
The system divides the complex processing task into smaller units distributed across multiple sensor nodes, with each node handling local data processing independently. This segmentation reduces the complexity burden on any single component while maintaining the adaptability benefits of distributed sensing throughout the garment.
Solution Approach 2:
Each sensor node performs partial processing of the overall measurement task by determining local surface shape information and exchanging data with neighboring nodes. This distributed partial action approach allows the system to achieve high adaptability through comprehensive coverage while managing device complexity by limiting the processing burden at each individual node.
Data Source
AI summary
A body garment including sensors distributed throughout the garment, each sensor senses body state information from a local surface area of a body; and sensor nodes in proximity to the plurality of sensors, each sensor node including a processor to receive sensing body state information from at least one of the plurality of sensors. Each processor is configured to receive body state information locally from sensors, to utilize the information to determine a local surface shape of the surface of a portion of the body part; and to exchange local surface shape information with neighboring sensor nodes. At least one processor of utilizes the local surface shape information received from the sensor nodes to generate one overall model of a surface shape of the entire surface of the body part covered by the garment.