Method for Generating Sensor Data of Movement of a Living Organism

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This invention describes a method for generating realistic, well-annotated sensor data that captures the movement of living beings—especially humans. The method involves collecting raw movement data (such as motion capture), creating a digital model of the moving being, and simulating how wave-based sensors (e.g., radar, LiDAR, cameras, ultrasound) would record this movement in virtual environments. The process allows for augmenting, editing, annotating, and diversifying the generated data, which can then be used for training artificial intelligence systems or developing sensor technologies.

Use CasesContent extracted from patent full text and abstract with AI.

• Training AI systems for accurate human motion detection, recognition, and gesture analysis.
• Development and testing of automotive sensors (e.g., for recognizing pedestrians or vulnerable road users).
• Enhancing fall detection and monitoring systems for healthcare and elderly care.
• Diagnostics and therapy support in medicine (e.g., gait analysis, Parkinson's diagnosis, physical rehabilitation).
• Security systems including intrusion detection and body scanners.
• Industrial human-machine interaction and safety monitoring.
• Realistic motion modeling in computer graphics, film special effects, and video games (realistic avatars).
• Augmented and virtual reality applications needing realistic movement datasets.
• Developing, benchmarking, and optimizing sensor configurations or new sensor systems.
• Counting people or tracking movement in public spaces for analytics or safety.

BenefitsContent extracted from patent full text and abstract with AI.

• Ability to generate large, perfectly annotated and diversified datasets, enhancing AI training's quality and generalizability.
• Highly realistic emulation of different sensor types, environments, and configurations without the need for repeated real-world experiments.
• Supports editing and augmentation, enabling the simulation of various scenarios, body types, and movements—including those impossible or unsafe to recreate in reality.
• Facilitates the development and testing of sensor systems using "hardware- and software-in-the-loop" methods.
• Improves safety and diagnostics in medical and industrial contexts through precise, repeatable, and customizable motion data.
• Enables separate annotation and simulation of individual body parts or motion components, advancing both AI training and sensor signal analysis.
• Cost and time savings compared to collecting extensive real-world sensor data.
• Enables consideration of physical impossibilities and edge cases, helping improve system robustness.

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Patent Abstract

The invention relates to a method for generating sensor data for the movement of a living being, in particular a human being, having the following steps: - providing raw data for the movement of the living being; - generating a model of the living being from the raw data; and - simulating the detection of the movement of the living being by means of a wave-based detection means using the model and/or the raw data and a simulated detection means in a simulated environment, wherein a process of generating sensor data for the movement is carried out.