Causal AI framework for neuro/bio product insights
An innovative three-layer framework utilizing causal AI and controlled stimuli to decode neuro/bio signals for product and packaging insights. This solution enhances the interpretability and value of neuro/bio data in consumer research.
Overview
This solution leverages a three-layer causal AI framework to transform neuro/bio signals into actionable insights for product and packaging development. By using controlled stimulus generation, this approach isolates and manipulates specific design cues, allowing for precise causal identification of consumer responses. The framework captures neuro/bio signals through EEG, fNIRS, and biomarkers, enabling the estimation of which design elements trigger specific implicit responses and how these responses correlate with consumer preferences and perceived value.
Technical specifications
Key features:
- Controlled Stimulus Generation: Utilizes generative AI to manipulate product or packaging cues such as color, material, and text while maintaining other variables constant.
- Signal Capture: Employs EEG, fNIRS, and biomarkers to record responses, either in partnership with client facilities or other measurement partners.
- Causal Decoding: Machine learning algorithms estimate the causal links between design cues and neuro/bio responses, identifying consumer segments with the strongest reactions.
Technology readiness level
This technology is currently at TRL 3, indicating that it has been validated in a laboratory setting. The next phases of development include proof of concept and further validation across diverse consumer populations and product categories.
About Temple University
Temple University is a comprehensive public research university serving a large, diverse student body and anchored in Philadelphia. Industry engagement is enabled by co-located research facilities across its main and health sciences campuses and direct integration with a major hospital system that supports clinical research and trials. Companies access shared instrumentation cores, sponsored research agreements, and flexible IP pathways to accelerate product development. Research is supported by competitive federal funding, including sustained awards from NIH and NSF, together with state and philanthropic sources. A dedicated technology transfer office advances IP protection, licensing, startup formation, and corporate matchmaking.
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