NeuronUP Labs
Data-driven research lines at NeuronUP Labs
Using a data-driven approach, we seek to uncover patterns and correlations that were previously invisible, enabling more precise and personalized interventions to improve the competencies of our professionals as well as the quality of life of patients.
Data-driven stratification of subtypes in neurological and mental health conditions
Application of big data and machine learning techniques to identify subgroups within heterogeneous conditions, based on multimodal data patterns.
Examples of Studies:
- On cross-sectional and longitudinal cognitive performance data in NeuronUP.
- Predictive analysis of subgroups of chronic fatigue patients using cognitive performance patterns and physiological data.
- Development of clustering algorithms to differentiate subtypes of mild cognitive impairment.
State of the art in generative artificial intelligence for intelligent session design
Implementation of generative AI to adapt and personalize cognitive stimulation sessions, improving efficiency and user experience, and reducing practitioner time.
Examples of studies:
- Evaluation of the effectiveness of AI-generated adaptive sessions in improving specific cognitive skills.
- Development of an AI-based recommendation system to optimize exercise selection based on the user’s performance history.
Multimodal neuropsychological intervention with comprehensive monitoring
Integration of cognitive performance data with psychophysiological variables (such as heart rate variability and eye activity) and signals obtained from wearables, for a holistic understanding of the patient.
Examples of studies:
- Correlational analysis between cognitive task performance metrics and indicators of physiological stress using wearables to measure heart rate variability.
- Evaluation of the impact of personalized neuropsychological interventions based on eye movement and cognitive performance data in different groups of patients.
On-session and off-session monitoring
Fusion of data collected during and outside NeuronUP sessions with wearables, including sleep metrics, to optimize interventions.
Examples of studies:
- Longitudinal study to assess how sleep metrics affect cognitive performance using wearable data.
- Research on the efficacy of personalized cognitive interventions integrating data obtained during and outside NeuronUP sessions.
Funded research projects in which NeuronUP participates
In competitive calls, NeuronUP is participating in different projects collaborating with scientific professionals and first level institutions.
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Access to NeuronUP Labs research tools
Would you like to have access to NeuronUP Labs research tools? Send us your research proposal, our committee will evaluate your project and, once validated, we will provide you with the most innovative tools to develop your research.