Ambient Intelligence for Understanding Neuropsychiatric Symptoms (AmI-NPS)

Ambient intelligence (AmI) represents the future vision of intelligent computing where explicit input and output devices will not be required; instead sensors and processors will be embedded into everyday devices and the environment will adapt to the user’s needs and desires seamlessly.

In this project, we develop automated artificial intelligence (AI) and AmI methods to detect and track an individual’s neuropsychiatric symptoms (NPS) using non-intrusive privacy-preserving ambient sensors at home. Our software will document the sequence of occurrences of NPS, predict adverse events and provide interpretable data for accurate diagnosis during a clinic visit.

References

[1] Ehsan Adeli: Automatic Assessment of Neuropsychiatric Symptoms at Home Predictive of Mental Health and Cognitive Disorders Using Non-Intrusive Ambient Intelligence Technologies, Department of Psychiatry and Behavioral Sciences, Stanford University