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MINDWATCH PUBLICATIONS Media Attention Software Education & Outreach

Project Overview

Smartwatch-like wearables have enabled seamless tracking of vital signs and physical activities, but still lack a significant feature: they are currently unable to provide any information about brain states or to modulate brain function for optimizing human health and performance. This project aims to make it possible for wearables to feature such capabilities. Being aware of brain states is not only extremely valuable in clinical studies but is also crucial to improving human performance in various everyday life activities. While recording neural signals directly from the scalp region is possible, it is impractical for use in everyday life. In order to fill this gap, the goal of this project is to pioneer a closed-loop brain-aware wearable architecture called MINDWATCH. This enables (1) decoding multidimensional brain states from noninvasive wearable devices and (2) applying corrective control. MINDWATCH will transform healthcare delivery (e.g., aging, autism, dementia) as well as human performance and productivity enhancement (e.g., online learning, smart workplaces). For instance, knowledge of mental health and cognitive engagement can enable detecting if a student is depressed or is not cognitively engaged/learning, which makes it possible to take corrective action early on.

This project seeks to overcome the barriers to achieving brain-aware wearables by pioneering a transformative system-theoretic computational toolset for noninvasive closed-loop wearable architectures that monitor and modulate brain function without needing neural recordings. The proposed framework will (1) infer discrete brain-related events in real-world settings, (2) decode multidimensional latent neurobehavioral states based on inferred brain activity, and (3) apply robust adaptive control to maintain the neurobehavioral states within desired ranges. The closed-loop framework will be rigorously validated using experiments on interactive human-technology environments and mental health.

MINDWATCH Publication

Journal Papers [9 ],

Full-Length Conference Papers [4 ],

E- Books [1].

– E-Books:

[1] McConnell, G.C., Santaniello, S., Gale, J.T., Faghih, R.T., Kemere, C., Han, M., Hilliard, J.D.,“Towards the Next Generation of Deep Brain Stimulation Therapies: Technological Advancements, Computational Methods, and New Targets“, Frontiers in Neuroscience, 2021.

– Journal Articles:

[1] Wickramasuriya, D.S., and Faghih R.T., “A Mixed Filter Algorithm for Sympathetic Arousal Tracking from Skin Conductance and Heart Rate Measurements in Pavlovian Fear Conditioning,” PLOS ONE, 2020.

[2] Pednekar D, Amin M.R., Fekri Azgomi H, Aschbacher K, J. Crofford L, and Faghih R.T., “Characterization of Cortisol Dysregulation in Fibromyalgia and Chronic Fatigue Syndromes: A State-Space Approach” IEEE Transactions on Biomedical Engineering, 2020. (supplementary info)

[3] Genty J. X., Amin M.R., Shaw N. D., Klerman E. B., and Faghih R.T., “Sparse Deconvolution of Pulsatile Growth Hormone Secretion in Children,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021. (Supplementary Info)

[4] Amin, M.R. and Faghih, R.T., 2020. “Identification of Sympathetic Nervous System Activation from Skin Conductance: A Sparse Decomposition Approach with Physiological Priors“. IEEE Transactions on Biomedical Engineering, 2020. (Supplementary Info)

[5] Wickramasuriya D.S., and Faghih R.T., “A Marked Point Process Filtering Approach for Tracking Sympathetic Arousal from Skin Conductance” IEEE Access, 2020.

[6] Casile A, Faghih R.T., Brown E. N., “Robust point-process Granger causality analysis in presence of exogenous temporal modulations and trial-by-trial variability in spike trains,” PLoS computational biology, 2021.

[7] Fekri Azgomi H, Cajgas I, and Faghih R.T., “Closed-Loop Cognitive Stress Regulation Using Fuzzy Control in Wearable-Machine Interface Architectures,” IEEE Access, 2021.

[8] Fekri Azgomi H, Hahn J-O, and Faghih R.T., “Closed-Loop Fuzzy Energy Regulation in Patients With Hypercortisolism via Inhibitory and Excitatory Intermittent Actuation,” Frontiers in Neuroscience,2021. (Supplementary Info)

[9] Steel A. G, Parekh S, Fekri Azgomi H, Badri Ahmadi M, Craik A, Pati S, Francis J. T.Contreras-Vidal J.L., and Faghih R.T., “A Mixed Filtering Approach for Real-Time Seizure State Tracking Using Multi-Channel Electroencephalography Data” IEEE Transactions on Neural Systems and Rehabilitation Engineering 2021.(Supplementary Info)

– Conference Proceedings:

[1] Seet M. S., Amin M. R., Abbasi N. I., Hamano J., Bezerianos A., Faghih R.T., Thakor N. V., Dragomir A., “Olfactory-induced Positive Affect and Autonomous Response as a Function of Hedonic and Intensity Attributes of Fragrances,” The Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2020.

[2] Amin, M.R, Tahir, M., and Faghih, R.T.,”An Investigation of music impacts on cognitive Performance and Arousal in the presence of Yerkes-Dodson Law.”The Annual International Conference of the IEEE Engineering in Medicine and Biology Society,2021.

[3] Yaghmour, A., Amin, M.R, and Faghih, R.T., “Decoding a Music-Modulated Cognitive Arousal State using Electrodermal Activity and Functional Near-infrared Spectroscopy Measurements.”The Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2021.

[4] Khazaei, S., Amin, M.R, and Faghih, R.T., “Decoding a Neurofeedback-Modulated Cognitive Arousal State to Investigate Performance Regulation by the Yerkes-Dodson Law.”The Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2021

Selected Media Attention

Paper from CML outlines new Approach for Management of Cushing’s disease

New Smartwatch Technology Uses Sweat on Skin to Infer Brain Stress

ECE students Fekri Azgomi, Amin among 21 students presenting at national meeting

New research method from Faghih, Amin allows more reliable brain information inference using electrodermal activity

Faghih tabbed for 2020-21 Interstellar Initiative

Computational Medicine Lab’s Research Featured by IEEE Xplore

UH’s Faghih Named an MIT Technology Review 2020 Innovator Under 35

College honors 17 with yearly Faculty and Student Excellence Awards

Faghih featured in IEEE publication as ‘Woman to Watch’

Continuously Tracking Fear Response Could Improve Mental Health Treatment

Students provide videos to public modeling spread of COVID-19

Adapting Smartwatches to Improve Distance Learning and Health

Provisional Patent

R. T. Faghih., Wickramasuriya, D.S., . SYSTEMS AND METHODS FOR ESTIMATING A NERVOUS SYSTEM STATE BASED ON MEASUREMENT OF A PHYSIOLOGICAL CONDITIONU.S. Provisional Patent Application No.: 63/110,48