Author Archives: Rose

NYU Biomedical Engineering welcomed Rose

The Department of Biomedical Engineering’s newest faculty member is pioneering new, brain-aware wearables

NYU Biomedical Engineering welcomed Rose with a news article feature. The feature reads: “MINDWATCH. While it may sound like an exciting hit show on Netflix, it’s actually an acronym for a project from Associate Professor Rose Faghih, a new member of the Department of Biomedical Engineering. It stands for Multimodal Intelligent Noninvasive brain state Decoder for Wearable AdapTive Closed-loop arcHitectures, which she has …”

Read more in NYU News

CML Publications in 2021

 

Rose contributed as a co-editor of an e-book published by . The e-book is comprised of multiple papers which mainly investigate deep brain stimulation and is available for free download
Submissions are open for Volume II of this Frontiers in Neuroscience Research Topic. Contributions from the research community are welcome for “Towards the Next Generation of Deep Brain Stimulation Therapies: Technological Advancements, Computational Methods, and New Targets”. Manuscripts can be submitted here.  

 

Several journal articles were published by CML this year. The journals included IEEE Transactions on Biomedical EngineeringIEEE Transactions on Neural Systems and Rehabilitation EngineeringIEEE AccessFrontiers in neuroscienceIEEE/ACM Transactions on Computational Biology and Bioinformatics, and PLoS Computational Biology. Example focus areas of research covered in these journal publications included inferring sympathetic nervous system activation, seizure state tracking, designing closed-loop systems for stress regulation as well as energy regulation, quantification of growth hormone secretion and causality analysis of spike train data.

 

CML graduate students presented their research at the 2021 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Conference  (EMBC) and published three conference papers in proceedings of EMBC. Their research mainly described the impact of different types of music on cognitive arousal and performance during working memory experiments performed at CML. The conference papers focused on decoding cognitive arousal using skin conductance variations and functional near-infrared spectroscopy (fNIRS) data, characterizing cognitive performance based on behavioral data, and quantifying the performance as a function of cognitive arousal with the goal of eventually designing controllers that use music as an actuator to regulate arousal and improve performance. The experimental dataset used in these publications was collected by CML before the pandemic; those interested in collaborations on this dataset can contact Rose at rfaghih@nyu.edu to access the data. CML plans to make the dataset publicly available in the next couple of years for the public to use.


  • Publications:

[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.

[2] 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).

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

[4] 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.

[5] 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.

[6] 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.

[7] Amin, M.R, Tahir, M., and Faghih, R.T.,”A State-Space Investigation of Impact of Music on Cognitive Performance during a Working Memory Experiment.The Annual International Conference of the IEEE Engineering in Medicine and Biology Society,2021. 

CML Graduations in 2021

  • 2021 PhD Graduates 

Md. Rafiul Amin defended his thesis “Scalable and Robust Inference of Sparse Brain Signals via Personalized Physiological System Identification”. He has joined Aeva Inc as a DSP Characterization Engineer.

 

Hamid Fekri Azgomi defended his thesis “Closed-Loop Regulation of Internal Brain States using Wearable Brain Machine Interface Architectures with Real-World Experimental Implementation”. Hamid started his postdoctoral training in the Department of Neurological Surgery at the University of California, San Francisco.

 

  • 2021 M.S. Graduates

Luciano Branco defended his thesis “Closed-Loop Control of Brain States using Physiological Signals from Wearable Devices”. Luciano has started his PhD in Biomedical Engineering at the University of Houston. 

 

Saman Khazaei defended his thesis “Bayesian Decoder Design for Investigation of Cognitive Arousal and Performance Using Physiological and Behavioral Data”. Saman has started his PhD in Biomedical Engineering at NYU’s CML. 

NSF CAREER Project – MINDWATCH

MINDWATCH PUBLICATIONS          Media Attention          Software         Education & Outreach

Acknowledgment: This material is based upon work supported by the National Science Foundation under Grant Number 1755780 Disclaimer: Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

 

  • Project Overview

MINDWATCH Demonstration Video

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.

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:

[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 DataIEEE 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

Software

Deconvolution

Estimation

Closed-Loop Control

Emotion Recognition from Heartbeat Dynamics

Real-Time Seizure Tracking

Educational and Outreach Activities    

Girls Engineering the Future Outreach Event  (2021) – (Video Link)

Educational Videos

State-Space Modeling and control of power systems – Video by Thejas Rajan (Spring 2020)

Feedback displacement control of Dielectric Elastomer Actuator (DEA) – video by Shengbin Wang (Spring 2020)

CartPloe LQR Control Analysis – Video by Pengyu (Ben) Yuan (Spring 2020)

An Application of Optimal Control in EM – Video by Neil Jerome A. Egarguin (Summer 2020)

Matrix Algebra and Linear Equations – Video by Prasanna Kumar Reddy Gade (Fall 2018)

Video on Stability by Nitin Bhabsar (Fall 2018)

Lyapunov’s Indirect Method and Linking Lyapunov Function to LQR –  Video by Harshitha Kethyreddy (Fall 2018)

Gilbert Realization and Pole Zero Cancellation – Video by Divesh Pednekar

Reference Tracking and McMillan Degree –  Video by Aruj Khandelwal

Web Outreach

Computational Medicine Lab’s Youtube Channel

K-12 and College Level Mentor on Engineer Girl, a website by the National Academy of Engineering.

MIT Technology Review

MIT Technology Review selected Rose as one of the visionaries in its list of Innovators Under 35 for the year 2020. The recognition highlighted her idea of sensor-laden wrist-watches that could monitor states of the brain traditionally accessed via neuroimaging technologies such as EEG. The idea would not only have clinical relevance for treating patients with neuropsychiatric or hormone disorders but would also have applicability to people who want to improve everyday health as well. Futuroprossimo, an Italian futurology magazine, also highlighted her as one of the three MIT Technology Review’s 2020 Innovators Under 35 female awardees, who work on an innovation that has the highest potential for a future Nobel prize.  

Read more