Research & Publications

My focus is on developing light and robust algorithms for low power computational eyewears, in order to extract useful information regarding the cognitive state of the user.
The extended abstract of my thesis can be found here, for which I have won the Best PhD Forum Presentation at the 2021 International Conference on Embedded Wireless Systems and Networks (EWSN), Delft, Netherlands.

Sleep Mask

We introduce a lightweight and all-textile sleep mask, PhyMask, that can continuously and simultaneously measure eye parameters (EOG), brain activity (EEG), heart rate, breathing rate, and sleep posture. We have designed a first-of-its-kind, thread-based, reusable wet electrode to measure biopotential signals and EEG micro-events (i.e. spindles and k-complexes), and a pressure-sensitive, ionic fabric sensor to capture pulse and respiration wave-forms from the head. We perform exhaustive data collection studies to validate our device against clinical polysomnography and demonstrate the accuracy of our device. Among our results, we show that the PhyMask outperforms two other wearable sleep trackers, i.e., Fitbit wristband and Oura Ring.

PhyMask data collection

PhyMask: Robust Sensing of Brain Activity and Physiological Signals During Sleep with an All-textile Eye Mask
Soha Rostaminia, Seyedeh Zohreh Homayounfar, Ali Kiaghadi, Trisha Andrew, Deepak Ganesan
First Place Graduate Poster Award, ACM Richard Tapia Celebration of Diversity in Computing Conference (TAPIA 2020)


Bimodal measures of eye parameters and physiological signals can reveal holistic biometrics that are both medically important and integral for improving the responsiveness of augmented reality/virtual reality interfaces and gaming headsets. A longstanding and pernicious challenge is that wearable bimodal systems inevitably tradeoff comfort and form factor for noise. We introduce a lightweight and portable eyemask, that can continuously measure eye parameters over prolonged periods through textile-based sensors.


Multimodal Smart Eyewear for Longitudinal Eye Movement Tracking
Zohreh Homayounfar, Soha Rostaminia, Ali Kiaghadi, Xingda Chen, Emerson Alexander, Deepak Ganesan, Trisha Andrew
Matter, 2020.

Wearable Textile-based Hydrogel Electrode for Measuring Biopotential. (U.S. Patent App. 17/091,675)
Zohreh Homayounfar, Ali Kiaghadi, Soha Rostaminia, Deepak Ganesan, Trisha Andrew

MEDIA COVERAGE: ScienceDaily, E&T, EurekAlert! of AAAS, C&EN of ACS, Neuroscience News, UMass News, and etc.


iShadow is a computational eyeglass that provides a suite of context-sensing tools in a low-power, robust manner, and in an unobtrusive form factor.
We have developed a computationally light algorithm, called iLid, for the purpose of fatigue detection on iShadow platform. iLid can extract eye features such as blink rate, blink duration, and percentage of eye closure (PERCLOS) and can run continuously and up to 2 days using a 570mAh battery, such as the type used on Google Glass.

iLid: Low-power Sensing of Fatigue and Drowsiness Measures on a Computational Eyeglass
Soha Rostaminia, Addison Mayberry, Benjamin Marlin, Deepak Ganesan, Jeremy Gummeson
Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '17)
Best Poster Award, Capital Region Celebration of Women in Computing Conference (CAPWIC 2017)


We present W!NCE, an EOG-based system that can continuously and reliably monitor facial expressions in the natural environment by using a commercially available eyeglass (J!NS MEME). W!NCE detects facial gestures using a two-stage processing pipeline involving motion artifact removal and facial action detection, which has been extensively evaluated by 17 users separately under stationary and ambulatory settings. We also validate our system’s applicability to continuous pain monitoring through a pilot study and several performance benchmarks.

W!NCE: Unobtrusive Sensing of Upper Facial Action Units with EOG-based Eyewear
Soha Rostaminia, Alexander Lamson, Subhransu Maji, Tauhidur Rahman, Deepak Ganesan
Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '19)


WearID is a wearable RFID reader to sense RFID tags on objects. In this project, we present the design and implementation of a full hardware prototype of such a wearable RF reader that tackles several challenges including reader power consumption and body blockage. More information can be found here.


Continuous Measurement of Interactions with the Physical World with a Wrist-worn Backscatter Reader
Ali Kiaghadi, Pan Hu, Jeremy Gummeson, Soha Rostaminia, Deepak Ganesan.
ACM Transactions on Internet of Things (TIOT '19).

Parkinson's Disease Eye Symptoms

In this research, we want to capture and analyze the eye movement/closure patterns of the Parkinson’s patients during the time interval of their morning and afternoon dopaminergic medication intake. The goal is to explore the Parkinson's patients’ eye movement patterns throughout their off and on medication stages. We hope that this investigation leads to finding out the correlations between the patients’ dopamine level and their eye movement behavior.

Parkinson's patient