About Us

Who we are

A group of young and motivated scientists venturing through and exploring the uncharted terrain of scientific advancements to quench the thirst of our curious minds. We are very critical, analytical, observant, and detail-orientated. We came from different backgrounds believing that diversity will enrich our scientific journey with creativity, innovation, knowledge, and personal growth.

Active Projects

  • Driving behavior prediction in connected vehicles using joint physiological and behavioral modeling: A deep learning approach
  • Automatic electroencephalogram ocular artifact removal using independent component analysis
  • Automatic compliance monitoring of smart brace treatment for patients with adolescent idiopathic scoliosis
  • Ambulatory brain-computer interface: visual-evoked potential (VEP) incremental modeling and adaptation
  • Unsupervised patient gait and lower body motion analysis for adherence of foot brace treatment
  • Investigating driver drowsiness monitoring and prediction via virtual reality based driver simulation
  • Continuous heart rate estimation from electrocardiogram (ECG) signals using sparse decomposition
  • Wearable driver state monitoring using a single wrist-band and session invariant feature extraction

Team Members

Omid Dehzangi

Omid Dehzangi is currently an Assistant Professor of Computer Science in the Department of Computer and Information Science at the University of Michigan-Dearborn. His research interests lie broadly in the area of wearable embedded systems, their signal processing, and data analytic algorithm design with the emphasis on healthcare and well-being applications. The focus of his current research is on different aspects of Pervasive System Design and Wireless Health such as heterogeneous sensing, biomedical signal processing, power vs. accuracy optimization, data analytic and predictive modeling, and algorithm design for wireless sensor networks. His research extends to the areas of signal processing, embedded systems, machine learning, and data mining. His research has been funded by the NSF, NIH, and industry (Texas Instruments, Samsung, Ford, and Toyota).

Omid Dehzangi received B.Sc. and M.Sc. degrees in Computer Science and Engineering from the School of Electrical and Computer Engineering, Shiraz University. He also received his Ph.D. degree from the School of Computer Engineering at Nanyang Technological University.  In 2013 and 2014, he completed postdoctoral fellowships in the Center for Brain Health and the Department of Electrical Engineering at the University of Texas at Dallas, respectively.

Graduate Students

Alex

Automatic electroencephalogram ocular artifact removal using independent component analysis

Anticipated graduation date: April 2017

My name is Alex, I am a Master’s student in the ECE department, I am also currently working as a software engineer. My project uses high dimensional feature analysis to classify blinks in wearable EEG data

Bahvani

Automatic compliance monitoring of smart brace treatment for patients with adolescent idiopathic scoliosis

Anticipated graduation date: December 2017

My name is Bhavani. I am currently pursuing my Master’s degree in Electrical Engineering.  I’m working on developing a pervasive brace monitoring systems for patients with Scoliosis. The system evaluates the effectiveness of the treatment by analyzing the patient data

Mojtaba

Biomedical instruments, signal and image processing

My name is Mojtaba, I am a Research Scientist at Wearable Sensing and Signal Processing Laboratory, CIS Department.  My research concentrates on biological signal analysis for multimodal cognitive load measurement

Muhamed

Ambulatory brain-computer interface: visual-evoked potential (VEP) incremental modeling and adaptation

Anticipated graduation date: December 2017

My name is Muhamed, and I am seeking my Master’s degree in Computer and Information Science.  My research concentrates on Brain-Computer Interface as a communication platform between Intensive-Care Unit Patients and the medical staff

Omar

Unsupervised patient gait and lower body motion analysis for adherence of foot brace treatment

Anticipated graduation date: December 2018

My area of research revolves around brace monitoring and compliance in patients wearing Orthotics. I study force and activity detection in adolescents with Idiopathic Scoliosis, in addition to recognizing gait patterns of patients wearing Ankle-Foot Orthotics. I have a Bachelor’s degree in Electrical Engineering, and am currently pursuing a Master’s in Computer and Information Science. My work involves signal processing and machine learning

Priyal

Investigating driver drowsiness monitoring and prediction via virtual reality based driver simulation

Anticipated graduation date: December 2017

I am pursuing my Master’s in Automotive Engineering at the University of Michigan, Dearborn. I have always been curious to learn new things, irrespective of my discipline, hence, interdisciplinary studies excite me. My passion is to develop a system which has positive impact on the society. therefore, I am working in WSSP Lab on Driver Drowsiness Detection System. WSSP team provides me a state of art infrastructure and environment to hone my skills.

Priyanka

Highly comparative driver distraction analysis: feature extraction and decomposition

My name is Priyanka. I am currently pursuing my master’s in Computer and Information Science. My research focuses on developing a driver distraction detection system using ECG and EEG signals. The system involves high-dimensional feature analysis to monitor driver distraction in real time

Shalini

Cloud-based unsupervised activity monitoring: incremental learning of streaming data

Anticipated graduation date: December 2017

My name is Shalini, and I am a Master’s student at the Computer and Information Department. My research focuses on analyzing the ability to predict individual parameters with the accumulation of additional data. ECG signals are collected using the Shimmer Capture Mobile app for long duration considering daily activities of the subject like sitting, walking, eating, etc. Propose a method for predicting the activities classifiers based on incremental data collecting and learning, using K-means algorithm and Gaussian Mixture Model.

Shantanu

Continuous heart rate estimation from electrocardiogram (ECG) signals using sparse decomposition

Anticipated graduation date: December 2017

It’s all about the heart. My research focuses on the human heart (i.e. ECG). “Electrocardiography (ECG or EKG*) is the process of recording the electrical activity of the heart over a period of time using electrodes placed on the skin – Wikipedia. Now that you know what I am working on- here is the brief info- I am a graduate student and research assistant at WSSP lab. Working on ECG motion artifact analysis, detection and removal of Motion Artifact (MA) contaminated components from ECG signal

Vikas

Wearable driver state monitoring using a single wrist-band and session invariant feature extraction

Anticipated graduation date: December 2017

My name is Vikas, a Master’s student at the Computer and Information Science Department. The main aim of my research is to detect distraction under naturalistic driving using Galvanic Skin Responses

Undergraduate Students

Cayce

Research applications developer

I’m Cayce, an undergraduate Data Science major in the Department of Computer and Information Science. My interest is in creating software that is fun and reliable. My primary projects revolve around writing data acquisition scripts and android applications for other research projects. The research project I focus on is about determining various tasks based on motion

Alumni

Bohan

Multiple sensor data acquisition board design

Derrick

Time series feature extraction with genetic algorithm feature selection

Raminderdeep

Android-based synchronization of multiple motion sensors

Sai

Android-based wearable brain-computer interface

Satya

Acquisition and synchronization of multiple inertial sensors

We are always looking for cool and motivated students

Contact Us