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--- projects [2018/09/18 13:36] – lesperan
+++ projects [2018/09/18 15:44] (current) – lesperan
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 ~~NOTOC~~
 ====== Proposed Projects   ======
+====== Heart and Voice Signal Processing For Sleep Apnea Detection ======
+**Supervisor:** Hossein Kassiri
+Sleep apnea is a neurological condition where the patient’s breathing is interrupted during sleep, which can lead to excessive daytime sleepiness, irritability, and morning headaches. Left untreated, it increases the risk of numerous serious health issues, including high blood pressure, irregular heartbeat, and stroke. An estimated 860,000 Canadians reported being told by a health professional that they have sleep apnea, but many more people likely remain undiagnosed.
+This project will be done in collaboration with a Toronto-based medical device company that is working on the development of a miniature wearable device for sleep monitoring and apnea detection. The project will be conducted in two phases. In the first phase, the goal is to study and evaluate the efficacy of using various sensory signal (i.e., biomarker) in sleep apnea detection. A short list of candidate biomarkers are selected as a result of literature review, and their importance in apnea detection is evaluated using pre-recorded labelled online datasets. In the second phase, a signal processing algorithm for sleep apnea detection is developed that uses the selected biomarkers from Phase I as its inputs. In addition to detection, the algorithm is intended to evaluate the episode’s severity, frequency, and patient-specific pattern.
+The collaborating company will develop the hardware that contains the biosensors identified by the students and will be responsible for firmware development to control and extract data from the sensors. The company will also develop a mobile app that displays the data obtained, and produces test units that can be used by real human testers.
+**Required skills:** General CSE408x prerequisites, good programming skills, good math skills, knowledge of C or MATLAB programming languages.
+====== Patient-specific epilepsy seizure detection using machine learning ======
+**Supervisor:** Hossein Kassiri
+Accurate detection of neurological disorders such as epilepsy seizures using brain signals requires algorithms that can adjust themselves from patient to patient and from time to time. Data-driven algorithms using machine learning provide us with such patient-specific tools that allow for processing the data recorded from the brain and decide whether or not it can be classified as an abnormal activity for a specific patient.
+This project is aimed at development and optimization of such a machine learning algorithm for early detection of epilepsy seizures. The student will use pre-recorded labeled data from an online standard dataset to train, cross-validate, and test the algorithm. The algorithm is later optimized for computational resource consumption.
+**Required skills:** General CSE408x prerequisites, good programming and math skills, knowledge of C or MATLAB programming languages, basic knowledge of machine learning and pattern recognition (EECS 4404 or similar).
+====== Mobile app development for interfacing with a brain implant ======
+**Supervisor:** Hossein Kassiri
+Our group of researchers in ICSL are working towards implementation of an implantable closed-loop microelectronic system-on-chip (SoC) for recording and processing of EEG signals to be able to detect and treat various neurological disorder patients.
+Online monitoring and control of brain signals is one of the key features that can help the clinician significantly. Currently an electrical engineer has to be on-site to setup the system and adjust it upon clinician’s request. Therefore, a simple GUI that can be operated by a non-engineer enables the clinician to control the process entirely. The project’s goal is to develop a mobile application that is capable of receiving signals and sending commands through a Bluetooth link. Also the app should be capable of displaying the recorded signal.
+The student is expected to have experience with mobile app development (iOS or Android).
+**Required skills:** General CSE408x prerequisites, mobile app development (iOS or Android) experience.
 ====== Biometric access control ======
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-====== Design and development of a low‐power backend PCB for brain neural signal processing and wireless data transmission ======
-**Supervisor:** Hossein Kassiri
-The student will be responsible for the design and testing of a printed circuit board (PCB) that receives brain electrophysiological signals from multiple recording sites; analyze, decode, and organizes them; and transmit them through a wireless link to a handheld (e.g., cellphone) or stationary (e.g. a laptop) device. The board must be designed while the strict power and area budgets of a medical device taken into account.
-Once developed, the prototype along with the currently‐available wearable brain monitoring device will form a complete wireless wearable solution for point‐of‐care brain monitoring and diagnosis applications.
-**Required Background:** Solid knowledge of electrical and electronic circuits, proficiency in Verilog and MATLAB, previous PCB design experience is not a must but definitely is a plus.