Texas MRC Research Projects

 

Obstructive Sleep Apnea (OSA) is a public health concern. Unfortunately, the primary means of treatment, Positive Airway Pressure (PAP) therapy, is met with high rates of poor adherence in part attributed to side effects. Air flow leak (leak), one of the most frequent side effects that has not been addressed in treatment programs, directly impacts the effectiveness of PAP therapy and continued use. The research team will develop a novel universal device that will measure leak and provide real-time feedback to users in order to increase adherence.

Brandy M. Roane, Ph.D., CBSM, UNTHSC
Brandy.Roane@unthsc.edu//Biography
Assistant Professor – Department of Internal Medicine
Co-PIs:
Eileen Clements, Ph.D. UTARI
Sherif Al-Farra, MD, DABSM, UNTHSC

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We propose to create a miniaturized watch-based energy expenditure monitoring system. Our proposed system will combine heart rate acquired from a wrist-worn photoplethysmogram (PPG) sensor and physical activities using motion sensors in a watch. We will create predictors and fitting functions that use heart rate and activity type/level to estimate the energy expenditure. Our fitting functions customized for individuals will be validated in conjunction with an integrated metabolic measurement system. We will focus on advanced motion artifact rejection techniques that will incorporate the notion of context. Context includes noise models obtained from the motion sensors, as well as the models for the heart rate collected in the past. Knowing that the heart rate cannot fluctuate rapidly, during the periods when the noise due to the motion artifacts increases significantly, we will use the heart rate detected prior to the increased motion-induced artifacts to guide the signal processing modules. We will create signal processing techniques to identify physical activities from the motion sensors. We will validate our energy expenditure monitoring system against an integrated metabolic measurement system at UT-Arlington on (N=20) human subjects.


Roozbeh Jafari, Ph.D. UTD
Associate Professor – Electrical Engineering
rjafari@utdallas.edu//972.883.5609//Biography

Co-PI:
Christpher Ray, Ph.D. UTA

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Device-related infection is a leading cause of failure in many medical devices such as joint prostheses, catheters, prosthetic heart valves and pacemakers. For example, the infection rate of orthopedic implants is 4-5%. Given the aging population and increased need for medical devices, there is an estimate of 100,000 device related infections, which poses a major liability of over $4.0 billion annually on the healthcare system. Infection of medical devices is caused by formation of bacterial biofilm on the device. Biofilms are colonies of bacteria attached to a surface in a self-produced and highly protective matrix. Biofilms on medical devices are the source of major challenges for medical settings. This is because bacteria in biofilms are >1,000 times resistant to antibiotics compared to the free-floating bacteria. Eradication of an infected implant through regular antibiotic therapy is not feasible, and often times the only solution is a revision surgery and second implant, which has a higher chance of infection; and its failure may result in amputation in orthopedic cases. FDA has been concerned about device infection and held a conference as recent as February 2014. Generally, the best solution for fighting biofilms is preventing their formation in early stages, which requires highly sensitive sensors, and is currently lacking. We, a team of PIs with complementary Engineering and Microbiology background, propose to develop and commercialize a marker-free integrated Micro/Nano-Electromechanical (M/NEMS) sensor with fully electronic readout. The sensor will detect biofilm formation in very early stages and actively deliver highly localized doses of antibiotic to eliminate bacteria before biofilm formation. This highly sensitive sensor will find applications in “intelligent implantable devices”, in an over $10 billion market.


Majid Minary, Ph.D., UTD
Assistant Professor-Mechanical Engineering
majid.minary@utdallas.edu//972.883.4641//Biography

Co-PIs:
Siavash Pourkamali, Ph.D. UTD
Woo-Suk Chang, Ph.D. UTA
Jerry Simecka, Ph.D. UNTHSC
Randall Todd Richwine, Ph.D. THR

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We propose to develop a fully automated blood infusion pump equipped with peripherals for monitoring the critical signs and parameters for the fetal blood transfusion operation. The proposed system is called the Computerized Infusion and Monitoring System for Fetal Blood Transfusion, or Computerized Fetal Transfusion System (CFTS) for short. It is to facilitate the blood transfusion operations with high precision and reliability under full control of the surgeon. Intrauterine fetal blood transfusion for Rh disease (Rhesus isoimmunisation) is a lifesaving operation which becomes necessary when Rh-sensitized mother’s immune system attacks and destroys fetal red blood cells endangering the life of the fetus during pregnancy. The fetal blood transfusion through the umbilical vein in the placenta is a delicate operation providing blood to fetus directly with fast positive results. Such operation may need to be repeated multiple times during a pregnancy.

(more…)

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The breadth of treatments involving electrical stimulation of neural tissue is expanding.  However, major issues remain unresolved in terms of the selectivity and safety of neural electrodes, particularly as most clinical application demand chronic recording/stimulation.  We have demonstrated that peripheral nerves could be interfaced by enticing them to grow in close proximity to electrodes placed in a tridimensional open regenerative multielectrode interface, and that coating commercial electrodes with carbon nanotubes (CNTs) can dramatically enhance the electrical properties of the interface.

Principal Investigator:

Mario Romero-Ortega, Ph.D. UTA
Associate Professor-Bioengineering
mromero@uta.edu // (817) 272-5018 // Biography (more…)

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Approximately one in four epilepsy patients suffer with seizures that cannot be controlled through medication or surgery. In addition to the direct effects of these seizures, their seeming unpredictability causes further loss in quality of life and increased health risk for these patients. The transition from inter-ictal to ictal state is not an abrupt transition. Rather, the pre-ictal state (a timeframe just prior to seizure onset) can last minutes to hours. Further, a number of physiological changes may be observed during this period, although the types and intensities of those changes vary from patient to patient and from one type of seizure to another.

Our proposal is to monitor multiple extra-cranial physiological changes that are known to occur during the pre-ictal period of some seizures. Our twin goals will be to:

(a) Find a set of metrics per patient that provide a clear indication that a seizure is imminent in time to warn the patient/caregiver, and

(b) Use metrics that can be monitored in a non-stigmatizing way.

Achieving these goals will require the use of machine learning (classification) to build a personalized pre-ictal footprint for each patient, and selection of metrics that can be monitored in a non-stigmatizing way. We plan to use sensors mounted on a wristband to achieve this second goal.

Principal Investigator:

Mehrdad Nourani, Ph.D UTD
Associate Professor-Electrical Engineering
Mehrdad.Nourani@utdallas.edu // (972) 883-4391 // Biography (more…)

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Existing blood pressure measurement techniques requiring catheterization are not suitable for wearable applications and continuous monitoring. Cuff-based solutions, on the other hand, are uncomfortable and are only suitable for occasional monitoring. Monitoring blood pressure for individuals with hypertension, the elderly in home-care/assisted-living units, or people who are recovering at home following medical treatment requires a simple, inexpensive, non-invasive and comfortable device. The aim of this project is to develop a non-invasive wearable blood pressure monitoring device using pulse transit time (PTT).

Principal Investigator:

Roozbeh Jafari, Ph.D UTD
Electrical Engineering Department
rjafari@utdallas.edu // 972-883-6509 // Biography (more…)

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We propose to build and test an imaging instrument prototype that uses near‐infrared light to map changes in blood oxygenation on the surface of the brain after traumatic brain injury (TBI) has occurred. This instrument will address the immediate clinical need for a non‐invasive technology capable of alerting the attending clinical staff when a rising intracranial fluid pressure event has occurred after TBI. These events can occur rapidly and unexpectedly at anytime up to a few days post‐trauma. The rising pressure events result in the collapse of blood vessels supplying oxygen to the brain, which often leads to permanent brain damage or death. The current standard of care is a very invasive procedure that involves placing a pressure transducer through a catheter inside the brain, which is very traumatic and has been shown to result in increased morbidity. (more…)

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Mental health is one of the major health issues costing more than $57B annually. Depressive disorder is a major disease of psychiatric disorders. For those patients who failed current behavioral and pharmacological treatment, one option is the deep brain stimulation. The objective of this proposal is to develop an implantable wireless close-loop feedback system that enables the detection of neural signals in the targeted brain site(s) and use these neural signals to trigger electrical stimulation for depression management. Electrical stimulation of neural substrates will increase the set of neurotransmitters (serotonin, norepinephrine, dopamine) that are determinants for mood. The final goal of the project is to design an implantable system that can be used for clinical treatment of depression. (more…)

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This project aims to develop a low-cost home-based wireless automatic sleep apnea detection and sleep quality monitoring system. As internet access becomes part of every home’s de facto facility, the system proposed here will be based on internet. This facilitates reaching out to the public and allows flexibility, scalability, adaptability, ease of access, efficient data storage and statistical profiling. The primary signal we will use for apnea detection and sleep quality assessment is onelead electrocardiogram (EKG) signal. EKG contains not only cardio-related information (e.g., heart rate, heart rate variability (HRV), abnormalities of the heart) but also respiratory-related information useful in detecting sleep apnea. We will also explore how the audio (snoring, teeth grinding) and passive infra-red (PIR) or video (movement, pose) signals recorded during the sleep can complement and enhance the reliability of the results.

(more…)

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