Person:
Inan, Omer T.

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    TENSE Ball: A Smart Therapeutic Squeeze Ball to Monitor Hand Activities and Patients’ Pain and Stress Level
    (Georgia Institute of Technology, 2021-03) Shahmiri, Fereshteh ; Schwartz, Steven ; Usanmaz, Can ; Inan, Omer T. ; Edwards, W. Keith
    Hand dexterity, grip strength, and fine motor control are important to our daily routines but can be severely impacted by the development of prognoses such as Parkinson’s disease, Arthritis, recoveries after stroke, surgery, or coma. Simple yet effective squeeze ball exercises have been shown to accelerate recovery, restore mobility, and reduce pain. Hence, there is a need to monitor patient performance and compliance with respect to these exercises along with additional assessments of pain and stress levels. Commercially available hand exercising balls do not provide quantitative data, which is crucial for assessing patient performance and pain level as well as informing clinicians for proper treatment. To the best of our knowledge, there is no single device in the market or existing research domains, with a flexible form factor that can identify the gripping patterns and correctness of the performed therapeutic exercises as well as assess the pain level that patient is experiencing before and after those exercises. Hence, we designed TENSE ball, a triboelectric nanogenerator-based squeezable electronic ball that is computationally capable of addressing discussed problems, while maintaining the innate features as its non-computational counterparts. The major contributions of our design include first, capturing psycho-physiological data utilizing an Electro-dermal Activity (EDA) sensor. Second, it monitors the biomechanical status of hand motions and dexterity to assess the correctness of the patient’s performed therapeutic exercises and tracks compliance and improvement with time. Third, it detects hand tremors and other involuntary motion artifacts which allows for the capturing of valuable patient prognostic information.
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    Wearable Joint Health Assessment with Acoustic Emission and Bioimpedance Spectroscopy Sensing
    (Georgia Institute of Technology, 2019-10-10) Inan, Omer T.
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    Non-Invasive Physiological Sensing and Modulation for Human Health and Performance
    (Georgia Institute of Technology, 2018-11-13) Inan, Omer T.
    The Precision Medicine Initiative challenges biomedical researchers to reframe health optimization and disease treatment in a patientspecific, personalized manner. Rather than a one-size-fits-all paradigm, the charge is for a particular profile to be fit to each patient, and for disease treatment (or wellness) strategies to then be tailored accordingly. Non-invasive physiological sensing and modulation can play an important role in this effort by augmenting existing research in omics and medical imaging towards better developing such personalized models for patients, and in continuously adjusting such models to optimize therapies in real-time to meet patients’ changing needs. While in many instances the focus of such efforts is on disease treatment, optimizing performance for healthy individuals is also a compelling need. This talk will focus on my group’s research on non-invasive sensing of the sounds and vibrations of the body, with application to musculoskeletal and cardiovascular monitoring applications. In the first half of the talk, I will discuss our studies that are elucidating mechanisms behind the sounds of the knees, and particularly the characteristics of such sounds that change with acute injuries. We use miniature microelectromechanical systems (MEMS) air-based and piezoelectric contact microphones to capture joint sounds emitted during movement, then apply data analytics techniques to both visualize and quantify differences between healthy and injured knees. In the second half of the talk, I will describe our work studying the vibrations of the body in response to the heartbeat using modified weighing scales and wearable MEMS accelerometers. Our group has extensively studied the timings of such vibrations in relation to the electrophysiology of the heart, and how such timings change for patients with cardiovascular diseases during treatment. Ultimately, we envision that these technologies can enable personalized titration of care and optimization of performance to reduce injuries and rehabilitation time for athletes and soldiers, improve the quality of life for patients with heart disease, and reduce overall healthcare costs.
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    Health Systems: The Next Generation - Rapid Fire Research Presentations 2018
    (Georgia Institute of Technology, 2018-11-09) DuBose, Jennifer R. ; Hughes, Danny ; Inan, Omer T. ; Li, Zihao ; Styczynski, Mark P.
    This event will focus on improving health systems, with a focus on promoting wellness in addition to treating disease, and how data and technology might enable and support a transformation. Through panel discussion, we will explore the theme of "Moving from Sick-care to Healthcare" and further dive into the topic of "Proactive Innovations Moving Healthcare Forward.” Rapid fire presentations and the poster sessions will showcase ideas for the future, allowing for dialogue and networking between presenters and participants.
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    Non-invasive Physiological Sensing and Modulation for Human Health and Performance
    (Georgia Institute of Technology, 2016-10-11) Inan, Omer T.
    The Precision Medicine Initiative challenges biomedical researchers to reframe health optimization and disease treatment in a patient-specific, personalized manner. Rather than a one-size-fits-all paradigm, the charge is for a particular profile to be fit to each patient, and for disease treatment (or wellness) strategies to then be tailored accordingly. Non-invasive physiological sensing and modulation can play an important role in this effort by augmenting existing research in omics and medical imaging towards better developing such personalized models for patients, and in continuously adjusting such models to optimize therapies in real-time to meet patients’ changing needs. While in many instances the focus of such efforts is on disease treatment, optimizing performance for healthy individuals is also a compelling need. This talk will focus on my group’s research on non-invasive sensing of the sounds and vibrations of the body, with application to musculoskeletal and cardiovascular monitoring applications. In the first half of the talk, I will discuss our studies that are elucidating mechanisms behind the sounds of the knees, and particularly the characteristics of such sounds that change with acute injuries. We use miniature microelectromechanical systems (MEMS) air-based and piezoelectric contact microphones to capture joint sounds emitted during movement, then apply data analytics techniques to both visualize and quantify differences between healthy and injured knees. In the second half of the talk, I will describe our work studying the vibrations of the body in response to the heartbeat using modified weighing scales and wearable MEMS accelerometers. Our group has extensively studied the timings of such vibrations in relation to the electrophysiology of the heart, and how such timings change for patients with cardiovascular diseases during treatment. Ultimately, we envision that these technologies can enable personalized titration of care and optimization of performance to reduce injuries and rehabilitation time for athletes and soldiers, improve the quality of life for patients with heart disease, and reduce overall healthcare costs.