| Start Date: | 8/5/2022 | Start Time: | 12:00 PM |
| End Date: | 8/5/2022 | End Time: | 2:00 PM |
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Event Description
BIOMED PhD Research Proposal
Title:
Developing an Arduino-based Functional Near Infrared Spectroscopy (fNIRS) and Two Clinical Studies
Speaker:
Ardy Wong, PhD Candidate
School of Biomedical Engineering, Science and Health Systems
Drexel University
Advisor:
Kambiz Pourrezaei, PhD
Professor
School of Biomedical Engineering, Science and Health Systems
Drexel University
Details:
Functional near infrared spectroscopy (fNIRS) is a non-invasive and wearable optical imaging modality that has been used for many applications to monitor hemodynamic response in the clinical setting and experimental setting. These applications demonstrate the versatility of fNIRS as an imaging modality in comparison to its more expensive counterparts such as PET, SPECT, fMRI and EEG. Our lab has developed an affordable fNIRS system using the Arduino microcontroller. Validation tests, such as drift, linearity test and liquid phantom were done to compare with a commercial fNIRS system. This system was used on two different studies: [1] assessment of cerebral oxygenation response to Hemodialysis using fNIRS, and [2] hemodynamic response during odor detection task, as measured by fNIRS.
Hemodialysis (HD) is the most common modality of renal replacement therapy for patients with end stage renal disease (ESRD). HD is a life-saving chronic procedure that removes metabolic waste products, balances the body’s acid contents, and removes excess body water to replace the function of patients’ failing kidneys. However, this therapy is highly burdensome to patients, causing numerous side effects and worsening quality of life. Experts have hypothesized that many of the symptoms and side effects of HD are related to the negative impact of HD on organ perfusion and oxygenation. HD is traditionally performed with continuous monitoring of heart rate and blood pressure. However, based on a few recent studies, blood pressure can be normal while patients on HD are experiencing substantial decrements in cerebral oxygen supply. Cognitive impairment, particularly in executive function domains, commonly affects patients on HD and worsens with longer durations of dialysis. Studies have shown that some patients exhibit worse cognitive function during HD sessions. This finding also does not seem to correlate with intradialytic blood pressure. Therefore, we are proposing to test fNIRS as an additional monitoring strategy during HD. Our goal is to monitor hemodynamic response of multiple patients during a hemodialysis session across three different clinics in Philadelphia.
In addition, the Arduino-based fNIRS system has been used to investigate the hemodynamic response during odor detection task conducted at the olfactory laboratory of Institute for Research in Fundamental Sciences (IPM). Different smells surround us and affect our behavior and emotion. We mostly do not acknowledge how intensely the smells shape our perceptual world until we lose it. This loss might be temporary as it happens during a common cold rhinitis or permanent following a head trauma. Assessment of olfactory nerve function has been part of the neurological examination in clinic, but its subjectivity and lack of precision has caused it not to be emphasized as expected. With the growing evidence for the importance of olfactory evaluation, several attempts were made to prepare precise and valid olfactory tests. Among such tests, University of Pennsylvania Smell Identification Test (UPSIT) has been extensively accepted for a quick assessment in clinic. Despite its high test-retest reliability, it still lacks objectivity as it relies on a subjective report. To overcome this subjectivity, neuroscientists have tried to utilize brain imaging techniques to make an inexpensive test which could easily be compared across different subjects. We hypothesize that the hemodynamic response between odor and non-odor trials will be significantly different. |
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Audience:
Undergraduate StudentsGraduate StudentsFacultyStaff |
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