Medical device development includes prototyping, benchtop characterization, preclinical studies, and clinical trials. Understanding the limitations and potential adverse effects of medical devices prior to their administration in humans is a crucial first step. Optimizing medical devices is essential to employing technology and improving patients care. Computational modeling is widely adopted as a powerful tool to predict stimulation/recording parameter optimization, rapid electrode/device prototyping, investigating novel mechanism of action, and testing working principles of any medical devices. Many implantable neuromodulation technologies including Spinal Cord Stimulation (SCS), which provide substantial therapeutic benefit for patient population with lower back pain, produces heat via the principle of joule heating. Similarly, several therapeutic cooling technologies are providing neuroprotective effects in brain injury patients via focal intracranial cooling technologies. Nonetheless, heating or cooling effects of these medical devices require further investigation and optimization to establish safety limits. The purpose of this work was to: (1) develop a bioheat FEM model to characterize joule heating during Spinal Cord Stimulation; (2) develop and validate a time-dependent adaptive bioheat model of therapeutic brain cooling device. We employed both technical and experimental methods in achieving these two objectives. Kilohertz frequency SCS (kHz-SCS) deposits significantly more power in tissue compared to SCS at conventional frequencies, reflecting increased duty cycle (pulse compression). We hypothesized that 10 kHz-SCS increases local tissue temperature by joule heat, which may influence the clinical outcomes. First, we fully characterized, through extensive in vitro benchtop characterization testing, the extent of spinal tissue heating during Conventional and 10 kHz-SCS in a homogenous basic phantom medium. Later, we developed and validated a bioheat FEM model of the spinal column using an advanced realistic in vitro spinal phantom. Next, we used the validated FEM model to evaluate tissues heating during Conventional, High Density (HD), and 10 kHz-SCS systems with broader stimulation parameters testing. Finally, we developed an adaptive bioheat model to characterize an intracranial cooling device to optimize therapeutic outcomes. We validated the intracranial cooling model using existing pilot clinical data.
","abstract_html":"<p>Medical device development includes prototyping, benchtop characterization, preclinical studies, and clinical trials. Understanding the limitations and potential adverse effects of medical devices prior to their administration in humans is a crucial first step. Optimizing medical devices is essential to employing technology and improving patients care. Computational modeling is widely adopted as a powerful tool to predict stimulation/recording parameter optimization, rapid electrode/device prototyping, investigating novel mechanism of action, and testing working principles of any medical devices. Many implantable neuromodulation technologies including Spinal Cord Stimulation (SCS), which provide substantial therapeutic benefit for patient population with lower back pain, produces heat via the principle of joule heating. Similarly, several therapeutic cooling technologies are providing neuroprotective effects in brain injury patients via focal intracranial cooling technologies. Nonetheless, heating or cooling effects of these medical devices require further investigation and optimization to establish safety limits. The purpose of this work was to: (1) develop a bioheat FEM model to characterize joule heating during Spinal Cord Stimulation; (2) develop and validate a time-dependent adaptive bioheat model of therapeutic brain cooling device. We employed both technical and experimental methods in achieving these two objectives. Kilohertz frequency SCS (kHz-SCS) deposits significantly more power in tissue compared to SCS at conventional frequencies, reflecting increased duty cycle (pulse compression). We hypothesized that 10 kHz-SCS increases local tissue temperature by joule heat, which may influence the clinical outcomes. First, we fully characterized, through extensive in vitro benchtop characterization testing, the extent of spinal tissue heating during Conventional and 10 kHz-SCS in a homogenous basic phantom medium. Later, we developed and validated a bioheat FEM model of the spinal column using an advanced realistic in vitro spinal phantom. Next, we used the validated FEM model to evaluate tissues heating during Conventional, High Density (HD), and 10 kHz-SCS systems with broader stimulation parameters testing. Finally, we developed an adaptive bioheat model to characterize an intracranial cooling device to optimize therapeutic outcomes. We validated the intracranial cooling model using existing pilot clinical data.</p>","abstract_has_math":false,"creators":["Zannou, Adantchede Louis"],"institution":null,"degree_name":"Doctor of Philosophy (Ph.D.)","degree_level":"Dissertation","degree_discipline":"Biomedical Engineering","degree_department":null,"school":null,"contributors":["Marom Bikson"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-01-01T08:00:00Z","date_published":"2023-01-01T08:00:00Z","updated_at":"2026-07-24T01:57:59Z","subjects":["Brain Stimulation","Spinal Cord Stimulation","Therapeutic Hypothermia","Medical Devices Optimization","Bioheat Transfer FEM Modeling","Neuromodulation","Bioelectrical and Neuroengineering","Biomedical Devices and Instrumentation","Biomedical Engineering and Bioengineering","Computational Engineering","Computer-Aided Engineering and Design","Engineering","Hardware Systems","Heat Transfer, Combustion","Therapeutics","Translational Medical Research"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://academicworks.cuny.edu/cc_etds_theses/1134","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Marom Bikson"]},{"key":"dc:creator","label":"Author","values":["Zannou, Adantchede Louis"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2023-05-24T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biomedical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (Ph.D.)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Brain Stimulation","Spinal Cord Stimulation","Therapeutic Hypothermia","Medical Devices Optimization","Bioheat Transfer FEM Modeling","Neuromodulation","Bioelectrical and Neuroengineering","Biomedical Devices and Instrumentation","Biomedical Engineering and Bioengineering","Computational Engineering","Computer-Aided Engineering and Design","Engineering","Hardware Systems","Heat Transfer, Combustion","Therapeutics","Translational Medical Research"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://academicworks.cuny.edu/cc_etds_theses/1134"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Medical device development includes prototyping, benchtop characterization, preclinical studies, and clinical trials. Understanding the limitations and potential adverse effects of medical devices prior to their administration in humans is a crucial first step. Optimizing medical devices is essential to employing technology and improving patients care. Computational modeling is widely adopted as a powerful tool to predict stimulation/recording parameter optimization, rapid electrode/device prototyping, investigating novel mechanism of action, and testing working principles of any medical devices. Many implantable neuromodulation technologies including Spinal Cord Stimulation (SCS), which provide substantial therapeutic benefit for patient population with lower back pain, produces heat via the principle of joule heating. Similarly, several therapeutic cooling technologies are providing neuroprotective effects in brain injury patients via focal intracranial cooling technologies. Nonetheless, heating or cooling effects of these medical devices require further investigation and optimization to establish safety limits. The purpose of this work was to: (1) develop a bioheat FEM model to characterize joule heating during Spinal Cord Stimulation; (2) develop and validate a time-dependent adaptive bioheat model of therapeutic brain cooling device. We employed both technical and experimental methods in achieving these two objectives. Kilohertz frequency SCS (kHz-SCS) deposits significantly more power in tissue compared to SCS at conventional frequencies, reflecting increased duty cycle (pulse compression). We hypothesized that 10 kHz-SCS increases local tissue temperature by joule heat, which may influence the clinical outcomes. First, we fully characterized, through extensive in vitro benchtop characterization testing, the extent of spinal tissue heating during Conventional and 10 kHz-SCS in a homogenous basic phantom medium. Later, we developed and validated a bioheat FEM model of the spinal column using an advanced realistic in vitro spinal phantom. Next, we used the validated FEM model to evaluate tissues heating during Conventional, High Density (HD), and 10 kHz-SCS systems with broader stimulation parameters testing. Finally, we developed an adaptive bioheat model to characterize an intracranial cooling device to optimize therapeutic outcomes. We validated the intracranial cooling model using existing pilot clinical data.
"]},{"key":"dc:title","label":"Title","values":["Use of Bioheat Modeling to Characterize and Optimize Implantable Medical Devices and Neuromodulation Technologies"]}]}],"canonical_facts":{"dc:contributor":["Marom Bikson"],"dc:creator":["Zannou, Adantchede Louis"],"dc:date.available":["2023-05-24T07:00:00Z"],"dc:description.abstract":["Medical device development includes prototyping, benchtop characterization, preclinical studies, and clinical trials. Understanding the limitations and potential adverse effects of medical devices prior to their administration in humans is a crucial first step. Optimizing medical devices is essential to employing technology and improving patients care. Computational modeling is widely adopted as a powerful tool to predict stimulation/recording parameter optimization, rapid electrode/device prototyping, investigating novel mechanism of action, and testing working principles of any medical devices. Many implantable neuromodulation technologies including Spinal Cord Stimulation (SCS), which provide substantial therapeutic benefit for patient population with lower back pain, produces heat via the principle of joule heating. Similarly, several therapeutic cooling technologies are providing neuroprotective effects in brain injury patients via focal intracranial cooling technologies. Nonetheless, heating or cooling effects of these medical devices require further investigation and optimization to establish safety limits. The purpose of this work was to: (1) develop a bioheat FEM model to characterize joule heating during Spinal Cord Stimulation; (2) develop and validate a time-dependent adaptive bioheat model of therapeutic brain cooling device. We employed both technical and experimental methods in achieving these two objectives. Kilohertz frequency SCS (kHz-SCS) deposits significantly more power in tissue compared to SCS at conventional frequencies, reflecting increased duty cycle (pulse compression). We hypothesized that 10 kHz-SCS increases local tissue temperature by joule heat, which may influence the clinical outcomes. First, we fully characterized, through extensive in vitro benchtop characterization testing, the extent of spinal tissue heating during Conventional and 10 kHz-SCS in a homogenous basic phantom medium. Later, we developed and validated a bioheat FEM model of the spinal column using an advanced realistic in vitro spinal phantom. Next, we used the validated FEM model to evaluate tissues heating during Conventional, High Density (HD), and 10 kHz-SCS systems with broader stimulation parameters testing. Finally, we developed an adaptive bioheat model to characterize an intracranial cooling device to optimize therapeutic outcomes. We validated the intracranial cooling model using existing pilot clinical data.
"],"dc:identifier":["https://academicworks.cuny.edu/cc_etds_theses/1134"],"dc:subject":["Brain Stimulation","Spinal Cord Stimulation","Therapeutic Hypothermia","Medical Devices Optimization","Bioheat Transfer FEM Modeling","Neuromodulation","Bioelectrical and Neuroengineering","Biomedical Devices and Instrumentation","Biomedical Engineering and Bioengineering","Computational Engineering","Computer-Aided Engineering and Design","Engineering","Hardware Systems","Heat Transfer, Combustion","Therapeutics","Translational Medical Research"],"dc:title":["Use of Bioheat Modeling to Characterize and Optimize Implantable Medical Devices and Neuromodulation Technologies"],"thesis:degree_discipline":["Biomedical Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (Ph.D.)"]},"updated_at":"2026-07-24T01:57:59Z"}