Tuesday, Aug, 20, 2024 11 a.m. - noon IBB Suddath Room Can't attend inTuesday, Aug, 20, 2024 11 a.m. - noon IBB Suddath Room Can't attend in person? Virtual Link: https://gatech.zoom.us/j/93712683727?pwd=SlQ2K2JzZW1mWFNlQkJhVlVvcFpuQT09 Meeting ID: 937 1268 3727Passcode: 447264 Abstract: Electrical stimulation is a powerful modality used for brain mapping studies, understanding neuronal function and connectivity, and treating neurological conditions. Since the first implantable neuromodulation device half a century ago, their use has become widespread. Despite significant progress in neuromodulation devices, one of the critical challenges that limits successful outcomes and broader adoption is the lack of dose personalization or dose automatic adjustment, leading to sub-optimal outcomes sometimes due to trade-offs between stimulation performance and stimulation-induced side effects. This requires appropriate dose-control algorithms based on relevant physiological biomarkers and/or mechanistic knowledge of optimal dose adjustments. In this presentation, two novel medical device approaches addressing this pivotal challenge are discussed. One approach entails dynamically adjusting stimulation based on sensed physiological biomarkers, exemplified by the world’s first adaptive brain stimulation system currently in use. Identifying and extracting the medically relevant biomarkers is a critical challenge for success, requiring the use of advanced signal processing, machine learning, and control systems principles to develop a decision algorithm capable of controlling or reversing the disease state. The other novel approach consists of dynamically adjusting a parameter of the stimulation pulses based on mathematical constructs inspired by the way the nervous system operates, exemplified by findings from an exploratory clinical study in patients with chronic neuropathic pain. The study results suggest impactful effects on sensory function and axonal recruitment in the dorsal column, as predicted by computational modeling. Key engineering and clinical trial design challenges in advancing these device approaches from concept to translational deployment will be illustrated. The hurdles and advantages of each approach will be discussed, and finally, future applications of these two device approaches will be explored, looking at the intersection of neuromodulation, unmet medical needs, and accelerated clinical translation, with particular attention to potential new targets and emerging applications. person? Virtual Link: https://gatech.zoom.us/j/93712683727?pwd=SlQ2K2JzZW1mWFNlQkJhVlVvcFpuQT09 Meeting ID: 937 1268 3727Passcode: 447264 Abstract: Electrical stimulation is a powerful modality used for brain mapping studies, understanding neuronal function and connectivity, and treating neurological conditions. Since the first implantable neuromodulation device half a century ago, their use has become widespread. Despite significant progress in neuromodulation devices, one of the critical challenges that limits successful outcomes and broader adoption is the lack of dose personalization or dose automatic adjustment, leading to sub-optimal outcomes sometimes due to trade-offs between stimulation performance and stimulation-induced side effects. This requires appropriate dose-control algorithms based on relevant physiological biomarkers and/or mechanistic knowledge of optimal dose adjustments. In this presentation, two novel medical device approaches addressing this pivotal challenge are discussed. One approach entails dynamically adjusting stimulation based on sensed physiological biomarkers, exemplified by the world’s first adaptive brain stimulation system currently in use. Identifying and extracting the medically relevant biomarkers is a critical challenge for success, requiring the use of advanced signal processing, machine learning, and control systems principles to develop a decision algorithm capable of controlling or reversing the disease state. The other novel approach consists of dynamically adjusting a parameter of the stimulation pulses based on mathematical constructs inspired by the way the nervous system operates, exemplified by findings from an exploratory clinical study in patients with chronic neuropathic pain. The study results suggest impactful effects on sensory function and axonal recruitment in the dorsal column, as predicted by computational modeling. Key engineering and clinical trial design challenges in advancing these device approaches from concept to translational deployment will be illustrated. The hurdles and advantages of each approach will be discussed, and finally, future applications of these two device approaches will be explored, looking at the intersection of neuromodulation, unmet medical needs, and accelerated clinical translation, with particular attention to potential new targets and emerging applications.