PFI-RP: Smart Seizure Prediction System based on AI-enabled Implantable Sensor Networks

这一创新-研究伙伴关系(PFI-RP)项目的更广泛的影响/商业潜力是为那些抗癫痫药物无效的神经疾病患者提供更好的生活质量。虽然这项技术将专注于抗药性癫痫的新疗法，但其他一些医疗应用也是可能的，包括治疗心脏起搏器、帕金森病或创伤后应激障碍(PTSD)患者。根据疾病控制中心(CDC)的数据，1.2%的美国人口(约340万人)患有活动性癫痫，全球有超过6500万人受到影响。虽然癫痫患者受益于植入式医疗设备(IMD)，但目前食品和药物管理局(FDA)批准的用于缓解耐药癫痫患者癫痫发作强度的神经刺激剂都没有提供预防性治疗或提前、准确、预测的警报。该项目可能使医疗专业人员能够准确预测癫痫发作，从而使患者能够采取预防措施，避免严重受伤或死亡等不良后果。拟议的项目将通过嵌入式人工智能(AI)算法为患有无法用抗癫痫药物治疗的神经疾病的患者实现现场智能医疗推理。这种疗法可能不再需要皮下布线和高速全身无线连接，从而提供了一种更安全、更节能的解决方案。目前，商业神经刺激器系统使用皮下发电机的有线导线将电信号发送到目标刺激部位。这种连接是导致术后并发症的主要原因。此外，这些系统大多是开环的，边缘计算能力有限。他们需要大量的临床医生输入来调整他们的反应参数，有些人仍然使用持续刺激，因为他们不能预测癫痫发作。该项目可能会通过开发具有嵌入式、就地、人工智能处理的智能和无线供电植入物来改进深部大脑和其他神经刺激技术。这一发展可能会消除预测模型对外部云计算的依赖，外部云计算需要将稳定的数据流从植入式传感器传输到外部设备。无线连接、可充电和可重新编程将通过低功率超声波添加到系统中。这项创新可能会消除电极和植入物之间的皮下布线以及大型植入式电池的需要。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Partnerships for Innovation - Research Partnerships (PFI-RP) project is to provide a better quality life for patients affected by neurological disorders for whom antiepilepsy drugs are not effective. While the technology will focus on novel treatments for drug-resistant epilepsy, a number of additional medical applications, including the treatment of patients with cardiac pacemakers, Parkinson disease, or post-traumatic stress disorder (PTSD) could be possible. According to the Centers for Disease Control (CDC), 1.2% of the US population (about 3.4 million people) has active epilepsy with more than 65 million people affected globally. While epilepsy patients have benefited from Implantable Medical Devices (IMDs), none of the current Food and Drug Administration (FDA)-approved neurostimulators that are used to alleviate seizure intensity in patients with drug-resistant epilepsy offer preventive treatment or well-in-advance, accurate, predictive alerts. This project may enable medical professionals to accurately predict a seizure so that patients could take precautions and avoid adverse outcomes such as serious injuries or death.The proposed project will enable in-situ smart medical inference via embedded Artificial Intelligence (AI) algorithms for patients affected by neurological disorders not treatable with antiepilepsy madications. The treatment may eliminate the need for subcutaneous wiring and highspeed through-body wireless links, offering a safer and more energy efficient solution. Currently, commercial neurostimulator systems use wired leads from a subcutaneous generator to send electrical signals to the targeted stimulation site. This wiring is a major cause of post-operative complications. Additionally, most of these systems are open-loop and have limited edge-computing capabilities. They require significant manual clinician input to adjust their response parameters and some still use continuous stimulation since they cannot predict a seizure. This project may improve deep brain and other neurostimulation technologies by developing intelligent and wirelessly-powered implants with embedded, in-situ, AI processing. This development may remove the dependency of the prediction models on external cloud computing, which requires transmission of a steady stream of data from implantable sensors to external devices. Wireless connectivity, re-chargeability, and re-programmability will be added to the system through low-power ultrasonic waves. This innovation may eliminate the needs for subcutaneous wiring between electrodes and implants and for large, implanted batteries.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.