Parker Samuel R, Calvert Jonathan S, Darie Radu, Jang Jaeson, Govindarajan Lakshmi Narasimhan, Angelino Keith, Chitnis Girish, Iyassu Yohannes, Shaaya Elias, Fridley Jared S, Serre Thomas, Borton David A, McLaughlin Bryan L
School of Engineering, Brown University, Providence, RI, United States of America.
Cognitive & Psychological Sciences, Brown University, Providence, RI, United States of America.
J Neural Eng. 2025 Mar 19;22(2):026023. doi: 10.1088/1741-2552/adba8b.
. Epidural electrical stimulation (EES) has shown promise as both a clinical therapy and research tool for studying nervous system function. However, available clinical EES paddles are limited to using a small number of contacts due to the burden of wires necessary to connect each contact to the therapeutic delivery device, limiting the treatment area or density of epidural electrode arrays. We aimed to eliminate this burden using advanced on-paddle electronics.. We developed a smart EES paddle with a 60-electrode programmable array, addressable using an active electronic multiplexer embedded within the electrode paddle body. The electronics are sealed in novel, ultra-low profile hermetic packaging. We conducted extensive reliability testing on the novel array, including a battery of ISO 10993-1 biocompatibility tests and determination of the hermetic package leak rate. We then evaluated the EES device, placed on the epidural surface of the ovine lumbosacral spinal cord for 15 months.The active paddle array performed nominally when implanted in sheep for over 15 months and no device-related malfunctions were observed. The onboard multiplexer enabled bespoke electrode arrangements across, and within, experimental sessions. We identified stereotyped responses to stimulation in lower extremity musculature, and examined local field potential responses to EES using high-density recording bipoles. Finally, spatial electrode encoding enabled machine learning models to accurately perform EES parameter inference for unseen stimulation electrodes, reducing the need for extensive training data in future deep models.. We report the development and chronic large animalevaluation of a high-density EES paddle array containing active electronics. Our results provide a foundation for more advanced computation and processing to be integrated directly into devices implanted at the neural interface, opening new avenues for the study of nervous system function and new therapies to treat neural injury and dysfunction.
硬膜外电刺激（EES）作为一种临床治疗方法和研究神经系统功能的研究工具已显示出前景。然而，由于将每个触点连接到治疗输送设备所需的电线负担，现有的临床EES极板仅限于使用少量触点，这限制了硬膜外电极阵列的治疗面积或密度。我们旨在使用先进的极板上电子设备消除这种负担。我们开发了一种智能EES极板，其具有60电极可编程阵列，可使用嵌入在电极极板主体内的有源电子多路复用器进行寻址。电子设备密封在新型超薄气密包装中。我们对新型阵列进行了广泛的可靠性测试，包括一系列ISO 10993-1生物相容性测试以及确定气密包装的泄漏率。然后，我们评估了放置在绵羊腰骶部脊髓硬膜外表面15个月的EES设备。当植入绵羊体内超过15个月时，有源极板阵列表现正常，未观察到与设备相关的故障。板载多路复用器能够在实验过程中以及实验过程内进行定制电极排列。我们确定了下肢肌肉组织对刺激的刻板反应，并使用高密度记录双极电极检查了对EES的局部场电位反应。最后，空间电极编码使机器学习模型能够准确地对未见过的刺激电极进行EES参数推断，减少了未来深度模型中对大量训练数据的需求。我们报告了一种包含有源电子设备的高密度EES极板阵列的开发和长期大型动物评估。我们的结果为将更先进的计算和处理直接集成到植入神经接口的设备中奠定了基础，为研究神经系统功能和治疗神经损伤及功能障碍的新疗法开辟了新途径。
