Designs for implanted brain-computer interfaces (BCIs) have increased significantly in recent years. Each device promises better clinical outcomes and quality-of-life improvements, yet due to severe and inflexible safety constraints, progress requires tight co-design from materials to circuits and all the way up the stack to applications and algorithms. This trend has become more aggressive over time, forcing clinicians and patients to rely on vendor-specific hardware and software for deployment, maintenance, upgrades, and replacement. This over-reliance is ethically problematic, especially if companies go out-of-business or business objectives diverge from clinical promises. Device heterogeneity additionally burdens clinicians and healthcare facilities, adding complexity and costs for in-clinic visits, monitoring, and continuous access. Reliability, interoperability, portability, and future-proofed design is needed, but this unfortunately comes at a cost. These system features sap resources that would have otherwise been allocated to reduce power/energy and improve performance. Navigating this trade-off in a systematic way is critical to providing patients with forever access to their implants and reducing burdens placed on healthcare providers and caretakers. We study the integration of on-device storage to highlight the sensitivity of this trade-off and establish other points of interest within BCI design that require careful investigation. In the process, we revisit relevant problems in computer architecture and medical devices from the current era of hardware specialization and modern neurotechnology.

翻译：近年来，植入式脑机接口（BCI）的设计显著增加。每种设备都承诺更好的临床效果和生活质量改善，但由于严格且不灵活的安全约束，其进展需要从材料到电路、直至上层应用与算法的紧密协同设计。这一趋势日益加剧，迫使临床医生和患者依赖特定供应商的硬件和软件进行部署、维护、升级和更换。这种过度依赖在伦理上存在问题，尤其是在公司倒闭或商业目标与临床承诺背离的情况下。设备的异质性进一步加重了临床医生和医疗机构的负担，增加了门诊就诊、监测和持续访问的复杂性与成本。可靠性、互操作性、可移植性和面向未来的设计是必要的，但这不可避免地会带来成本。这些系统特性消耗了本可用于降低功耗/能耗和提升性能的资源。以系统化的方式权衡这一取舍，对于为患者提供对其植入体的永久访问权并减轻医疗提供者和护理人员的负担至关重要。我们研究了设备上存储的集成，以突显这一权衡的敏感性，并确立BCI设计中其他需要仔细研究的关键点。在此过程中，我们结合当前硬件专业化与现代神经技术的时代背景，重新审视了计算机体系结构和医疗设备领域的相关问题。