Objective. Brain-computer interfaces (BCIs) that record neural activity using intracortical microelectrode arrays (MEAs) have shown promise for mitigating disability associated with neurological injuries and disorders. While the chronic performance and failure modes of MEAs have been well studied and systematically described in non-human primates, there is far less reported about long-term MEA performance in humans. Our group has collected one of the largest neural recording datasets from a Utah MEA in a human subject, spanning over 5 years (2014–2019). Here we present both long-term signal quality and BCI performance as well as highlight several acute signal disruption events observed during the clinical study. Approach. Long-term Utah array performance was evaluated by analyzing neural signal metric trends and decoding accuracy for tasks regularly performed across 448 clinical recording sessions. For acute signal disruptions, we identify or hypothesize the root cause of the disruption, show how the disruption manifests in the collected data, and discuss potential identification and mitigation strategies for the disruption. Main results. Neural signal quality metrics deteriorated rapidly within the first year, followed by a slower decline through the remainder of the study. Nevertheless, BCI performance remained high 5 years after implantation, which is encouraging for the translational potential of this technology as an assistive device. We also present examples of unanticipated signal disruptions during chronic MEA use, which are critical to detect as BCI technology progresses toward home usage. Significance. Our work fills a gap in knowledge around long-term MEA performance in humans, providing longevity and efficacy data points to help characterize the performance of implantable neural sensors in a human population. The trial was registered on ClinicalTrials.gov (Identifier NCT01997125) and conformed to institutional requirements for the conduct of human subjects research.

目标。使用皮层内微电极阵列 (MEA) 记录神经活动的脑机接口 (BCI) 已显示出减轻与神经损伤和疾病相关的残疾的希望。虽然 MEA 的慢性性能和失效模式已在非人类灵长类动物中得到充分研究和系统描述，但关于人类长期 MEA 性能的报道却少得多。我们的小组从犹他州 MEA 的人类受试者中收集了最大的神经记录数据集之一，时间跨度超过 5 年（2014-2019）。在这里，我们介绍了长期信号质量和 BCI 性能，并重点介绍了临床研究期间观察到的几个急性信号中断事件。方法. 通过分析 448 个临床记录会话中定期执行的任务的神经信号度量趋势和解码准确性，评估了犹他州阵列的长期性能。对于急性信号中断，我们确定或假设中断的根本原因，展示中断如何在收集的数据中表现出来，并讨论中断的潜在识别和缓解策略。主要结果. 神经信号质量指标在第一年迅速恶化，随后在研究的剩余时间内下降缓慢。尽管如此，植入 5 年后 BCI 性能仍然很高，这对于该技术作为辅助设备的转化潜力是令人鼓舞的。我们还展示了长期使用 MEA 期间意外信号中断的例子，随着 BCI 技术向家庭使用发展，这些对于检测到检测至关重要。意义. 我们的工作填补了有关人类长期 MEA 性能的知识空白，提供了寿命和功效数据点，以帮助表征可植入神经传感器在人群中的性能。该试验在ClinicalTrials.gov（标识符NCT01997125）上注册，符合进行人体受试者研究的机构要求。