This study demonstrates that people with tetraplegia can use a neurally controlled robotic arm to perform three-dimensional reach and grasp movements. Two participants with long-standing tetraplegia, caused by brainstem strokes, used a neural interface system to control a robotic arm. The system decoded signals from a small population of motor cortex neurons recorded via a 96-channel microelectrode array. The participants were able to perform complex tasks, including reaching for and grasping targets in three-dimensional space, and even drinking from a bottle using the robotic arm. Although the robotic movements were not as fast or accurate as those of able-bodied individuals, the results show that people with tetraplegia can regain control over complex devices using neural signals. The study also highlights the feasibility of using neural interface systems for daily activities, such as drinking, which were previously impossible for these individuals. The results suggest that chronic implantation of neural sensors can provide long-term functionality, as demonstrated by the participant who had a sensor implanted five years earlier. The study also shows that neural signals recorded from a small intracortical array can provide sufficient information for complex manual tasks. The findings have implications for the development of neural prosthetics and the restoration of motor function in individuals with paralysis. The study was conducted in a clinical trial and involved both robotic arms, the DLR Light-Weight Robot III and the DEKA Arm System. The results demonstrate the potential of neural interface systems to restore mobility and independence for people with paralysis.This study demonstrates that people with tetraplegia can use a neurally controlled robotic arm to perform three-dimensional reach and grasp movements. Two participants with long-standing tetraplegia, caused by brainstem strokes, used a neural interface system to control a robotic arm. The system decoded signals from a small population of motor cortex neurons recorded via a 96-channel microelectrode array. The participants were able to perform complex tasks, including reaching for and grasping targets in three-dimensional space, and even drinking from a bottle using the robotic arm. Although the robotic movements were not as fast or accurate as those of able-bodied individuals, the results show that people with tetraplegia can regain control over complex devices using neural signals. The study also highlights the feasibility of using neural interface systems for daily activities, such as drinking, which were previously impossible for these individuals. The results suggest that chronic implantation of neural sensors can provide long-term functionality, as demonstrated by the participant who had a sensor implanted five years earlier. The study also shows that neural signals recorded from a small intracortical array can provide sufficient information for complex manual tasks. The findings have implications for the development of neural prosthetics and the restoration of motor function in individuals with paralysis. The study was conducted in a clinical trial and involved both robotic arms, the DLR Light-Weight Robot III and the DEKA Arm System. The results demonstrate the potential of neural interface systems to restore mobility and independence for people with paralysis.