With a little training, the two participants took control of the arm. It was the first time the man had used a limb of any kind in three years, and the first time in 15 years for the woman. Both were able to move the robotic arm and hand skillfully enough to pick up foam objects.

“It was encouraging to see that, 15 years after the brain was disconnected from the limbs, it was still able to generate all the neural activity necessary to make movements,” John P. Donoghue, a neuroscientist at Brown University and the study’s senior author, said in a conference call on Tuesday.

His co-authors included Dr. Hochberg, who is also affiliated with Brown and with Massachusetts General Hospital, and Patrick van der Smagt, of the Institute of Robotics and Mechatronics, in Germany.

The researchers still have many hurdles to clear before this technology becomes practical in the real world, experts said. The equipment used in the study is bulky, and the movements made with the robot are still crude. And the silicon implants generally break down over time (though the woman in the study has had hers for more than five years, and it is still effective).

No one has yet demonstrated an effective wireless system, nor perfected one that could bypass the robotics altogether — transmitting brain signals directly to muscles — in a way that allows for complex movements.

In an editorial accompanying the study, Andrew Jackson of the Institute of Neuroscience at Newcastle University wrote that economics might be the largest obstacle: “It remains to be seen whether a neural-interface system that will be of practical use to patients with diverse clinical needs can become a commercially viable proposition.”

But all agree that the new study — and the look on the paralyzed woman’s face when she served herself a sip of coffee — should give researchers the incentive and confidence to solve these problems.

The ultimate goal, Dr. Donoghue said, is to develop a system that is so effective and discreet that people with brain injuries “can interact with the environment without anyone knowing they’re using a brain-machine interface.”