AI-powered deep brain stimulation improves walking in Parkinson's patients

Deep brain stimulation (DBS) has been used for more than three decades to treat motor symptoms of Parkinson's disease. Today, over 200,000 patients worldwide have been implanted with these systems, which continuously deliver electrical stimulation to specific deep brain regions to reduce rigidity and tremor. Yet despite its clinical success, conventional deep brain stimulation (DBS) remains limited in its ability to address one of the most disabling symptoms of the disease: walking impairments.

Researchers in Lausanne have developed a new approach, published in Nature Medicine, that adapts DBS in real time to the patient's mobility in everyday situations. Thanks to artificial intelligence, the system continuously interprets the patient's activity and adjusts stimulation in real time, improving walking, climbing stairs, and even the simple act of standing up.

Adapting stimulation to real-life situations

"Before, I could barely walk because my legs would feel heavy or sometimes move uncontrollably. Now, as the stimulation adapts to what I'm doing, I can walk better and for longer stretches," recounts Mr. F, one of the study's participants. Unlike conventional DBS, which delivers stimulation continuously with fixed parameters, the new therapy adjusts stimulation dynamically based on the patient's ongoing locomotor activity.

Eduardo Moraud, the newly appointed Medtronic Chair in Neuromodulation professor at EPFLDaily locomotor activity involves a variety of activities, such as standing, walking, running, turning or navigating obstacles, each imposing distinct motor requirements. This work shows that we can decode many of these activities from neural biomarkers and adapt stimulation to match their physiological demands, helping patients move more naturally."

Using artificial intelligence on data from forty patients, the researchers developed neural decoders that detect different locomotor states directly from brain activity in real time. These signals are then used to modulate stimulation within seconds, allowing the therapy to adjust as movement unfolds.

The approach builds on clinically established DBS systems. Through collaboration with industry partner Medtronic, the researchers were able to access and refine key aspects of the technology to target gait problems, enabling the development of adaptive, real-time stimulation strategies.

From the clinic to everyday use

"Walking problems often respond differently to DBS than tremor or rigidity, something clinicians have recognized for years. Our work shows that stimulation settings can be adjusted automatically to meet a person's needs as they move", says Jocelyne Bloch, head of neurosurgery at CHUV and senior co-author of the study.

Conducted within the .NeuroRestore interdisciplinary center co-directed by Bloch, this work brings together CHUV's clinical expertise with EPFL's leadership in neurotechnology to accelerate the translation of next-generation therapies. "Turning deep brain stimulation into an intelligent therapy opens entirely new possibilities for patients, especially those living with severe walking impairments", explains Bloch.

The research team is considering conducting a follow-up study to evaluate long-term outcomes of this therapy and extend the approach to a larger patient population.

Source:

Ecole Polytechnique Federale de Lausanne (EPFL)

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