We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App


ATTENTION: Due to the COVID-19 PANDEMIC, many events are being rescheduled for a later date, converted into virtual venues, or altogether cancelled. Please check with the event organizer or website prior to planning for any forthcoming event.

Implantable Neuro-Chip Uses Machine Learning Algorithm to Detect and Treat Neurological Disorders

By HospiMedica International staff writers
Posted on 31 Jan 2023
Print article
Image: The neuro-chip with soft implantable electrodes could manage brain disorders (Photo courtesy of EPFL)
Image: The neuro-chip with soft implantable electrodes could manage brain disorders (Photo courtesy of EPFL)

Using a combination of low-power chip design, machine learning algorithms, and soft implantable electrodes, researchers have produced a neural interface that can identify and suppress symptoms of different types of neurological disorders.

NeuralTree, a closed-loop neuromodulation system-on-chip, developed by researchers at EPFL (Lausanne, Switzerland) can detect and alleviate disease symptoms. By utilizing a 256-channel high-resolution sensing array and an energy-efficient machine learning processor, the system can extract and classify a wide range of biomarkers from real patient data and animal models of disease in-vivo, resulting in highly accurate prediction of symptoms. NeuralTree works by extracting neural biomarkers – patterns of electrical signals believed to be associated with specific neurological disorders – from brain waves. It classifies the signals and indicates the possibility of an approaching epileptic seizure or Parkinsonian tremor, for instance. Upon detection of a symptom, a neurostimulator located on the chip becomes activated and sends out an electrical pulse to block it.

NeuralTree’s unique design provides the highest levels of efficiency and versatility as compared to the state-of-the-art. The chip features 256 input channels, as compared to 32 for previous machine-learning-embedded devices, enabling the implant to process more high-resolution data. The chip’s area-efficient design makes it extremely small (3.48mm2), creating significant potential for scalability to additional channels. The integrated ‘energy-aware’ learning algorithm that penalizes features consuming a lot of power also makes NeuralTree extremely energy efficient.

The system can also detect a wider range of symptoms than other devices, which focus mainly on the detection of epileptic seizures. The researchers trained the chip’s machine learning algorithm on datasets from both epilepsy and Parkinson’s disease patients, and accurately classified pre-recorded neural signals from both the categories. With the aim of making neural interfaces more intelligent for more effective disease control, the researchers are already looking ahead to innovate further. As a next step, the team plans to enable on-chip algorithmic updates in order to keep up with the evolution of neural signals.

“To the best of our knowledge, this is the first demonstration of Parkinsonian tremor detection with an on-chip classifier,” said Mahsa Shoaran of the Integrated Neurotechnologies Laboratory in the School of Engineering. “Eventually, we can use neural interfaces for many different disorders, and we need algorithmic ideas and advances in chip design to make this happen.”

Related Links:

Gold Supplier
12-Channel ECG
Breathing Set
ICU-Level Ventilator
Full Face NIV Mask
Nivairo RT046

Print article


Critical Care

view channel
Image: An earbud prototype that has been wired for data collection (Photo courtesy of MUSC)

Earbuds to Outperform Smartwatches in Monitoring Blood Pressure

While blood pressure cuffs are considered the most accurate method of measurement, they require the user to sit down, put on the cuff, and stay still. This can be inconvenient and may lead to errors in... Read more

Health IT

view channel
Image: Using digital data can improve health outcomes (Photo courtesy of Unsplash)

Electronic Health Records May Be Key to Improving Patient Care, Study Finds

When a patient gets transferred from a hospital to a nearby specialist or rehabilitation facility, it is often difficult for personnel at the new facility to access the patient’s electronic health records... Read more


view channel
Image: The demand for endometrial ablation devices is increasing due to rising prevalence of gynecological disorders (Photo courtesy of Pexels)

Global Endometrial Ablation Market Driven by Rising Prevalence of Gynecological Disorders

Gynecological disorders, such as menorrhagia, PCOD, abnormal vaginal bleeding, affect millions of women globally every year and are on the rise. Abnormal Uterine Bleeding (AUB) is the most common disorder... Read more
Copyright © 2000-2023 Globetech Media. All rights reserved.