Brain Computer Interface Based Personalized Interventions for Neuropathic Pain Relief

  • BCI
  • GSR
  • LSL
  • multimodal
  • neurorehabilitation
  • VR

This paper considers using Brain Computer Interface framework for Neuropathic Pain Relief. Chronic neuropathic pain is a widespread health issue affecting a significant portion of the population. Traditional pain assessment methods, relying on self-reported scales, often fail to capture the multidimensional nature of pain (physiological and cognitive).

To tackle this issue, the researchers  from ETH Zürich, work on innovative solutions for personalized pain management. A recent study titled “Brain-Computer Interface to Deliver Individualized Multisensory Intervention for Neuropathic Pain” explores the potential of brain-computer interfaces (BCIs) to revolutionize pain relief treatment.

This study uses the combination of wireless EEG (Smarting) and the combined VR-TENS stimulation to deliver personalized neuropathic pain treatment.

The Neuropathic Pain Problem

For those who are new to the field, neuropathic pain is characterized by burning or electric-like sensations. It affects millions of people worldwide, and happens as a consequence of nerve system dysfunction or damage.

This phenomenon is strongly influenced by cognitive and physiological overlap and interconnection: a chronic pain state negatively impacts the patients’ emotional sphere and may lead to depression and anxiety. In turn, the patients feel helpless and catastrophize their condition. This how a vicious cycle of pain and emotional suffering is generated.

Traditional pain scales, such as the Numerical Pain Rating Scale or the Visual Analogue Scale, are self-reporting scales, and therefore they fail to capture the full essence and multidimensionality of pain, making it mostly a subjective measure.

To overcome these limitations, researchers are turning towards neurophysiological biomarkers based on electroencephalography (EEG) and skin conductance (SC), to try to objectively measure and decode pain signals.

Brain Computer Interface for Pain Detection

The researchers started with the vision to develop a BCI capable of detecting neurophysiological signatures of neuropathic pain and triggering personalized interventions. By combining EEG and SC data, they first identified reliable pain biomarkers and then successfully validated the BCI’s ability to decode pain in real-time.

Once the pain biomarkers are identified and validated, the next step involved devising a personalized multisensory (physiological and emotional) intervention, incorporating transcutaneous electrical nerve stimulation (TENS) and virtual reality (VR).

Personalized intervention

The transcutaneous electrical nerve stimulation (TENS) stimulates the peripheral nerves to alleviate pain through neuromodulation. VR, on the other hand, modulates patients’ attention and perception, effectively diverting their focus from pain. Eventhough a combination of the two could result in an intervention targeting both the physiological and attentional (emotional) components of pain, their empirical examination remained unexplored.

BCI Validation approach

To test the proposed method, they set up the experiments involving both healthy subjects and neuropathic patients. Initially, the multisensory intervention was tested on healthy individuals, and the results were promising. Experimental pain induced in the healthy subjects was effectively decreased with the combined TENS-VR intervention.

TENS-VR Combination

To combine TENS and VR, the researchers made the platform that performs the physiological/cognitive stimulation simultaneously (see the figure below). This is done in a way that VR shows the subject from the firs person sitting at the shore, while the waves come and go.

When the contact between the virtual wave and the legs start, the stimulation starts, and when the wave retracts, the stimulation stops. The stimulation intensity simulates the wave height. The setup was validated for 4 different conditions – VR+TENS, TENS only, VR only and control group, that received no (virtual nor physiological) stimulation.

TENS and VR protocol for Neuropathic Pain Relief
The figure borrowed from the original paper.

 

The BCI system was also tested to timely release the intervention based on EEG (measured by SMARTING device) and SC (measured by eSense MINDFIELD). Online data processing was performed in Python, where EEG and SC signals were streamed through Lab Streaming Layer (LSL) and Open Sound Control (OSC) communication protocols respectively.

Brain-Computer Interface with wireless EEG Smarting and VR combined for neuropathic pain relief
The figure borrowed from the original paper.

Validating Results

The BCI, when applied to healthy subjects, demonstrated an impressive 82% accuracy in real-time pain detection.

The researchers further validated their approach on the neuropathic patients group. The BCI achieved a promissing 75% online pain precision rate, which is slightly worse than in healthy subjects. This difference most likely comes from the fact that the pain was induced in healthy subjects, compared to chronic pain in patients, and their different perception of the pain.

What’s more important, however, is that when the BCI intervention was applied to neuropathic patients, the pain was significantly decreased (over 50% NPRS score) the day after the session, showing significant potential of this novel method.

Embracing Data-Driven Pain Therapies

This is specifically important as it lays the foundation for a new era of personalized data-driven pain therapies and portable technologies. By harnessing the power of BCIs, objective neurophysiological signals can be used to detect pain in real-time, providing a more accurate assessment compared to self-reported scales.

The combination of TENS and VR offers a unique and tailored intervention, targeting both the peripheral nerves and the patients’ attention, resulting in a significant reduction in neuropathic pain perception.

Now, while this study is a significant step forward, there are still challenges to overcome before BCIs and personalized pain therapies become mainstream. Further research and refinement are needed to enhance the accuracy and reliability of neurophysiological pain detection. Additionally, the further development of portable and user-friendly BCI devices will be crucial for widespread adoption.

Nonetheless, this study showcases the immense potential of BCIs in transforming pain management. By bridging the gap between neurophysiology and interventions, researchers are paving the way for a future where pain relief is personalized, data-driven, and accessible to all.

With ongoing advancements in technology and a growing understanding of the complexities of pain, we can look forward to a day when chronic pain no longer holds us captive.

In conclusion, the marriage of brain-computer interfaces, neurophysiological biomarkers, and multisensory interventions holds tremendous promise for improving the lives of individuals living with neuropathic pain. By embracing this cutting-edge research, we take a step closer to a world where personalized pain relief is within reach for everyone.

The original paper source: https://link.springer.com/article/10.1007/s13311-023-01396-y

Recommended reading