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A longitudinal study to explore the efficacy of a multisensory therapy combining VR and TENS on neuropathic pain
We aim to conduct a longitudinal study validating a multisensory therapy combining Transcutaneous Electrical Nerve Stimulation (TENS) and Virtual Reality (VR) for the treatment of neuropathic pain. This will allow to explore short and long-term lasting effects of the proposed multimodal therapy on neuropathic pain perception. During the study, neurophysiological data of Electroencephalography (EEG) and Skin Conductance (SC) will be collected, together with self-reported pain assessments, to unravel reliable biomarkers of pain.
Keywords: Neuropathic pain, VR, TENS, EEG, SC, Signal Processing
Chronic neuropathic pain is a distressing health problem affecting up to 7% of the general population [1]. Due to side effects [2] and limited efficacy of pharmacological approaches[3], novel therapies for the treatment of neuropathic pain are emerging. Some of them, such as Transcutaneous Electrical Nerve Stimulation (TENS) [4], aim at targeting the physiological component of pain, while others, such as Virtual Reality (VR) [5], try to address the cognitive components by modulating attention.
However, there are no holistic therapies which simultaneously tackle pain in all its physical and cognitive components.
We aim to develop a novel multisensory therapy combining TENS and VR and test its benefit on four days treatment sessions.
During the study, we furthermore aim to collect objective and subjective indicators of pain perception to unravel reliable pain signatures. To this extent, we would make use of robust signal processing pipelines, together with the development of a user-friendly phone application where the patient could self-report his pain experience.
Chronic neuropathic pain is a distressing health problem affecting up to 7% of the general population [1]. Due to side effects [2] and limited efficacy of pharmacological approaches[3], novel therapies for the treatment of neuropathic pain are emerging. Some of them, such as Transcutaneous Electrical Nerve Stimulation (TENS) [4], aim at targeting the physiological component of pain, while others, such as Virtual Reality (VR) [5], try to address the cognitive components by modulating attention. However, there are no holistic therapies which simultaneously tackle pain in all its physical and cognitive components. We aim to develop a novel multisensory therapy combining TENS and VR and test its benefit on four days treatment sessions. During the study, we furthermore aim to collect objective and subjective indicators of pain perception to unravel reliable pain signatures. To this extent, we would make use of robust signal processing pipelines, together with the development of a user-friendly phone application where the patient could self-report his pain experience.
The student will be guided in understanding the neuroscientific basis of neuropathic pain and the state of the art of treatment approaches starting from the scientific literature. He will also be guided towards the use of robust signal processing techniques for unveiling reliable pain indicators. At the moment, the therapy has already been developed by the Lab, and tested on few patients.
The major goals for the student will be:
1) Actively play a role in contacting clinics for patients’ recruitment to test the proposed multisensory therapy on several neuropathic patients.
2) Collect experimental data and process them with state-of-the-art Machine Learning approaches for the identification of reliable pain biomarkers.
3) Develop a mobile application where patients could self-report their pain experience during the 4 days of therapies, so as to correlate subjective indicators with objective neurophysiological pain signatures.
• Recommended skills: Strong Knowledge of Matlab/Python for data analysis; Knowledge of AI and Machine Learning algorithms; Experience with neurophysiological data analysis.
• Extra skills: Unity, C#, Neuroscience of pain; Experience with mobile app development.
The student will be guided in understanding the neuroscientific basis of neuropathic pain and the state of the art of treatment approaches starting from the scientific literature. He will also be guided towards the use of robust signal processing techniques for unveiling reliable pain indicators. At the moment, the therapy has already been developed by the Lab, and tested on few patients. The major goals for the student will be:
1) Actively play a role in contacting clinics for patients’ recruitment to test the proposed multisensory therapy on several neuropathic patients.
2) Collect experimental data and process them with state-of-the-art Machine Learning approaches for the identification of reliable pain biomarkers.
3) Develop a mobile application where patients could self-report their pain experience during the 4 days of therapies, so as to correlate subjective indicators with objective neurophysiological pain signatures.
• Recommended skills: Strong Knowledge of Matlab/Python for data analysis; Knowledge of AI and Machine Learning algorithms; Experience with neurophysiological data analysis.
• Extra skills: Unity, C#, Neuroscience of pain; Experience with mobile app development.
Valerio Aurucci, PhD Student at the Neuroengineering laboratory, Email: giuseppevalerio.aurucci@hest.ethz.ch; Noemi Gozzi, PhD Student at the Neuroengineering laboratory, Email: noemi.gozzi@hest.ethz.ch; Greta Preatoni, PhD Student at the Neuroengineering laboratory, Email: greta.preatoni@hest.ethz.ch; Dr. Stanisa Raspopovic, Assistant Professor Neuroengineering laboratory, Head ETH Zurich, Switzerland Email: stanisa.raspopovic@hest.ethz.ch
Valerio Aurucci, PhD Student at the Neuroengineering laboratory, Email: giuseppevalerio.aurucci@hest.ethz.ch; Noemi Gozzi, PhD Student at the Neuroengineering laboratory, Email: noemi.gozzi@hest.ethz.ch; Greta Preatoni, PhD Student at the Neuroengineering laboratory, Email: greta.preatoni@hest.ethz.ch; Dr. Stanisa Raspopovic, Assistant Professor Neuroengineering laboratory, Head ETH Zurich, Switzerland Email: stanisa.raspopovic@hest.ethz.ch