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Design and Implementation of a Novel Subject-Specific Neurofeedback Evaluation and Treatment System

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Abstract

Electroencephalography (EEG)-based neurofeedback (NF) is a safe, non-invasive, non-painful method for treating various conditions. Current NF systems enable the selection of only one NF parameter, so that two parameters cannot be feedback simultaneously. Consequently, the ability to individually-tailor the treatment to a patient is limited, and treatment efficiency may therefore be compromised. We aimed to design, implement and test an all-in-one, novel, computerized platform for closed-loop NF treatment, based on principles from learning theories. Our prototype performs numeric evaluation based on quantifying resting EEG and event-related EEG responses to various sensory stimuli. The NF treatment was designed according to principles of efficient learning, and implemented as a gradual, patient-adaptive 1D or 2D computer game, that utilizes automatic EEG feature extraction. Verification was performed as we compared the mean area under curve (AUC) of the theta band of a dozen subjects staring at a wall or performing the NF. Most of the subjects (75%) increased their theta band AUC during the NF session compared with the trial staring at the wall (p = 0.041). Our system enables multiple feature selection and its machine learning capabilities allow an accurate discovery of patient-specific biomarkers and treatment targets. Its novel characteristics may allow for improved evaluation of patients and treatment outcomes.

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Author notes

  1. Sigal Portnoy and Tami Bar-Shalita contributed equally to this work.

Authors and Affiliations

  1. Biomedical Engineering Department, Faculty of Engineering, Tel Aviv University, Tel Aviv, Israel

    Gil Issachar

  2. Occupational Therapy Department, School of Health Professions, Sackler Faculty of Medicine, Tel Aviv University, Ramat-Aviv, 6997801, Tel Aviv, Israel

    Tami Bar-Shalita & Sigal Portnoy

  3. Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel

    Tami Bar-Shalita, Bar Horing & Sigal Portnoy

Authors
  1. Gil Issachar
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  2. Tami Bar-Shalita
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  3. Yair Baruch
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  4. Bar Horing
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  5. Sigal Portnoy
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Correspondence to Sigal Portnoy.

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Associate Editor Joel Stitzel oversaw the review of this article.

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Issachar, G., Bar-Shalita, T., Baruch, Y. et al. Design and Implementation of a Novel Subject-Specific Neurofeedback Evaluation and Treatment System. Ann Biomed Eng 47, 1203–1211 (2019). https://doi.org/10.1007/s10439-019-02228-x

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  • DOI: https://doi.org/10.1007/s10439-019-02228-x

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