Research on an EEG-based Neurofeedback System for the Auxiliary Intervention of Post-Traumatic Stress Disorder

TAN Lize; DING Peng; WANG Fan; LI Na; GONG Anmin; NAN Wenya; LI Tianwen; ZHAO Lei; FU Yunfa

doi:10.11999/JEIT250093

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TAN Lize, DING Peng, WANG Fan, LI Na, GONG Anmin, NAN Wenya, LI Tianwen, ZHAO Lei, FU Yunfa. Research on an EEG-based Neurofeedback System for the Auxiliary Intervention of Post-Traumatic Stress Disorder[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250093

Citation:

TAN Lize, DING Peng, WANG Fan, LI Na, GONG Anmin, NAN Wenya, LI Tianwen, ZHAO Lei, FU Yunfa. Research on an EEG-based Neurofeedback System for the Auxiliary Intervention of Post-Traumatic Stress Disorder[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250093

Citation:

TAN Lize, DING Peng, WANG Fan, LI Na, GONG Anmin, NAN Wenya, LI Tianwen, ZHAO Lei, FU Yunfa. Research on an EEG-based Neurofeedback System for the Auxiliary Intervention of Post-Traumatic Stress Disorder[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250093

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Research on an EEG-based Neurofeedback System for the Auxiliary Intervention of Post-Traumatic Stress Disorder

doi: 10.11999/JEIT250093

TAN Lize^{1, 2},
DING Peng^{1, 2},
WANG Fan^{1, 2},
LI Na³,
GONG Anmin⁴,
NAN Wenya⁵,
LI Tianwen^{2, 6},
ZHAO Lei^{2, 6},
FU Yunfa^{1, 2
,
,}

1.
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
2.
Brain Cognition and Brain-computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming 650500, China
3.
The First Affiliated Hospital of Kunming Medical University , Kunming 650500, China
4.
Faculty of Information Engineering, Engineering University of Armed Police Force, Xi’an 710000, China
5.
Faculty of Psychology, Shanghai Normal University, Shanghai 200234, China
6.
Faculty of Science, Kunming University of Science and Technology, Kunming 650500, China

Funds: The National Natural Science Foundation of China (82172058, 62376112, 81771926, 61763022, 62366026, 62006246), The 73rd batch of China Postdoctoral Science Foundation (2023M734315), Xi’an City Young Talent Support Plan (959202413100)

Received Date: 2025-02-18
Rev Recd Date: 2025-04-16

Available Online: 2025-05-08

Abstract

Abstract

Objective The ElectroEncephaloGram (EEG)-based Neurofeedback Regulation (ENR) system is designed for real-time modulation of dysregulated stress responses to reduce symptoms of Post-Traumatic Stress Disorder (PTSD) and anxiety. This study evaluates the system’s effectiveness and applicability using a series of neurofeedback paradigms tailored for both PTSD patients and healthy participants. Methods Employing real-time EEG monitoring and feedback, the ENR system targets the regulation of alpha wave activity, to alleviate mental health symptoms associated with dysregulated stress responses. The system integrates MATLAB and Unity3D to support a complete workflow for EEG data acquisition, processing, storage, and visual feedback. Experimental validation includes both PTSD patients and healthy participants to assess the system’s effects on neuroplasticity and emotional regulation. Primary assessment indices include changes in alpha wave dynamics and self-reported reductions in stress and anxiety. Results and Discussions Compared with conventional therapeutic methods, the ENR system shows significant potential in reducing symptoms of PTSD and anxiety. During functionality tests, the system effectively captures and regulates alpha wave activity, enabling real-time and efficient neurofeedback. Dynamic adjustment of feedback thresholds and task paradigms allows participants to improve stress responses and emotional states following training. Quantitative data indicate clear enhancements in EEG pattern modulation, while qualitative assessments reflect improvements in participants’ self-reported stress and anxiety levels. Conclusion This study presents an effective and practical EEG-based neurofeedback regulation system that proves applicable and beneficial for both individuals with PTSD and healthy participants. The successful implementation of the system provides a new technological approach for mental health interventions and supports ongoing personalized neuroregulation strategies. Future research should explore broader applications of the system across neurological conditions to fully assess its efficacy and scalability.
- Neurofeedback,
- ElectroEncephaloGram (EEG),
- Post-Traumatic Stress Disorder (PTSD),
- Brain-Computer Interface (BCI) medicine,
- Applications of BCI medicine

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References(32)

References

[1]	SELYE H. A syndrome produced by diverse nocuous agents[J]. Nature, 1936, 138(3479): 32–32. doi: 10.1038/138032a0.
[2]	BOYCE W T and ELLIS B J. Biological sensitivity to context: I. An evolutionary–developmental theory of the origins and functions of stress reactivity[J]. Development and Psychopathology, 2005, 17(2): 271–301. doi: 10.1017/s0954579405050145.
[3]	DAVIU N, BRUCHAS M R, MOGHADDAM B, et al. Neurobiological links between stress and anxiety[J]. Neurobiology of Stress, 2019, 11: 100191. doi: 10.1016/j.ynstr.2019.100191.
[4]	CHU B, MARWAHA K, SANVICTORES T, et al. Physiology, stress reaction[M]. StatPearls [Internet]. Treasure Island: StatPearls Publishing, 2024.
[5]	KAR N. Cognitive behavioral therapy for the treatment of post-traumatic stress disorder: A review[J]. Neuropsychiatric Disease and Treatment, 2011, 7(1): 167–181. doi: 10.2147/NDT.S10389.
[6]	STEINERT C, MUNDER T, RABUNG S, et al. Psychodynamic therapy: As efficacious as other empirically supported treatments? A meta-analysis testing equivalence of outcomes[J]. American Journal of Psychiatry, 2017, 174(10): 943–953. doi: 10.1176/appi.ajp.2017.17010057.
[7]	MONSOUR M, EBEDES D, and BORLONGAN C V. A review of the pathology and treatment of TBI and PTSD[J]. Experimental Neurology, 2022, 351: 114009. doi: 10.1016/j.expneurol.2022.114009.
[8]	RUGLASS L M, SMITH K Z, KILLEEN T K, et al. Pharmacological treatment of trauma and stressor-related disorders[M]. EVANS S M and CARPENTER K M. APA Handbook of Psychopharmacology. Washington: American Psychological Association, 2019: 281–307. doi: 10.1037/0000133-013.
[9]	AVERILL L A and ABDALLAH C G. Investigational drugs for assisting psychotherapy for posttraumatic stress disorder (PTSD): Emerging approaches and shifting paradigms in the era of psychedelic medicine[J]. Expert Opinion on Investigational Drugs, 2022, 31(2): 133–137. doi: 10.1080/13543784.2022.2035358.
[10]	GASPARYAN A, NAVARRO D, NAVARRETE F, et al. Pharmacological strategies for post-traumatic stress disorder (PTSD): From animal to clinical studies[J]. Neuropharmacology, 2022, 218: 109211. doi: 10.1016/j.neuropharm.2022.109211.
[11]	GOUVEIA F V, DAVIDSON B, MENG Ying, et al. Treating post-traumatic stress disorder with neuromodulation therapies: Transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation[J]. Neurotherapeutics, 2020, 17(4): 1747–1756. doi: 10.1007/s13311-020-00871-0.
[12]	MATSUMOTO H and UGAWA Y. Adverse events of tDCS and tACS: A review[J]. Clinical Neurophysiology Practice, 2017, 2: 19–25. doi: 10.1016/j.cnp.2016.12.003.
[13]	SARICA C, NANKOO J F, FOMENKO A, et al. Human Studies of Transcranial Ultrasound neuromodulation: A systematic review of effectiveness and safety[J]. Brain Stimulation, 2022, 15(3): 737–746. doi: 10.1016/j.brs.2022.05.002.
[14]	SABÉ M, HYDE J, CRAMER C, et al. Transcranial magnetic stimulation and transcranial direct current stimulation across mental disorders: A systematic review and dose-response meta-analysis[J]. JAMA Network Open, 2024, 7(5): e2412616. doi: 10.1001/jamanetworkopen.2024.12616.
[15]	PAN He, DING Peng, WANG Fan, et al. Comprehensive evaluation methods for translating BCI into practical applications: Usability, user satisfaction and usage of online BCI systems[J]. Frontiers in Human Neuroscience, 2024, 18: 1429130. doi: 10.3389/fnhum.2024.1429130.
[16]	陈龙, 张定泽, 王坤, 等. 运动意图的头皮脑电编解码及其脑-机接口研究进展[J]. 电子与信息学报, 2023, 45(10): 3458–3467. doi: 10.11999/JEIT221449. CHEN Long, ZHANG Dingze, WANG Kun, et al. Research progress on the coding and decoding of scalp electroencephalogram induced by movement intention and brain-computer interface[J]. Journal of Electronics & Information Technology, 2023, 45(10): 3458–3467. doi: 10.11999/JEIT221449.
[17]	ZHANG Yuan, DAI Zhongxiang, HU Jianping, et al. Stress-induced changes in modular organizations of human brain functional networks[J]. Neurobiology of Stress, 2020, 13: 100231. doi: 10.1016/j.ynstr.2020.100231.
[18]	FENSTER R J, LEBOIS L A M, RESSLER K J, et al. Brain circuit dysfunction in post-traumatic stress disorder: From mouse to man[J]. Nature Reviews Neuroscience, 2018, 19(9): 535–551. doi: 10.1038/s41583-018-0039-7.
[19]	MAHMOOD D, NISAR H, and TSAI C Y. Exploring the efficacy of neurofeedback training in modulating alpha-frequency band and its effects on functional connectivity and band power[J]. Expert Systems with Applications, 2024, 254: 124415. doi: 10.1016/j.eswa.2024.124415.
[20]	SHAW S B, NICHOLSON A A, ROS T, et al. Increased top-down control of emotions during symptom provocation working memory tasks following a RCT of alpha-down neurofeedback in PTSD[J]. NeuroImage: Clinical, 2023, 37: 103313. doi: 10.1016/j.nicl.2023.103313.
[21]	ROS T, FREWEN P, THÉBERGE J, et al. Neurofeedback tunes scale-free dynamics in spontaneous brain activity[J]. Cerebral Cortex, 2017, 27(10): 4911–4922. doi: 10.1093/cercor/bhw285.
[22]	KLUETSCH R C, ROS T, THÉBERGE J, et al. Plastic modulation of PTSD resting‐state networks and subjective wellbeing by EEG neurofeedback[J]. Acta Psychiatrica Scandinavica, 2014, 130(2): 123–136. doi: 10.1111/acps.12229.
[23]	DU BOIS N, BIGIRIMANA A D, KORIK A, et al. Neurofeedback with low-cost, wearable electroencephalography (EEG) reduces symptoms in chronic Post-Traumatic Stress Disorder[J]. Journal of Affective Disorders, 2021, 295: 1319–1334. doi: 10.1016/j.jad.2021.08.071.
[24]	MARCU G M, DUMBRAVĂ A, BĂCILĂ I C, et al. Increasing value and reducing waste of research on neurofeedback effects in post-traumatic stress disorder: A state-of-the-art-review[J]. Applied Psychophysiology and Biofeedback, 2024, 49(1): 23–45. doi: 10.1007/s10484-023-09610-5.
[25]	NICHOLSON A A, DENSMORE M, FREWEN P A, et al. Homeostatic normalization of alpha brain rhythms within the default-mode network and reduced symptoms in post-traumatic stress disorder following a randomized controlled trial of electroencephalogram neurofeedback[J]. Brain Communications, 2023, 5(2): fcad068. doi: 10.1093/braincomms/fcad068.
[26]	ROS T, THÉBERGE J, FREWEN P A, et al. Mind over chatter: Plastic up-regulation of the fMRI salience network directly after EEG neurofeedback[J]. Neuroimage, 2013, 65: 324–335. doi: 10.1016/j.neuroimage.2012.09.046.
[27]	CARDONA ALVAREZ Y N. EEG-based BCI monitoring framework: Real-time acquisition and visualization from audiovisual stimulation paradigms[D]. [Master dissertation], Universidad Nacional de Colombia, 2022.
[28]	GEMBORN NILSSON M, TUFVESSON P, HESKEBECK F, et al. An open-source human-in-the-loop BCI research framework: Method and design[J]. Frontiers in Human Neuroscience, 2023, 17: 1129362. doi: 10.3389/fnhum.2023.1129362.
[29]	MEI Jie, LUO Ruixin, XU Lichao, et al. MetaBCI: An open-source platform for brain–computer interfaces[J]. Computers in Biology and Medicine, 2024, 168: 107806. doi: 10.1016/j.compbiomed.2023.107806.
[30]	CARDONA-ÁLVAREZ Y N, ÁLVAREZ-MEZA A M, CÁRDENAS-PEÑA D A, et al. A novel OpenBCI framework for EEG-based neurophysiological experiments[J]. Sensors, 2023, 23(7): 3763. doi: 10.3390/s23073763.
[31]	ERGENOGLU T, DEMIRALP T, BAYRAKTAROGLU Z, et al. Alpha rhythm of the EEG modulates visual detection performance in humans[J]. Cognitive Brain Research, 2004, 20(3): 376–383. doi: 10.1016/j.cogbrainres.2004.03.009.
[32]	何峰, 董博文, 韩锦, 等. 基于头皮脑电的游戏型脑机接口应用研究综述[J]. 电子与信息学报, 2022, 44(2): 415–423. doi: 10.11999/JEIT211337. HE Feng, DONG Bowen, HAN Jin, et al. Advances in application of game brain-computer interface based on ElectroEncephaloGram[J]. Journal of Electronics & Information Technology, 2022, 44(2): 415–423. doi: 10.11999/JEIT211337.