JMIR Research Protocols

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Electrophysiological Insights in Exergaming—Electroencephalography Data Recording and Movement Artifact Detection: Systematic Review

Our research focuses on evaluating Hap Hop-Physio’s effectiveness through electroencephalography (EEG) [22]. EEG is one of the most commonly used methods for inspecting electrical activity in the brain by recording brain signals with electrodes placed on the scalp [24,25]. EEG is increasingly used in studies on infant development [23]. EEG captures voltage fluctuations resulting from ionic currents within neurons, which produces signals that represent various brain waves.

Carolina Rico-Olarte, Diego M Lopez, Bjoern M Eskofier, Linda Becker

JMIR Serious Games 2025;13:e50992

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Integrating Virtual Reality, Neurofeedback, and Cognitive Behavioral Therapy for Auditory Verbal Hallucinations (Hybrid): Protocol of a Pilot, Unblinded, Single-Arm Interventional Study

Neurofeedback has most commonly been provided via electroencephalography (EEG) or real-time functional magnetic resonance imaging (rtf MRI). In an example of EEG neurofeedback, individuals receive real-time information on their brain activity, often presented as a bar graph, where the height of the bar represents the power of oscillatory activity in a given frequency band (eg, α or β) measured in terms of power (ie, amplitude squared).

Jessica Spark, Elise Rowe, Mario Alvarez-Jimenez, Imogen Bell, Linda Byrne, Ilvana Dzafic, Carli Ellinghaus, Suzie Lavoie, Jarrad Lum, Brooke McLean, Neil Thomas, Andrew Thompson, Greg Wadley, Thomas Whitford, Stephen Wood, Hok Pan Yuen, Barnaby Nelson

JMIR Res Protoc 2025;14:e63405

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Monitoring Sleep Quality Through Low α-Band Activity in the Prefrontal Cortex Using a Portable Electroencephalogram Device: Longitudinal Study

In this study, we aimed to explore the relationship between different frequency components of portable EEG and sleep quality, and whether a stable neurobiological feature strongly associated with sleep quality can be found through portable EEG. First, we collected a batch of portable EEG data from participants in the first month and identified some features as potential targets that are significantly correlated with sleep quality.

Chuanliang Han, Zhizhen Zhang, Yuchen Lin, Shaojia Huang, Jidong Mao, Weiwen Xiang, Fang Wang, Yuping Liang, Wufang Chen, Xixi Zhao

J Med Internet Res 2025;27:e67188

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Peer Review of “State Anxiety Biomarker Discovery: Electrooculography and Electrodermal Activity in Stress Monitoring (Preprint)”

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Daniela Saderi, Shailee Rasania, Toba Olatoye, Simon Muhindi Savai, Randa Salah Gomaa Mahmoud, Vasco Medeiros, Mitchell Collier

JMIRx Med 2025;6:e72093

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Measuring Bound Attention During Complex Liver Surgery Planning: Feasibility Study

The design of the EEG task follows a standard passive auditory oddball paradigm, in which both a frequent and a rare auditory stimulus are presented.

Tim Schneider, Timur Cetin, Stefan Uppenkamp, Dirk Weyhe, Thomas Muender, Anke V Reinschluessel, Daniela Salzmann, Verena Uslar

JMIR Form Res 2025;9:e62740

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Accuracy of Machine Learning in Detecting Pediatric Epileptic Seizures: Systematic Review and Meta-Analysis

Electroencephalography (EEG) has been established as an electrographic recording technique of brain activity, capable of timely predicting the occurrence of epileptic seizures from scalp EEG signals. This allows for more proactive and effective intervention for patients, making it an effective tool for the evaluation and diagnosis of epilepsy [5]. EEG is currently the gold standard for diagnosing neonatal epilepsy [6].

Zhuan Zou, Bin Chen, Dongqiong Xiao, Fajuan Tang, Xihong Li

J Med Internet Res 2024;26:e55986

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Neurological Evidence of Diverse Self-Help Breathing Training With Virtual Reality and Biofeedback Assistance: Extensive Exploration Study of Electroencephalography Markers

In this study, we attempted to use EEG to examine the neurobiological mechanism differences of different breathing training techniques in an integrated VR and BF environment. EEG is commonly applied in breathing training studies, as it can easily be integrated with other modalities, such as VR and breath signal sensors [13]. Previous EEG studies on breathing training with VR and BF also demonstrated that EEG suitably works with VR-BF equipment without significant interference [10,64].

Hei-Yin Hydra Ng, Changwei W Wu, Hao-Che Hsu, Chih-Mao Huang, Ai-Ling Hsu, Yi-Ping Chao, Tzyy-Ping Jung, Chun-Hsiang Chuang

JMIR Form Res 2024;8:e55478

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Linking Dementia Pathology and Alteration in Brain Activation to Complex Daily Functional Decline During the Preclinical Dementia Stages: Protocol for a Prospective Observational Cohort Study

Reference 7: EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive Reference 66: Event-related EEG/MEG synchronization and desynchronization: basic principles Reference 82: Validating the boundary element method for forward and inverse EEG computations in the Reference 83: Independent EEG sources are dipolar Reference 88: Auditory event-related dynamics of the EEG spectrum and effects of exposure to toneseeg

Pierfilippo De Sanctis, Jeannette R Mahoney, Johanna Wagner, Helena M Blumen, Wenzhu Mowrey, Emmeline Ayers, Claudia Schneider, Natasha Orellana, Sophie Molholm, Joe Verghese

JMIR Res Protoc 2024;13:e56726

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Design and Implementation of a Brief Digital Mindfulness and Compassion Training App for Health Care Professionals: Cluster Randomized Controlled Trial

Assessments were deployed on the Brain E platform with simultaneous EEG [43], delivered on a laptop (running on the Windows 10 operating system) at a comfortable viewing distance. The Lab Streaming Layer protocol was used to time stamp all user response events in this assessment [44]. In the interoceptive attention to breathing task, participants were instructed to close their eyes, breathe naturally, and respond every 2 breaths by tapping on the spacebar [45,46].

Satish Jaiswal, Suzanna R Purpura, James K Manchanda, Jason Nan, Nihal Azeez, Dhakshin Ramanathan, Jyoti Mishra