Integrated Biosignal Analysis to Provide Biomarkers for Recognizing Time Perception Difficulties

Area of Science:

• Neuroscience
• Biomedical Engineering
• Psychophysiology

Background:

• Time perception is crucial for cognitive function.
• Dyschronometria, a cerebellar dysfunction, impairs time estimation.
• Cardiac indicators like heart rate variability and biosignals (EEG, ECG, EMG) are linked to cognitive processes.

Purpose of the Study:

• To evaluate human time perception using neurological, cardiovascular, and muscular systems.
• To investigate electroencephalogram (EEG), electrocardiogram (ECG), and electromyography (EMG) as biomarkers for time perception difficulties.
• To explore the integration of these biosignals in assessing neurofeedback training efficacy.

Main Methods:

• Integrated EEG, ECG, and EMG recordings during time perception tasks.
• Utilized a simple neurofeedback exercise post-time perception tasks.
• Recorded biosignals from five healthy college students during rest, time estimation, and neurofeedback.

Main Results:

• Electrocardiogram (ECG) heart rate (HR), EEG Delta wave, and EMG root mean square (RMS) were identified as critical features.
• These biosignals are significant indicators of time perception difficulties.
• Established a connection between ECG, EEG, and EMG under time perception conditions.

Conclusions:

• Multiple biomarkers can enhance the diagnosis and monitoring of time perception disorders.
• These biomarkers are valuable for evaluating and treating dyschronometria.
• Biofeedback training shows potential for improving time perception.