Physiological assessment of the psychological flow state using wearable devices.
Melinda Rácz, Melinda Becske, Tímea Magyaródi, Gergely Kitta, Márton Szuromi, Gergely Márton
Scientific Reports April 7, 2025 DOI: 10.1038/s41598-025-95647-x (opens in new tab) via PubMed
Summary
AI-generated from the abstractFlow, the state of optimal experience linked to outstanding performance, can be detected and monitored with wearable devices. In an experiment with 28 Hungarian adults playing a game at varying difficulty to induce flow and anti-flow states, electroencephalography, heart rate, blood oxygen saturation, galvanic skin response, and head and hand motion were measured. During flow, alpha and theta brainwave power dominated, supporting the transient hypofrontality hypothesis. Heart rate variability showed a U-shaped characteristic, while blood oxygen saturation and its variability displayed inverse U-shaped and U-shaped patterns, respectively. Subjects were least physically active in flow and most active in boredom, indicating that lightweight wearables can monitor mental state for improving well-being.
Study at a glance
| Characteristics | Experimental study Peer reviewed |
|---|---|
| Sample size | 28 |
| Population | Hungarian adults |
| Keywords | Electroencephalography Motion tracking Photoplethysmography Psychological flow Tetris |
| Key finding | Flow states can be detected and monitored using wearable devices, with alpha and theta brainwave power dominating during flow and subjects being least physically active. |
Abstract
Flow is the state of optimal experience which can lead to outstanding performance. Our study demonstrates the feasibility of detecting and monitoring flow using wearable devices. Twenty-eight Hungarian adults participated in the experiment. They played a game at different levels to induce flow and anti-flow states, which was tested with questionnaires. We measured electroencephalography (EEG), heart rate (HR), blood oxygen saturation (SpO2) and galvanic skin response (GSR) signals as well as head and hand motion. We isolated EEG delta, theta, alpha and beta band power, HR, SpO2 and GSR average and standard deviation, as well as acceleration and angular velocity standard deviation. In flow condition, alpha and theta power were the dominant components, in accordance with the transient hypofrontality hypothesis. We also replicated the U-shaped characteristic of the heart rate variability; in addition, we propose an inverse U-shaped and a U-shaped characteristic for SpO2 and SpO2 variability, respectively. On the basis of motion tracking, subjects were the least physically active in flow, signifying a focused state, and the most active in boredom. Our results support the applicability of lightweight, wearable devices for monitoring mental state that can be utilized to improve well-being at work or in everyday situations.