Key result
Mental stress assessment using the EHR¯ signal achieved an accuracy of 97.3 ± 0.9%, outperforming fNIRS, RHR, and EHR signals by 13%, 30.8%, and 1.8%, respectively.
Why the study?
It was hypothesized that heart rate signals extracted from functional near-infrared spectroscopy include physiological information beyond heart rate, specifically functional brain responses, after removing global systemic changes.
Processed heart rate signals extracted from fNIRS contain brain-related functional responses that can accurately assess mental stress levels.
EHR from fNIRS may capture brain functional responses beyond HR; hypothesis-generating for mental state assessment in small cohorts.
Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive technique for studying brain hemodynamics. Since brain hemodynamics also involves components from the heart rate (HR), it is possible to extract the HR signal from the fNIRS (EHR). By removing global systemic changes from the EHR, we hypothesized that the EHR includes physiological information beyond HR, which is the functional response of the brain. To evaluate this hypothesis, the mental states of 10 healthy subjects were assessed under a stressful condition induced using the Montreal Imaging Stress Task (MIST). EHR and Reference HR (RHR) signals were then extracted from fNIRS and ECG, respectively. Next, a method based on Independent Component Analysis (ICA) was applied in order to discriminate the independent sources in the EHR signal. Thereafter, the least correlated components with RHR were reconstructed, which is the so-called target signal of EHR¯. Similarity measurement of EHR¯ with fNIRS signals revealed a significant correlation between them. To show the effectiveness of the existing information in EHR¯ signals, they were employed for mental stress assessment by using the SVM classifier, leading to an accuracy of 97.3 ± 0.9%, which was 13%, 30.8% and 1.8% greater than those of the fNIRS, RHR, and EHR signals, respectively. We showed not only that the EHR¯ signal is a brain-related response, but also that it contains useful information for mental stress level measurement. Moreover, it is concluded that the EHR signal includes information from both brain and heart, which is hence useful for applications in which brain and heart functions are altered.
No takes yet. Share an insight, caveat, or question.
Mirbagheri et al. (2019) studied Healthy subjects (mental stress assessment) (n=10). EHR¯ signal (fNIRS-derived heart rate with global systemic changes removed) vs. fNIRS, RHR (ECG-derived), and EHR signals was evaluated on Mental stress assessment accuracy using SVM classifier. Mental stress assessment using the EHR¯ signal achieved an accuracy of 97.3 ± 0.9%, outperforming fNIRS, RHR, and EHR signals by 13%, 30.8%, and 1.8%, respectively.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: