Background

Sound therapy is currently being explored as a promising way to promote mental health and well-being. Sound stimulation (music, nature sounds, etc.) shows positive results in clinic: from improving cognitive functions in Alzheimer's patients to reducing pain during surgery (Clements-Cortes & Bartel 2015; Nilsson et al. 2005). There is a growing body of evidence that sound therapy (i.e., music and poetry therapy) is effective in reducing stress and anxiety (Mohammadian et al. 2011; Jabarouti & Shariat 2013; Noel 2010; Maess, Koelsch, et al., 2001). At the same time, the mechanism of sound therapy is not well-understood. In current studies, music or poetry is seen more as a holistic phenomenon. Its influence was known in human culture long before it was supported by neuroscience research. In this way, we might miss hidden active components that may be present not only in specific arts but also in other types of sound stimulation, like normal human speech. For example, there is clinical evidence, that Lullaby performed only by voice (without music, through the headsets) could significantly reduce heart rate and increase blood oxygen saturation of neonates in the clinic (Taheri et al., 2016). However, it is not clear whether the therapeutic effect originated from the melody, or the human voice itself.

In our research, we focus on the effect of sound stimulation on the stress response as a universal component accompanying a wide range of physical and mental disorders. Stress is well known for its integrative physiological effects: it involves the whole body through sympathetic activation and changing biochemical balance. We need to find out the underlying mechanism behind sound therapy. Through this, we want to explore the therapeutic potential of human speech as the most common way of communication and mutual influence.

Research Question

The main Research Question is: how functional states of the brain (increase or decrease in stress response) can be influenced by nonverbal components of human speech (musical elements of speech (melody and rhythm) & socio-communicative elements (intonation, affective prosody)).

Method

fNIRS brain imaging + multimodal physiological sensing

Selected Publications

• Saskovets M, Liang Z, Piumarta I. (2024) The Utility of fNIRS for Evaluating Human Voice Acoustics for Stress Management. In Proceedings of the VIII Biennial Meeting of the Society for functional near-infrared spectroscopy (SfNIRS 2024), Birmingham, UK.

• Saskovets M, Liang Z, Piumarta I. (2024) The Effect of Soothing Human Voice on the Stress Response. In Proceedings of the joint meeting of the 47th Annual Meeting of the Japan Neuroscience Society (JNS), the 67th Annual Meeting of the Japanese Society for Neurochemistry (JSN), the 46th Annual Meeting of the Japanese Society of Biological Psychiatry (JSBP), and the 8th Federation of Asian-Oceanian Neuroscience Societies (FAONS) Congress (NEURO 2024), Fukuoka, Japan. 

• Saskovets M, Liang Z. (2023) Validation of a New Stress Induction Protocol using Speech Improvisation in Front of Audience: an fNIRS Pilot Study. The 2023 International Artinis (f)NIRS Symposium, Bangkok, Thailand.

Objective

 To explore stress-related abnormality in brain activity especially during sleep.

Method

• Design and perform data collection experiment using wearable fNIR (Artinis Brite 24), smartwatches (Fitbit), wearable rings (OURA), continuous glucose monitor (FreeStyle Libre) and salivary biochemical test (SOMA cube; cortisol & sIgA)

• Multimodal data retrieval, integration, and preprocessing

• Multimodal physiological data analysis using statistical techniques, signal processing, spatio-temporal time series analysis, machine learning and data mining

Contributors

Dr. Zilu Liang

Selected Publications

• Liang Z. (2022). Not Just a Matter of Accuracy: A fNIRS Pilot Study into Discrepancy Between Sleep Data and Subjective Sleep Experience in Quantified-Self Sleep Tracking. In: Spinsante, S., Silva, B., Goleva, R. (eds) IoT Technologies for Health Care. HealthyIoT 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 432. Springer, Cham.  [SCI/Scopus]     

• Liang Z. (2021) What does sleeping brain tell about stress? A pilot fNIRS study into stress-related cortical hemodynamic features during sleep. Frontiers in Computer Science (Section: Mobile and Ubiquitous Computing) 3:774949. Doi: 10.3389/fcomp.2021.774949. 

• Liang Z. (2021) An N-of-1 investigation into stress-related hemodynamics in the prefrontal cortex during the first sleep cycle. In Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2021), Melbourne, Australia. [SCI/Scopus]