An Experimental Study on the Effects of Deep Touch Pressure on Emotion Soothing

  • Qin Huang
  • Tashinga Walter Matiki
Keywords: Pressure Vest; Stress; Anxiety; Depression; Deep Pressure

Abstract

Stress, anxiety, and depression are normal reactions to a variety of stressors and have a detrimental effect on mental or physical well-being. An experimental study on the effects of deep touch pressure on emotion soothing was carried out. The study used an automated pressure vest and measured participants' vital signs and emotions before and after being exposed to a stressor. Secondly, an automatic pressure vest was used to explore the effects of deep touch pressure on emotion soothing. The State-Trait Anxiety Inventory, a self-rating anxiety scale, and electroencephalogram (EEG) readings measure deep touch pressure effects on anxiety reduction. The research found that the pressure vest helped to reduce stress and improve relaxation. It also found that the pressure vest induced a high theta in the prefrontal lobe of the brain, indicating that the participants became more relaxed. The study suggests that deep touch pressure may be an effective, non-pharmacological method for reducing stress, anxiety, and depression.

References

Baez-Lugo S. et al., "Exposure to negative socio-emotional events induces sustained alteration of resting-state brain networks in older adults," Nature Aging, vol. 3, no. January, 2023.

O'Connor DB, Thayer JF., and Vedhara K, "Stress and Health: A Review of Psychobiological Processes," (in eng), Annual review of psychology, vol. 72, pp. 663-688, 2021.

S. M. M. G. E. D. C. R. K. Edelson and G. Temple, ""Behavioral and physiological effects of deep pressure on children with autism: A pilot study evaluating the efficacy of Grandin’s Hug Machine."," The American Journal of Occupational Therapy 53, pp. 145-152, 1999.

Muhammad S and Sajjad K, "Methods of data collection," 2016, pp. 202-276.

Alarcão SM and Fonseca MJ, "Emotions recognition using EEG signals: A survey," IEEE Transactions on Affective Computing, vol. 10, no. 3, pp. 374-393, 2019.

Wang XW, Nie D, and Lu BL, "EEG-based emotion recognition using frequency domain features and support vector machines," Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7062 LNCS, no. PART 1, pp. 734-743, 2011.

Lagopoulos J. et al., "Increased theta and alpha EEG activity during nondirective meditation," Journal of Alternative and Complementary Medicine, vol. 15, no. 11, pp. 1187-1192, 2009.

Published
2023-09-15
Section
Original Research Article