Evaluation of the Effectiveness of the Elderly Cognitive and Exercise Forest Therapy Program According to Brain Wave and Autonomic Nervous System Parameters

Author:

Seo Jeong-Woo1ORCID,Kim Kahye1,Kim Seul Gee1ORCID,Yi Jiyune2,Shin Wonsop2ORCID,Choi Jungmi3ORCID,Kim Jaeuk U.14ORCID

Affiliation:

1. Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34504, Republic of Korea

2. Department of Forest Therapy, Graduate School of Chungbuk National University, Chungju 28644, Republic of Korea

3. Human Anti-Aging Standards Research Institute, Uiryeong 52151, Republic of Korea

4. Korean Convergence Medicine, University of Science and Technology, Daejeon 34504, Republic of Korea

Abstract

The purpose of this study is to more quantitatively identify changes in body function through various bio-signal parameters. (1) Background: Forest therapy is effective in stabilizing cognitive, emotional, cardiovascular, and autonomic nervous systems. In particular, it is necessary to more quantitatively confirm changes in body functions through various bio signals. (2) Methods: As a forest therapy program (FTP) for the elderly, it consisted of strength training in the forest, respiratory aerobic exercises, and cognitive function training, and a total of 19 sessions were performed for 12 weeks. The electroencephalography (EEG) and Photoplethysmography (PPG) before and after the program were measured and compared between program participants (FTP group) and non-participants (control group). (3) Results: the FTP group showed increase in the alpha band power in EEG and a decrease in the PRV index, Tad, and Tae after the program compared to the control group; (4) Conclusions: Significant differences occurred in the physiological functioning of the elderly participants after the program. This is a result that can confirm the effectiveness of forest therapy more quantitatively. Forest therapy has a positive effect on mental stress reduction and cardiovascular function.

Funder

KIOM

Korea Forest Service

Publisher

MDPI AG

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