Taipei Medical University Promotes Mindfulness Training—Building Better Physical and Mental Health

Source: College of Humanities and Social Sciences

Published on 2020-05-22

With the rapid aging of Taiwan’s population, coupled with a diminishing of economic strength and social resources, even as medical costs keep rising, it becomes ever more important that people take more responsibility for maintaining good health.


Thus, Taiwan is in urgent need of feasible approaches to prevent age-related disabilities so that people can stay physically and mentally active as they age. To achieve this goal, staying healthy can be achieved through advanced healthcare; however, mental health care, especially for middle-aged and elderly populations, is insufficient. In fact, promoting mental health can improve not only one’s physical condition, but also cognitive function. In recent years behavioral studies around the world have pointed out that mindfulness training helps to clear the mind of unwanted, anxiety-inducing thoughts, gradually leading to better mental health.

▓ Promote mindfulness to stay mentally healthy.
Mindfulness is one type of psychological exercise for changing the way people think and bringing one’s attention to ongoing experiences, in the present moment and without judgment. Most importantly, mindfulness practice can help improve attentional and emotional regulation, the key to promoting mental health in modern society. However, mindfulness practice, unlike passive watching of Youtube videos, requires active efforts and proper guidance for the novice. Unfortunately, there are less than hundred certified mindfulness trainers in Taiwan, and a trainer can only teach a small group of people per year. In addition, some people learn with self-guided resources but without proper guidance and sufficient training time. These factors all present inevitable challenges toward promoting mental health through learning mindfulness.

To face these challenges, the research team at TMU tries to build a smart support system for mindfulness training, using brain science and innovative technology. We name this interactive system “Mindfulness with Intelligent Neurofeedback and Disciplinary Virtual Reality (MINDVR)”; it is designed to address the following two challenges:

How does mindfulness change the way people think and improve emotional regulation?
We explore the neurophysiological mechanisms involved in mindfulness-based stress reduction (MBSR) and its effects on emotional regulation through integrated neuroimaging analysis.

How do people conduct mindfulness exercises by themselves at home?
We are building an interactive support system for mindfulness training by integrating virtual reality (VR), neurofeedback (NFB), and artificial intelligence (AI). In this way, people can practice mindfulness meditation with proper guidance through designed programs, similar to Wii games.

The MINDVR system in this study is built to provide guidance for people who practice mindfulness meditation at home and help improve attentional and emotional regulation, which, in turn, can improve the mental health of people around the world.

▓Smart support system for mindfulness training integrated with NFB and VR

The key to suppressing stress through mindfulness training lies in the ability to self-monitor and stay focused, undisturbed by any external or internal disturbances. By doing so, it is anticipated that people can acquire the ability to reflect on themselves and embrace their true selves. Studies show that during mindfulness practices, physiological responses including heart rate, skin-electrode impedance, and even electroencephalogram (EEG) signals will change accordingly. For this reason, various devices and applications for biofeedback can be applied to mindfulness-based exercises today, in order to help people understand and control their physiological responses.

Although physiological responses such as heart rate variability (HRV) can effectively reflect a person’s emotional state, such biofeedback is measured approximately in a sampling rate of 10 seconds. With such detection inefficiency, it is not possible to distinguish the mental shift between cognitive modes from the “Doing” to the “Being” mode, for people in mindfulness practice. The research team must first solve this problem. According to previous studies, during mindfulness practices, EEG signals exhibited alpha-wave asymmetry from the occipital lobe and enhanced beta power from the frontal lobe. Furthermore, EEG signals could, in principle, accurately mark the timing of the mental shift between different cognitive modes. 

In addition to high temporal resolution, spatial localization of the mindfulness-based mode switching is another important feature to take into account. Because of this, the research team utilizes functional magnetic resonance imaging (fMRI) to identify the exact part of the cortex related to MBSR, integrating EEG’s high temporal solution with data in the time and frequency domains to conduct deep learning-based analysis. In this way, researchers are able to identify the best time/space features of EEG data that appear during mindfulness exercises. The goal is to identify neural feedback based on EEG features related to mindfulness so people are able to adjust their training approaches during mindfulness exercises.

On the other hand, to improve the motivation of people practicing mindfulness at home, the research team attempts to integrate the neurophysiological feedback with VR technology, to create immersive visual environments. Users will be able to get away from the hustle and bustle of everyday life and enter the world of mindfulness practice, just like playing video games. This smart interactive system is designed based on brain science, VR technology, and customized neurophysiological feedbacks. The system will assist participants in monitoring and adjusting mindfulness practice approaches that are especially important for novices. We hope that in the near future, it can be used to help middle-aged and elderly population suffering from mental stress.

The MINDVR system will be based on the most advanced brain science and engineering technology. It will use deep learning techniques to generate neurophysiological features and then apply the data in virtual reality through wearable EEG devices. In this way, the integrated system will be able to guide users to perform correct mindfulness exercises and adjust their approaches during the process. The invention of the MINDVR system will undoubtedly benefit a huge group of people worldwide, helping them to relieve them of psychological pressure. Finally, with the guidance of the MINDVR system, middle-aged and elderly people will be able to practice mindfulness as one of their daily activities, thereby improving their mental health and enabling them to achieve the goal of healthy aging.

Illustration: Overview of the MINDVR project: from humanity, neuroimage, artificial intelligence, industrial cooperation to international academic collaborations.

Illustration: MINDVR system: simultaneously combination of biofeedback, neurofeedback and VR technology to assist people in mindfulness practices.

 Research Team

Associate Professor Changwei W. Wu from the Graduate Institute of Mind, Brain, and Consciousness (GIMBC), College of Humanities and Social Sciences, Taipei Medical University.

Prof. Wu’s research project- Cultivation of Mindfulness ‬via the ‬Intelligent Neurofeedback ‬and ‬Disciplinary Virtual Reality (‬MINDVR) ‬Platform on Middle-Aged and Elderly Population received subsidies from the 2019 Taiwan Brain Science Development and Global Expediting Project from the Department of Life Sciences- Ministry of Science and Technology (MOST 108-2321-B-038-005-MY2)

The team members include
– Associate Professor Feng-Ying Huang from the Department of Education, National Taipei University of Education
– Associate Professor Chih-Mao Huang from the Department of Biological Science and Technology, National Chiao Tung University
– Assistant Professor Chun-Hsiang Chuang from the Department of Computer Science and Engineering, National Ocean University
– Assistant Professor Yi-Ping Chao from the Department of Computer Science and Information Engineering, Chang Gung University
– Assistant Professor Chia-Fen Hsu from the Graduate Institute of Behavioral Sciences, Chang Gung University

This article is simultaneously available on QS WOWNews.

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