Cultivation‭ ‬Of Mindfulness‭ ‬Via‭ ‬The‭ ‬Intelligent Neurofeedback‭ ‬And‭ ‬Disciplinary‭ ‬ Vi Rtual Reality‭ (‬Mindvr‭)‬‭ ‬Platform‭ ‬On Middle-Aged and Elderly Population(2/2)

Project: A - Government Institutionb - Ministry of Science and Technology

Project Details

Description

With its rapidly aging population (by 2025, 20% of the population will be ≧65 years old), Taiwanese middle-aged and older adults are especially vulnerable to negative effects of multifaceted psychological stressors from workload, loneliness, or even bereavements, which poses a serious threat to senior’s mental health and even to the national welfare. Under such circumstance, the mindfulness-based intervention is designed to enhance the practitioner’s abilities to be present in the moment, accept things as they are and act appropriately regarding the difficulties of daily life based on reality, which improves their mental health of mindfulness practitioners toward successful aging. However, beyond its efficacy in improving mental health, the mindfulness intervention in current Taiwan society is facing multiple challenges such as insufficient number of qualified trainers, inaccurate mindfulness practices and implicit mind shifting. Even though the booming mindfulness-assisted wearable devices are plausible solutions to facilitate mindfulness practices, most biofeedback devices are unable to capture the subtle transitions of brain mental states during the mindfulness practices. Therefore, to achieve righteous mindfulness practices for the general middle-aged and elderly populations, we determine to build up a user-friendly platform for personalized mindfulness training on the basis of concentration enhancement (with immersive virtual environments) and accurate real-time neurofeedback (by disclosing neurophysiological mechanisms behind mindfulness practices). To alleviate the psychological stress using accurate mindfulness practices, this research team will proudly present one novel integrated platform of Mindfulness with Intelligent Neurofeedback and Disciplinary Virtual Reality (MINDVR) to assist mindfulness practitioners. The new platform originates from brain mechanisms by extracting temporal features based on spatial constraints, and then applies to neurofeedback with virtual reality (VR). We plan to recruit forty experienced mindfulness practitioners and sixty novice practitioners with 8-week mindfulness intervention for both training and testing in the current proposal. Specifically, the project will be initiated by differentiating mindfulness practices into four phases: mindfulness of breath, body scan, mindfulness of emotions, and compassion (subproject 1). Participants will be performing different phases of mindfulness practices and corresponding cognitive tasks (subproject 5), meanwhile performing the simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) recordings to extract the brain locations and temporal features, correspondingly (subproject 2). The targeting EEG temporal biomarkers will be extracted using deep learning for improving the quality of mindfulness practices (subproject 3). After synchronizing the EEG signals and the physiological signals (e.g., heartbeat pulsation), we will integrate biomarkers into a VR environment for practitioners to self-regulate one’s own mindfulness way of living (subproject 4). The research team will be collaborated with two highly recognized international scholars: Professor Richard J. Davidson (UW-Madison) and Scott Makeig (UCSD), and be supported by well-known industrial partners, including HTC Corporation (VR), MediaTek Inc. (biosensing IC), ArtiseBio (EEG) and Rooti Lab Limited (wearable device), toward benefiting the mental health for middle-aged and senior populations in an integrated team work.
StatusActive
Effective start/end date6/1/2012/1/20

Keywords

  • Mindfulness
  • attention
  • emotion
  • mindfulness-based stress reduction (MBSR)
  • electroencephalography (EEG)
  • heart rate variability (HRV)
  • functional magnetic resonance imaging (fMRI)
  • virtual reality (VR)
  • deep learning