Scholarlink

With growing mental health challenges among populations and limited access to in-person therapy, there is a critical need for accessible, personalized, and non-pharmacological interventions. To address this, we developed the Synergy-based Intuitive Virtual and Augmented Therapy for Mental Health (SIVAM) platform, a real-time home-deployable system that delivers emotionally responsive dance movement therapy (DMT). SIVAM integrates full-body and hand motion capture, avatar-based interaction, and humanoid robot mirroring, while simultaneously recording multimodal physiological signals (EEG, EMG, ECG, GSR, temperature). By extracting motor synergies and affective biomarkers, the system aims to adapt choreography and feedback to the user’s emotional and physical state. The platform demonstrates low-latency communication, high-fidelity mapping of body landmarks to avatars and robots, and seamless synchronization between movement and biofeedback. A pilot study confirmed SIVAM’s effectiveness across user profiles, supporting its potential as an emotion-aware, scalable therapeutic solution tailored to the need of individuals.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

SIVAM: Synergy-Based Intuitive Virtual and Augmented Therapy for Mental Health

  • 章节

  • 发表日期：

    2026年

查看全文
  • Parthan Olikkal,
  • Oritsejolomisan Mebaghanje,
  • Viraj Janeja,
  • Golnaz Moharrer,
  • Akshara Ajendla,
  • Sruthi Sundharram,
  • Andrea Kleinsmith,
  • Ann Sofie Clemmensen,
  • Ramana Vinjamuri

摘要

With growing mental health challenges among populations and limited access to in-person therapy, there is a critical need for accessible, personalized, and non-pharmacological interventions. To address this, we developed the Synergy-based Intuitive Virtual and Augmented Therapy for Mental Health (SIVAM) platform, a real-time home-deployable system that delivers emotionally responsive dance movement therapy (DMT). SIVAM integrates full-body and hand motion capture, avatar-based interaction, and humanoid robot mirroring, while simultaneously recording multimodal physiological signals (EEG, EMG, ECG, GSR, temperature). By extracting motor synergies and affective biomarkers, the system aims to adapt choreography and feedback to the user’s emotional and physical state. The platform demonstrates low-latency communication, high-fidelity mapping of body landmarks to avatars and robots, and seamless synchronization between movement and biofeedback. A pilot study confirmed SIVAM’s effectiveness across user profiles, supporting its potential as an emotion-aware, scalable therapeutic solution tailored to the need of individuals.