Bioengineering an AI-augmented platform for remote mental health interventions
• AI-generated summaries reduce therapists’ report-writing time by more than 50%, improving the clinical workflow and documentation efficiency. • The system enables remote EMDR therapy with real-time eye tracking and distance monitoring, ensuring treatment fidelity without requiring specialized hardware. • Emotion recognition using a Swin transformer model trained on Taiwanese datasets achieved an F1 score of 0.831, supporting culturally sensitive facial emotion analysis. • Deployed on the AWS cloud, the platform offers secure, scalable access with no software installation needed, which is ideal for broad implementation. • Early-career therapists reported improved self-reflection (4.3±0.64) and confidence in remote consultation (4.2±0.75), highlighting the system’s impact on professional development. This study developed and tested a new teletherapy system that uses artificial intelligence (AI) to improve remote psychological treatment and reduce therapists’ workload. The system includes a case management platform and a video-based therapy platform with support for remote Eye Movement Desensitization and Reprocessing (EMDR). After each session, the system uses AI tools such as emotion recognition, speech-to-text, and a large language model to automatically create a session summary and report, including emotional changes and a transcript. Real-time eye movement tracking and distance monitoring help standardize remote EMDR procedures. The case management system improves efficiency by helping schedule sessions and reminding clients (rated 4.25±0.83 out of 5). In clinical trials, AI-generated summaries reduced report writing time by over 50%. Less experienced therapists found the emotion recognition tool helpful for self-reflection (4.3±0.64), while experienced therapists believed the EMDR tools improved their remote consultation skills (4.2±0.75). User feedback shows the system is easy to use, with therapists rating it 4.83 and clients 4.33 for ease of use. Overall, the system improves access to mental health services, increases workflow efficiency, and supports professional development in digital therapy.
Authors
- Yi‐Chung Chen (ORCID: https://orcid.org/0000-0003-0353-7340)
- J Wu (ORCID: https://orcid.org/0009-0007-5288-7917)
- Lun‐De Liao (ORCID: https://orcid.org/0000-0002-2601-3673)
- Huimin Wang (ORCID: https://orcid.org/0000-0002-4692-4917)
- Congo Tak‐Shing Ching (ORCID: https://orcid.org/0000-0001-9796-9827)
- Yujie Chen (ORCID: https://orcid.org/0000-0002-9905-9138)
- Kuang Lin (ORCID: https://orcid.org/0000-0003-3017-6026)
- Yang-Chou Juan
Institutions
- National Chung Hsing University (TW)
- National Health Research Institutes (TW)
Publication Details
- Journal
- Results in Engineering
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1016/j.rineng.2025.105931
- Citations
- 1
- Primary Topic
- Telemedicine and Telehealth Implementation
- Type
- article
- Field-Weighted Citation Impact
- 1.88
Funders
- Ministry of Health and Welfare
- National Health Research Institutes
- National Chung-Hsing University