Author(s)

Zihan Li ¹, Tuomeiciren Heyang ², Wenjia Gu ³, Di Ma ⁴

Affiliation(s)

¹ College of Arts, Shinawatra University, Pathum Thani 12160, Thailand
² Chengdu University, Chengdu, Sichuan 610106, China
³ Shangrao Guangxin District Teaching Research Center, Shangrao, Jiangxi 334199, China
⁴ Sichuan Southwest Vocational College of Civil Aviation, Chengdu, Sichuan 610499, China

Corresponding Author

Tuomeiciren Heyang

ABSTRACT

Older adults with mild cognitive impairment (MCI) are at a critical window for interventions addressing cognitive decline. Dance healing can engage cognitive processing through movement, rhythm, space, and interaction, yet its practical implementation still faces challenges, including insufficient individual adaptation, unclear links between cognitive support objectives and implementation phases, and inadequate use of process records and feedback. Grounded in embodied cognition theory, this paper combines literature analysis with theoretical deduction and incorporates suggestions from experts in relevant fields. It emphasizes the supporting role of AI technology throughout model operation and constructs an AI-empowered closed-loop model for dance healing consisting of five functional modules: Assessment Profiling, Regimen Generation, Implementation Embedding, Monitoring and Early Warning, and Feedback Iteration. Guided by the principle of practitioner leadership and AI assistance, the model puts cognitive support objectives into practice throughout the dance healing process and proposes corresponding implementation conditions and governance boundaries.

KEYWORDS

Mild Cognitive Impairment (MCI); Dance Healing; Embodied Cognition; AI Empowerment; Closed-Loop Model

CITE THIS PAPER

Zihan Li, Tuomeiciren Heyang, Wenjia Gu, Di Ma. Construction of an AI-Empowered Closed-Loop Model for Dance Healing: Cognitive Support for Older Adults with Mild Cognitive Impairment. Applied & Educational Psychology (2026). Vol. 7, No. 1, 172-180. DOI: http://dx.doi.org/10.23977/appep.2026.070119.

REFERENCES

[1] Petersen RC, Smith GE, Waring SC, et al. Mild cognitive impairment: clinical characterization and outcome[J]. Archives of Neurology,1999,56(3):303-308. DOI:10.1001/archneur.56.3.303.
[2] World Health Organization. Risk reduction of cognitive decline and dementia: WHO guidelines[M]. Geneva: World Health Organization,2019.
[3] Barsalou LW. Grounded cognition[J]. Annual Review of Psychology, 2008, 59: 617-645. DOI:10.1146/annurev.psych.59.103006.093639.
[4] Toohey B, Moloney G, Hutchinson M. 'I'm still using my body' – dancing with the lived musical body: an interpretative phenomenological analysis of embodied knowledge. Ageing and Society. 2026;46:e3. doi:10.1017/S0144686X25100299
[5] Zhu Y, Wu H, Qi M, et al. Effects of a specially designed aerobic dance routine on mild cognitive impairment[J].Clinical Interventions in Aging,2018,13:1691-1700.DOI:10.2147/CIA.S163067.
[6] Liu C,Su M, Jiao Y, et al. Effects of dance interventions on cognition, psycho-behavioral symptoms, motor functions, and quality of life in older adult patients with mild cognitive impairment: a meta-analysis and systematic review[J].Frontiers in Aging Neuroscience,2021,13:706609.DOI:10.3389/fnagi.2021.706609.
[7] Yuan Y, Li X, Liu W. Dance activity interventions targeting cognitive functioning in older adults with mild cognitive impairment: a meta-analysis[J]. Frontiers in Psychology, 2022, 13: 966675. DOI:10.3389/fpsyg.2022.966675.
[8] Anand S, Schoo C. Mild cognitive impairment[EB/OL]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing, 2026[updated 2024-01-11; cited 2026-06-11].
[9] Waugh M, Youdan G Jr, Casale C, Balaban R, Cross ES, Merom D. The use of dance to improve the health and wellbeing of older adults: a global scoping review of research trials[J]. PLoS One, 2024, 19(10): e0311889. DOI: 10.1371/journal.pone.0311889.
[10] World Health Organization. WHO guideline: recommendations on digital interventions for health system strengthening[M]. Geneva: World Health Organization,2019.
[11] Chen M, Wang H, Yu L, et al. A systematic review of wearable sensor-based technologies for fall risk assessment in older adults[J].Sensors,2022,22(18):6752. DOI:10.3390/s22186752.
[12] He S, Meng D, Wei M, et al. Proposal and validation of a new approach in tele-rehabilitation with 3D human posture estimation: a randomized controlled trial in older individuals with sarcopenia[J].BMC Geriatrics,2024,24:586. DOI:10.1186/s12877-024-05188-7.
[13] World Health Organization. Ethics and governance of artificial intelligence for health: WHO guidance[M]. Geneva: World Health Organization, 2021.
[14] Kip H, Beerlage-de Jong N, van Gemert-Pijnen LJEWC, Kelders SM. The CeHRes Roadmap 2.0: update of a holistic framework for development, implementation, and evaluation of eHealth technologies[J]. Journal of Medical Internet Research, 2025, 27: e59601. DOI:10.2196/59601.
[15] Zhao Yu, Li Zheng. Intervention effect of square dance on elderly community residents with mild cognitive impairment combined with depressive symptoms [J]. Chinese Journal of Gerontology, 2020,40(9):1896-1900.
[16] Koch SC, Riege RFF, Tisborn K, et al. Effects of dance movement therapy and dance on health-related psychological outcomes: a meta-analysis update [J]. Frontiers in Psychology, 2019, 10: 1806. DOI:10.3389/fpsyg.2019.01806.
[17] Schroeder T, Dodds L, Georgiou A, et al. Older adults and new technology: mapping review of the factors associated with older adults’ intention to adopt digital technologies[J].JMIR Aging,2023,6(1):e44564.DOI:10.2196/44564.
[18] Wu C, Lim GG. Investigating older adults users' willingness to adopt wearable devices by integrating the technology acceptance model (UTAUT2) and the Technology Readiness Index theory[J]. Frontiers in Public Health, 2024, 12: 1449594. DOI:10.3389/fpubh.2024.1449594.
[19] Amouzadeh E, Dianat I, Faradmal J, Babamiri M. Optimizing mobile app design for older adults: systematic review of age-friendly design[J]. Aging Clinical and Experimental Research, 2025, 37: 248. DOI:10.1007/s40520-025-03157-7.
[20] World Health Organization Regional Office for Europe. Health data governance in the age of artificial intelligence: policy imperatives for the WHO European Region[R]. Copenhagen: WHO Regional Office for Europe, 2025.
[21] Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment[J]. Journal of the American Geriatrics Society, 2005,53(4):695-699. DOI:10.1111/j.1532-5415.2005.53221.x.
[22] Moore G F, Audrey S, Barker M, Bond L, Bonell C, Hardeman W et al. Process evaluation of complex interventions: Medical Research Council guidance BMJ 2015; 350 :h1258 doi:10.1136/bmj.h1258

Sponsors, Associates, and Links

---

• Advances in Educational Technology and Psychology
  
  
• Curriculum and Teaching Methodology
  
  
• Transactions on Comparative Education
  
  
• Advances in Vocational and Technical Education
  
  
• Adult and Higher Education