The Efficacy of a Home-Based, Augmented Reality Dual-Task Platform for Cognitive-Motor Training in Elderly Patients: A Pilot Observational Study

Article information

Psychiatry Investig. 2024;21(10):1045-1053

Publication date (electronic) : 2024 September 30

doi : https://doi.org/10.30773/pi.2024.0103

Bora Yoon ¹

, Jihye Park ²

, YongSoo Shim^,³

¹Department of Neurology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea

²Department of Rehabilitation Medicine, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea

³Department of Neurology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea

Correspondence: YongSoo Shim, MD, PhD Department of Neurology, College of Medicine, The Catholic University of Korea, 1021 Tongil-ro, Eunpyeon-gu, Seoul 03312, Republic of Korea Tel: +82-2-2030-4616, Fax: +82-2-2030-4617, E-mail: ysshim@catholic.ac.kr

Received 2024 March 20; Revised 2024 May 28; Accepted 2024 June 18.

Abstract

Objective

This study introduces a novel home-based dual-task platform incorporating augmented reality (AR), COGNIMO, aimed at simultaneously enhancing cognition and physical abilities. The purpose of this study was to assess the effectiveness of this intervention in enhancing cognitive and physical abilities in elderly individuals with subjective cognitive decline, mild cognitive impairment (MCI), and mild Alzheimer’s dementia.

Methods

A 12-week observational study enrolled 57 participants aged 60–85 years. Primary outcomes included changes in cognitive scores (Korean Mini-Mental State Examination, 2nd edition [K-MMSE-2] and Korean-Montreal Cognitive Assessment [K-MoCA]), while secondary outcomes measured physical parameters and depression scores between baseline and week 12 in the active and the control groups.

Results

Of 57 participants, 49 completed the study. The active group (≥12 sessions) exhibited significant improvement in K-MoCA compared to the control group (<12 sessions) (p=0.004), while K-MMSE-2 score changes showed no significant difference (p=0.579). Positive correlations between training sessions and K-MoCA changes were observed (r=0.31, p=0.038), emphasizing a dose-response relationship. Subgroup analyses revealed a distinction in cognitive changes, particularly in the MCI group.

Conclusion

The COGNIMO platform showed positive effects on cognitive function in MCI patients, suggesting potential benefits for this population. The study highlights the potential of AR-integrated home-based interventions for cognitive enhancement in elderly individuals, underlining the need for further trials in the future.

Keywords: Augmented reality; Home-based; Cognitive training; Mild cognitive impairment; Montreal cognitive assessment; Exercise

INTRODUCTION

With the growth of the aging population, there is a concurrent increase in the prevalence of dementia [1]. This upward trend is notably amplified in South Korea due to its rapid population aging, which suggests a rise from 10.3% in 2020 to an anticipated 15.9% by 2050 among individuals aged 65 or older [2]. Given the lack of currently approved disease-modifying therapies for Alzheimer’s dementia (AD), the surge in the number of dementia patients has resulted in increasing socioeconomic burdens. In response, various non-pharmacological treatments (NPT) aimed at prevention, delaying onset, or slowing progression are being explored [3]. Among these, cognitive training and physical exercise have been considered beneficial in some patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI) and very early stages of dementia [4]. In older adults with SCD, cognitive training interventions led to improvements in memory, attention, and executive function as well as physical exercise, particularly aerobic exercise, was associated with improvements in cognitive performance and a reduction in perceived cognitive decline in this population [5,6]. In the context of MCI and early stages of dementia, combined cognitive and physical interventions have demonstrated the potential to enhance global cognitive function, subsequently improving activities of daily living (ADLs) and mood in older adults with MCI or dementia [7]. A meta-analysis by Zhu et al. [8] highlighted the considerable benefits of combined cognitive and physical interventions on overall cognitive function in healthy older adults. Although cognitive-motor dual-task training that is performed simultaneously rather than sequentially has shown effectiveness in promoting cognitive and physical functions [9], successful execution of simultaneous training is often not practical. Moreover, most traditional interventions have required in-person guidance, entailing considerable time, cost, and resources. However, since the start of the coronavirus disease-2019 (COVID-19) pandemic, it exacerbated the situation, leaving dementia patients isolated at home, leading to a decline in cognitive, physical, or social function, and deteriorating dementia conditions [10]. Even beyond the COVID-19 pandemic, the requirement for remote interventions and remote care services remains prominent. In this context, home-based cognitive or physical training tools could emerge as attractive alternatives for intervention. Although there are individual cognitive training or physical exercise applications, dual-task methods enabling simultaneous cognitive and physical training for elderly people remain scarce yet. Moreover, they have limitations such as one-way content based on photos or videos, content complexity unsuited for elderly individuals, or the requirement for expensive motion recognition equipment. To address these gaps, we developed an elderly people-friendly, tablet-based, home-based dual-task service platform that enables concurrent cognitive and physical training with augmented reality (AR) and motion recognition. The aim of this study was to investigate the potential effectiveness and benefits of this novel home-based dual-task platform with AR, in enhancing both cognitive and physical abilities among elderly patients, particularly focusing on mild AD, MCI, and SCD.

METHODS

Participants

We consecutively enrolled a total of 57 patients in this 12-week observational study. The trial was registered with the Clinical Research Information Service (http://cris.nih.go.kr) with ID No. KCT0007765. The sponsor was not involved in the study design or operational procedures. Ethical approval was obtained from the institutional review boards at the participating institutions (IRB file no. PC22ONSI0137 at Eunpyeng St. Mary’s Hospital). Informed consent was obtained from all participants after a comprehensive explanation of the study’s objectives and protocols. Participants were also informed of their right to withdraw from the trial at any point during its duration.

Eligible participants were aged 60–85 years and diagnosed with SCD [11], MCI based on Petersen’s criteria [12], or probable AD based on the diagnostic NINCDS-ADRDA criteria [13]. Participants with SCD were those with self-perceived cognitive decline over time but normal cognitive performance and who had scores on the comprehensive neuropsychological tests that are -1.5 standard deviations (SD) or more from the mean [14]. An MCI diagnosis was characterized by 1) memory complaints by participants or caregivers; 2) objective memory impairment as evidenced by scores >-1.5 SD from the mean of age-appropriate norms on the delayed verbal–memory recall tests of either the Seoul Neuropsychological Screening Battery II [15] or the Literacy Independent Cognitive Assessment [16]; 3) normal general cognitive function as assessed by a score on the Korean Mini-Mental State Examination, 2nd edition (K-MMSE-2) [17] <-1.5 SD from the age- and education-adjusted normative means, and a clinical dementia rating (CDR) [18] score of 0.5; 4) preserved ADL; and 5) no dementia. For an AD diagnosis, mild cases (CDR score of 0.5 or 1) were additionally considered. We excluded participants who were unable to walk independently; those with aphasia or language problems; those with blindness or impaired visual acuity hindering a tablet use; those with hearing difficulties that would affect understanding tablet-based instructions; those who were uneducated or illiterate; and those with other neurological, psychological, or metabolic disorders that impacted cognitive function.

A home-based, AR dual-task platform

The home-based, AR dual-task platform, named the COGNIMO program, which is still unavailable for commercial use, was employed for this study. Developed by a multidisciplinary team consisting of two neurologists, a physiatrist, a psychologist, and a computer graphics team, the COGNIMO program aims to effectively target cognitive training and physical exercise domains. This collaboration was established in January 2021, focusing on designing engaging cognitive and physical exercises that are safe for elderly patients. The program regimen includes warming-up exercises, aerobic exercises, cognitive training tasks, strength and resistance exercise, and cool-down activities, referencing the previous study [19]. Careful consideration was given to selecting movements that were both effective and safe as well as easy to follow for elderly patients. Cognitive training tasks encompassed diverse domains such as attention, working memory, visuospatial perception and construction, episodic memory, frontal executive function, and language. For instance, the tasks of the program include matching color and shape pairs, identifying the identical card images, finding another one of four cards, selecting objects’ names, remembering a picture, drawing a clock, a Stroop Test, and Trail Making Tests (Figure 1). The program spans a total of 42 minutes. A detailed description of the program content is outlined in Table 1.

Figure 1.

Example of our platform program. A: First, touch in order the numbers in the circle, and then touch in order the numbers in the square. Touch the circle and square alternately, in that order. B: Reach out and select a picture of the movement required to accomplish the given task. For example, to win against the “Rock” of the picture, touch “Paper” among the three pictures. C: In accordance with the suggested time, open your arms to the clock displayed on the screen to indicate the time.

Table 1.

Contents of the dual-task training service platform

Upon obtaining informed written consent, participants were comprehensively acquainted with the procedure details and provided guidance on how to use the tablet and access the program. Baseline cognitive and physical assessments were conducted before participants took the personal tablet home. We strongly encouraged them to engage in the training program for a minimum of 3 days per week over the12-week period. Upon study completion, tablets were returned, and the same cognitive and physical assessments were re-evaluated as part of the 12-week follow-up. All data of the COGNIMO program were securely stored on an independent server managed by AI.Ble therapeutics, ensuring patient-deidentification for data privacy and confidentiality.

Outcome measures

The primary outcome measures encompassed cognitive parameters, specifically changes in scores for both the K-MMSE-2 and the Korean-Montreal Cognitive Assessment (K-MoCA) [20], between baseline and the 12th week. The secondary outcome measures included changes in scores for the Berg Balance Scale (BBS) [21], the Six-Minute Walking Test (6MWT) [22,23], the Five Times Sit-to-Stand test (5xSTS) [24], and the short form of the Geriatric Depression Scale (sGDepS) [25,26] between baseline and week 12. The BBS objectively assesses a patient’s ability (or inability) to safely maintain balance during a series of predetermined tasks. The BBS comprises 14 items requiring approximately 20 minutes to complete, and each item is rated on a 5-point ordinal scale ranging from 0 to 4, which quantifies functional levels from the lowest (0) to the highest (4). The 6MWT is a submaximal exercise evaluation of aerobic capacity and endurance [27], that measures the gait speed covered within six minutes. We counted the number of times that participants engaged in the program and considered it as ‘1 training session’ when performed once.

Statistical analysis

To determine program adherence, participants who completed at least one training session per week were considered compliant. Based on this criterion, participants were categorized into the active group (≥12 training sessions) and the control group (<12 sessions) during the 12-week study period. We employed chi-squared tests for categorical variables and Mann–Whitney U test for continuous variables to compare demographics and clinical characteristics between the two groups. Bivariate correlation analyses using Pearson’s correlation coefficient explored the relationship between training time and outcomes. Linear regression models were employed for outcome variables significantly correlated with training time. In addition, we performed subgroup analyses by diagnosis. Statistical analyses utilized the R software version 4.0.5 (R Foundation for Statistical Computing, Vienna, Austria; www.r-project.org). A p-value <0.05 was considered statistically significant in all two-sided tests.

RESULTS

Among the initial pool of 57 participants, 49 individuals successfully completed this study. Eight participants withdrew due to either withdrawal of consent or loss to follow-up. A comprehensive analysis comparing demographic and clinical variables was performed between the control group (n=19) and the active group (n=30), with detailed findings presented in Table 2. The active group had an average age of 73.8 years, while the control group had an average age of 75.9 years. Among the 49 participants, the clinical diagnosis distribution was as follows: 15 patients had AD, 19 had MCI, 15 had SCD. The distribution of these diagnoses across the two groups was not significantly different (p=0.307). The baseline characteristics were comparable between the active and control groups, with no statistically significant differences in the baseline scores of K-MMSE-2, K-MoCA, and sGDepS. However, baseline secondary outcomes assessing physical abilities such as BBB, 6MWT, and 5xSTS showed difference only in the BBS (Table 2). Concerning the changes in parameters, after the 12-week intervention period, the active group exhibited a notable improvement in K-MoCA scores (2.3±2.2), compared to the control group (0.2±2.6), indicating a statistically significant difference (p=0.008). In contrast, changes in K-MMSE-2 scores between the active group (0.3±2.3) and the control group (-0.1±1.9) were not statistically significant (p=0.506). Regarding changes of physical ability parameters, including BBB, 6MWT, and 5xSTS, no statistically significant differences were found between the two groups (Table 2).

Table 2.

Clinical characteristics of 49 participants

Initial bivariate correlations demonstrated a positive association between the number of training sessions and changes in K-MoCA scores (r=0.31, p=0.038), while no significant correlations emerged between the number of training sessions and other parameters, including changes in K-MMSE-2 scores (r=-0.13, p=0.417). Regression analyses consistently revealed a positive association between changes of K-MoCA scores and the number of training sessions (B(SE)=0.04(0.02), β=0.32, t=2.28, f=5.19, R²=0.101, p=0.027), as depicted in Figure 2A. Upon further analysis by diagnosis, this positive association was clearly observed, particularly within the MCI group (Figure 2B). Considering subgroup analyses by group and diagnosis, apparent discrepancies not only in the changed scores of the K-MoCA but also in the K-MMSE-2 were observed among participants with MCI, distinguishing the control group from the active group (Figure 3).

Figure 2.

Linear regression between the number of training sessions and change in K-MoCA scores. The regression line is reported for all the participants (A). The regression lines are shown according to clinical diagnosis (B). K-MoCA, Korean-Montreal Cognitive Assessment; AD, Alzheimer’s dementia; MCI, mild cognitive impairment; SCD, subjective cognitive decline.

Figure 3.

Comparison of the changes in K-MoCA (A) and K-MMSE-2 scores (B) based on group and clinical diagnosis. Among patients with MCI, improvements in scores not only on the K-MoCA but also on the K-MMSE-2 were observed in the active group. K-MoCA, Korean-Montreal Cognitive Assessment; K-MMSE-2, Korean MiniMental State Examination, 2nd edition; AD, Alzheimer’s dementia; MCI, mild cognitive impairment; SCD, subjective cognitive decline.

DISCUSSION

This study introduced a novel home-based AR dual-task platform, targeting both cognitive and physical abilities in elderly patients with cognitive complaints. The positive impact observed in terms of improved K-MoCA scores suggested the potential benefit of the COGNIMO platform in enhancing cognitive function particularly in the MCI group. The positive correlation between the number of training sessions and changes in K-MoCA scores suggested a dose-response relationship, emphasizing that steady repetitive training with this platform is likely to be effective in improving cognitive function.

The NPTs have demonstrated applicability across a spectrum of cognitive impairment, encompassing dementia, MCI [28] and even cognitively unimpaired adults at risk for dementia [11]. In particular, the combination of physical exercise and cognitive training within an NPT framework shows promise in enhancing cognitive function. Our results aligned with those of meta-analyses reporting consistent benefits of combined cognitive and physical training for elderly individuals without cognitive impairment [8], patients with MCI [29-33], or those with dementia [7]. These studies highlighting the effectiveness of dual-task platforms have observed improvements across various cognitive domains, encompassing global cognition, memory, executive function, and functional status, regardless of the baseline cognitive status [34,35]. Furthermore, compared to single-task approaches, dual-task interventions necessitate greater cooperation and high concentration during tasks, leading to broader brain activation [36] and increased blood flow [37]. The positive effects of cognitive training on cognition in patients with MCI may be linked to enhanced neuroplasticity, potentially mediated by increased brain-derived neurotrophic factor (BDNF) levels or neuroimaging findings [38-41].

The absence of significant improvement in the physical parameters over the 12-week period could be attributed to several factors. The relatively short duration may have been insufficient to elicit substantial physical improvements. Generally, moderate-intensity aerobic exercise is recommended for at least 30 minutes, five days per week [42], however, aerobic exercise in one session of this program is 16 minutes, comparatively shorter than the recommended guidelines, which could potentially affect the outcomes. Additionally, the platform’s design prioritized user-friendliness for elderly populations, which might have inadvertently restricted the exercise intensity or exertion level required to elicit significant changes. There is also the possibility that the selected parameters were not optimally suited to detect subtle alterations in physical functions or lacked adequate sensitivity to detect such changes. However, given prior research suggesting that the implication of aerobic or physical exercise combined with cognitive training has the potential to enhance neuroplasticity in individuals with MCI [41,43], the absence of statistically significant improvements in physical parameters within this short-term trial is to be expected. Based on the results of this pilot study, it might be beneficial to extend the duration of aerobic exercise in future iterations of the program to align with current guidelines, thereby potentially enhancing both physical and cognitive outcomes.

Regarding the differences in the observed efficacy between groups, one plausible reason for the differential effects could be the varying baseline cognitive reserves and progression rates of the conditions [44,45]. Patients with MCI may have a greater capacity for cognitive improvement due to less severe baseline impairments compared to those with AD [44,45]. Conversely, individuals with SCD might have minimal objective cognitive impairments, making significant improvements harder to detect with the given outcome measures. This suggests that the intermediate level of cognitive impairment in MCI allows for more noticeable improvements, and the possible heightened neuroplasticity response to the dual-task intervention might be more pronounced in this group.

The disparity in K-MMSE-2 and K-MoCA score improvements is perhaps because the assessment of K-MoCA involves more intricate cognitive functions, including frontal executive functions. This complexity might render the K-MoCA more sensitive to subtle cognitive changes. Encouragingly, among MCI patients, the improvement in K-MMSE-2 scores in the active group compared to the control group raises the potential for K-MMSE-2 improvement.

The dropout and compliance rates observed in our study could be indicative of several factors. The reasons for noncompliance may include the novelty of the AR platform, potential technical difficulties, or a lack of immediate perceived benefits, which could affect motivation. Future studies should aim to provide more detailed guidance and support to participants to enhance compliance and explore ways to increase engagement.

Home-based, self-administered computerized cognitive training enables individuals to independently access cognitive exercises from their personal devices at any time. Research indicates that this approach yields comparable benefits to cognitive function as supervised in-person training sessions in healthy elderly individuals [46-48]. Previous studies employing home-based cognitive training have shown cognitive benefits in patients with MCI [49-52].

AR involves overlaying virtual images onto the real world using visual devices such as cameras, which enables functional recovery through interactive manipulation of the patient’s environment and monitoring and enhances engagement, motivation, and immersion [53]. AR interventions can be applied comprehensively to patients of various ages, diseases, domains, and clinical patterns [54], promoting motivation and potentially improving outcomes [55]. AR interventions can be particularly valuable for patients with limited mobility, allowing interventions beyond the clinical setting to homes [56]. The growing application of AR in cognitive interventions for MCI and dementia shows its potential for enhancing daily life or reducing inconveniences [57,58]. From this perspective, our home-based, dual-task AR platform was useful in investigating whether it is suitable for elderly individuals, specifically those with cognitive decline.

The strength of our study lies in its distinctive features. Firstly, our program is home-based, a characteristic that enhances adherence to the intervention. This is particularly pivotal given the high costs and limited infrastructure for NPT in Korea, where many elderly patients encounter barriers to accessing such interventions. The home-based cognitive training program aims to enhance accessibility for a broader population of elderly individuals, especially those with cognitive decline. This potentially provides a cost-effective solution for cognitive and physical training in the elderly individuals. Utilizing human-computer interaction, our program fosters self-directed learning, aligning with the growing importance of personalized and self-directed interventions. Computerized tasks, being more interactive and engaging, may contribute to increased motivation levels within the active control group [47]. Another strength lies in the integration of AR in our program, introducing an innovative dimension that stimulates interest and enhances concentration during training sessions. This combination of dual-task training with AR technology suggests the potential for heightened engagement and effectiveness in improving cognitive and physical abilities among elderly individuals.

This observational study has several limitations. First, small sample size and short duration of this study necessitate cautious interpretation of the findings. Second, the observational study design, which lacks randomization and control group, gives rise to the potentials for confounding variables and selection biases, potentially affecting internal validity. The single-arm design, coupled with the limited sample size may also restrict the generalizability of the findings. Third, the heterogeneity within the MCI group adds complexity to the interpretation of outcomes. Despite these limitations, the findings from this pilot study provide valuable insights into the prospective efficacy of an AR-integrated, home-based dual task platform in enhancing cognitive function in elderly individuals, particularly those diagnosed with MCI. These promising results encourage the platform’s positive impact, suggesting a hopeful path for cognitive training interventions. To validate the true potential and efficacy of cognitive training and to amplify the present findings, further research involving larger, more extensive, randomized controlled trials, with a greater emphasis on individuals with MCI should be undertaken.

Notes

Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: YongSoo Shim, Jihye Park. Data curation: YongSoo Shim, Bora Yoon. Formal analysis: Bora Yoon. Funding acquisition: YongSoo Shim. Investigation: YongSoo Shim, Bora Yoon. Methodology: all authors. Project administration: YongSoo Shim. Resources: all authors. Software: all authors. Supervision: YongSoo Shim, Jihye Park. Validation: all authors. Visualization: Bora Yoon. Writing—original draft: Bora Yoon. Writing—review & editing: YongSoo Shim, Jihye Park.

Funding Statement

This study was supported by the Ministry of SMEs and Startups (MSS, Korea) (S3211612).

Acknowledgements

We would like to thank to research group in the AI.ble Therapeutics, Inc, Korea, which developed the cognitive-motor training platform, COGNIMO.

References

1. Lee J, Kang M, Lee O, Lee H, Kwak M, Yu W, et al. Korean dementia observatory 2020. 2021. [Internet]. Available at: https://ansim.nid.or.kr/community/pds_view.aspx?page=&BID=221. Accessed September 23, 2023.

2. Lee J, Kang M, Lee O, Kwak M, Seo J, Ko I, et al. Korean dementia observatory 2021. 2022. [Internet]. Available at: https://ansim.nid.or.kr/community/pds_view.aspx?bid=243. Accessed September 23, 2023.

3. Livingston G, Sommerlad A, Orgeta V, Costafreda SG, Huntley J, Ames D, et al. Dementia prevention, intervention, and care. Lancet 2017;390:2673–2734.

4. Sikkes SAM, Tang Y, Jutten RJ, Wesselman LMP, Turkstra LS, Brodaty H, et al. Toward a theory-based specification of non-pharmacological treatments in aging and dementia: focused reviews and methodological recommendations. Alzheimers Dement 2021;17:255–270.

5. Bhome R, Berry AJ, Huntley JD, Howard RJ. Interventions for subjective cognitive decline: systematic review and meta-analysis. BMJ Open 2018;8e021610.

6. Smart CM, Karr JE, Areshenkoff CN, Rabin LA, Hudon C, Gates N, et al. Non-pharmacologic interventions for older adults with subjective cognitive decline: systematic review, meta-analysis, and preliminary recommendations. Neuropsychol Rev 2017;27:245–257.

7. Karssemeijer EGA, Aaronson JA, Bossers WJ, Smits T, Olde Rikkert MGM, Kessels RPC. Positive effects of combined cognitive and physical exercise training on cognitive function in older adults with mild cognitive impairment or dementia: a meta-analysis. Ageing Res Rev 2017;40:75–83.

8. Zhu X, Yin S, Lang M, He R, Li J. The more the better? A meta-analysis on effects of combined cognitive and physical intervention on cognition in healthy older adults. Ageing Res Rev 2016;31:67–79.

9. Mancioppi G, Fiorini L, Rovini E, Cavallo F. The use of motor and cognitive dual-task quantitative assessment on subjects with mild cognitive impairment: a systematic review. Mech Ageing Dev 2021;193:111393.

10. Choi H, Lim JS, Lee CN, Jang JW, Yi S, Na S, et al. Coronavirus disease 2019 and dementia: the survey for dementia patients in COVID-19 crisis. Dement Neurocogn Disord 2021;20:16–17.

11. Jessen F, Amariglio RE, van Boxtel M, Breteler M, Ceccaldi M, Chételat G, et al. A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimers Dement 2014;10:844–852.

12. Winblad B, Palmer K, Kivipelto M, Jelic V, Fratiglioni L, Wahlund LO, et al. Mild cognitive impairment--beyond controversies, towards a consensus: report of the international working group on mild cognitive impairment. J Intern Med 2004;256:240–246.

13. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s disease. Neurology 1984;34:939–944.

14. Jessen F, Amariglio RE, Buckley RF, van der Flier WM, Han Y, Molinuevo JL, et al. The characterisation of subjective cognitive decline. Lancet Neurol 2020;19:271–278.

15. Ryu HJ, Yang DW. The Seoul neuropsychological screening battery (SNSB) for comprehensive neuropsychological assessment. Dement Neurocogn Disord 2023;22:1–15.

16. Choi SH, Shim YS, Ryu SH, Ryu HJ, Lee DW, Lee JY, et al. Validation of the literacy independent cognitive assessment. Int Psychogeriatr 2011;23:593–601.

17. Kang Y, Jahng S, Kim SY. Korean Dementia Association. In: Korean-Mini Mental State Examination, 2nd Edition (K-MMSE-2) Seoul: Hakjisa; 2020.

18. Morris JC. Clinical dementia rating: a reliable and valid diagnostic and staging measure for dementia of the Alzheimer type. Int Psychogeriatr 1997;9(Suppl 1):173–176. discussion 177-178.

19. Lee JI, Park J, Koo J, Son M, Hwang JH, Lee JY, et al. Effects of the home-based exercise program with an augmented reality system on balance in patients with stroke: a randomized controlled trial. Disabil Rehabil 2023;45:1705–1712.

20. Kang Y, Lee BC, Park J, Yu KH. The validity of the Korean-Montreal Cognitive Assessment (K-MoCA) as a screening test for both MCI and VCI [Internet]. Available at: https://doi.org/10.3389/conf.fnins.2010.14.00148. Accessed September 23, 2023.

21. Jung HY, Park JH, Shim JJ, Kim MJ, Hwang MR, Kim SH. [Reliability test of Korean version of Berg Balance Scale]. Ann Rehabil Med 2006;30:611–618. Korean.

22. Park SW, Kim SY, Kim HI, Sung DJ, Yu W. A study on the standardization of the 6-minute walking test for elderly Koreans. Medico Legal Update 2020;20:2085–2089.

23. ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med 2002;166:111–117.

24. Melo TA, Duarte ACM, Bezerra TS, França F, Soares NS, Brito D. The five times sit-to-stand test: safety and reliability with older intensive care unit patients at discharge. Rev Bras Ter Intensiva 2019;31:27–33.

25. Bae JN, Cho MJ. Development of the Korean version of the geriatric depression scale and its short form among elderly psychiatric patients. J Psychosom Res 2004;57:297–305.

26. Herrmann N, Mittmann N, Silver IL, Shulman KI, Busto UA, Shear NH, et al. A validation study of the geriatric depression scale short form. Int J Geriatr Psychiatry 1996;11:457–460.

27. Enright PL. The six-minute walk test. Respir Care 2003;48:783–785.

28. Petersen RC. Mild cognitive impairment. Continuum (Minneap Minn) 2016;22:404–418.

29. Xue D, Li PWC, Yu DSF, Lin RSY. Combined exercise and cognitive interventions for adults with mild cognitive impairment and dementia: a systematic review and network meta-analysis. Int J Nurs Stud 2023;147:104592.

30. Hu M, Wu X, Shu X, Hu H, Chen Q, Peng L, et al. Effects of computerised cognitive training on cognitive impairment: a meta-analysis. J Neurol 2021;268:1680–1688.

31. Hill NT, Mowszowski L, Naismith SL, Chadwick VL, Valenzuela M, Lampit A. Computerized cognitive training in older adults with mild cognitive impairment or dementia: a systematic review and meta-analysis. Am J Psychiatry 2017;174:329–340.

32. Meng Q, Yin H, Wang S, Shang B, Meng X, Yan M, et al. The effect of combined cognitive intervention and physical exercise on cognitive function in older adults with mild cognitive impairment: a meta-analysis of randomized controlled trials. Aging Clin Exp Res 2022;34:261–276.

33. Yang C, Moore A, Mpofu E, Dorstyn D, Li Q, Yin C. Effectiveness of combined cognitive and physical interventions to enhance functioning in older adults with mild cognitive impairment: a systematic review of randomized controlled trials. Gerontologist 2020;60:633–642.

34. Han K, Tang Z, Bai Z, Su W, Zhang H. Effects of combined cognitive and physical intervention on enhancing cognition in older adults with and without mild cognitive impairment: a systematic review and meta-analysis. Front Aging Neurosci 2022;14:878025.

35. Law LL, Barnett F, Yau MK, Gray MA. Effects of combined cognitive and exercise interventions on cognition in older adults with and without cognitive impairment: a systematic review. Ageing Res Rev 2014;15:61–75.

36. Lee BT, Lee KM. Neural basis involved in the interference effects during dual task: interaction between calculation and memory retrieval. Korean J Cogn Sci 2007;18:159–178.

37. Erickson KI, Colcombe SJ, Wadhwa R, Bherer L, Peterson MS, Scalf PE, et al. Training-induced functional activation changes in dual-task processing: an FMRI study. Cereb Cortex 2007;17:192–204.

38. Beishon L, Intharakham K, Swienton D, Panerai RB, Robinson TG, Haunton VJ. Neuroimaging outcomes in studies of cognitive training in mild cognitive impairment and early Alzheimer’s disease: a systematic review. Curr Alzheimer Res 2020;17:472–486.

39. Damirchi A, Hosseini F, Babaei P. Mental training enhances cognitive function and BDNF more than either physical or combined training in elderly women with MCI: a small-scale study. Am J Alzheimers Dis Other Demen 2018;33:20–29.

40. Anderson-Hanley C, Barcelos NM, Zimmerman EA, Gillen RW, Dunnam M, Cohen BD, et al. The aerobic and cognitive exercise study (ACES) for community-dwelling older adults with or at-risk for mild cognitive impairment (MCI): neuropsychological, neurobiological and neuroimaging outcomes of a randomized clinical trial. Front Aging Neurosci 2018;10:76.

41. Styliadis C, Kartsidis P, Paraskevopoulos E, Ioannides AA, Bamidis PD. Neuroplastic effects of combined computerized physical and cognitive training in elderly individuals at risk for dementia: an eLORETA controlled study on resting states. Neural Plast 2015;2015:172192.

42. Nelson ME, Rejeski WJ, Blair SN, Duncan PW, Judge JO, King AC, et al. Physical activity and public health in older adults: recommendation from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007;39:1435–1445.

43. Farhani F, Shahrbanian S, Auais M, Hekmatikar AHA, Suzuki K. Effects of aerobic training on brain plasticity in patients with mild cognitive impairment: a systematic review of randomized controlled trials. Brain Sci 2022;12:732.

44. Iraniparast M, Shi Y, Wu Y, Zeng L, Maxwell CJ, Kryscio RJ, et al. Cognitive reserve and mild cognitive impairment: predictors and rates of reversion to intact cognition vs progression to dementia. Neurology 2022;98:e1114–e1123.

45. Nelson ME, Jester DJ, Petkus AJ, Andel R. Cognitive reserve, Alzheimer’s neuropathology, and risk of dementia: a systematic review and meta-analysis. Neuropsychol Rev 2021;31:233–250.

46. Zokaei N, MacKellar C, Čepukaitytė G, Patai EZ, Nobre AC. Cognitive training in the elderly: bottlenecks and new avenues. J Cogn Neurosci 2017;29:1473–1482.

47. Kueider AM, Parisi JM, Gross AL, Rebok GW. Computerized cognitive training with older adults: a systematic review. PLoS One 2012;7e40588.

48. Lee HK, Kent JD, Wendel C, Wolinsky FD, Foster ED, Merzenich MM, et al. Home-based, adaptive cognitive training for cognitively normal older adults: initial efficacy trial. J Gerontol B Psychol Sci Soc Sci 2020;75:1144–1154.

49. Baik JS, Min JH, Ko SH, Yun MS, Lee B, Kang NY, et al. Effects of home-based computerized cognitive training in community-dwelling adults with mild cognitive impairment. IEEE J Transl Eng Health Med 2023;12:97–105.

50. Lim EH, Kim DS, Won YH, Park SH, Seo JH, Ko MH, et al. Effects of home based serious game training (Brain Talk^TM) in the elderly with mild cognitive impairment: randomized, a single-blind, controlled trial. Brain Neurorehabil 2023;16e4.

51. Hwang HF, Tseng KC, Chen SJ, Yu WY, Chen CY, Lin MR. Effects of home-based computerized cognitive training and tai chi exercise on cognitive functions in older adults with mild cognitive impairment. Aging Ment Health 2023;27:2170–2178.

52. Park J, Kim SE, Kim EJ, Lee BI, Jeong JH, Na HR, et al. Effect of 12-week home-based cognitive training on cognitive function and brain metabolism in patients with amnestic mild cognitive impairment. Clin Interv Aging 2019;14:1167–1175.

53. D’Cunha NM, Nguyen D, Naumovski N, McKune AJ, Kellett J, Georgousopoulou EN, et al. A mini-review of virtual reality-based interventions to promote well-being for people living with dementia and mild cognitive impairment. Gerontology 2019;65:430–440.

54. Iachini T, Maffei L, Masullo M, Senese VP, Rapuano M, Pascale A, et al. The experience of virtual reality: are individual differences in mental imagery associated with sense of presence? Cogn Process 2019;20:291–298.

55. Mesa-Gresa P, Gil-Gómez H, Lozano-Quilis JA, Gil-Gómez JA. Effectiveness of virtual reality for children and adolescents with autism spectrum disorder: an evidence-based systematic review. Sensors (Basel) 2018;18:2486.

56. Mubin O, Alnajjar F, Jishtu N, Alsinglawi B, Al Mahmud A. Exoskeletons with virtual reality, augmented reality, and gamification for stroke patients› rehabilitation: systematic review. JMIR Rehabil Assist Technol 2019;6e12010.

57. Zuschnegg J, Schoberer D, Häussl A, Russegger S, Ploder K, Fellner M, et al. Computerized cognitive interventions for preventing dementia in people with mild cognitive impairment: a systematic review with meta‐analyses. Alzheimers Dement 2022;18(suppl 1)e062090.

58. Rohrbach N, Gulde P, Armstrong AR, Hartig L, Abdelrazeq A, Schröder S, et al. An augmented reality approach for ADL support in Alzheimer’s disease: a crossover trial. J Neuroeng Rehabil 2019;16:66.

Article information Continued

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Time	Categories	Physical exercise	Cognitive training	Related cognitive domains
2 min	Warm-up	Putting both hands together and raising them over your head	Recognition of figures	Visuospatial perception and construction
2 min	Warm-up	Opening both arms	Recognition of figures	Visuospatial perception and construction
8 min	Aerobic exercise	Walking in place
		Avoiding sideways
		Punching while walking
19 min	Cognitive exercise	With arms outstretched	Continuing alternatively the order of numbers and days of the week (Trail Making Test)	Frontal executive
			Finding another one out of four	Language (semantics) and frontal executive
			Finding pairs of the same color and shape	Visuospatial perception and frontal executive
			Remembering the same picture	Visual memory
			Choosing objects’ name	Language (naming)
			Calculation	Attention and working memory, calculation
			Rock Paper Scissors: win or lose	Working memory and frontal executive
			Clock drawing (Stretch out arms, indicating the exact time)	Visuospatial construction
			Finding the same card image	Visuospatial perception and visual memory
4 min	Strength and resistance exercise	With arms elevated, holding a bottle of water	Recognition of figures	Visuospatial perception and construction
4 min	Strength and resistance exercise	With arms elevated, holding a bottle of water	Choosing the one that matches the text and color (Stroop Test)	Frontal executive
8 min	Aerobic exercise	Walking in place
		Avoiding sideways
		Punching while walking
1 min	Cool- down	Stretching
Total 42 min

Group	Active (N=30)	Control (N=19)	p
Age (yr)	73.8±6.1	75.9±6.7	0.267
Sex, female	20 (66.7)	14 (73.7)	0.754
Education (yr)	8.6±4.9	9.2±4.2	0.821
Diagnosis			0.307
AD	11 (36.7)	4 (21.1)
MCI	9 (30.0)	10 (52.6)
SCD	10 (33.3)	5 (26.3)
Training sessions (number)	36.5±15.6	4.2±3.5	<0.001
Baseline parameters
K-MMSE-2_1	24.5±4.6	23.6±4.4	0.376
K-MoCA_1	20.5±6.1	19.5±4.9	0.434
sGDepS_1	4.4±4.0	5.5±4.6	0.363
BBS_1	53.7±2.6	50.6±4.9	0.007
6MWT_1	1.2±0.3	1.1±0.3	0.380
5xSTS_1	13.1±4.2	14.6±3.4	0.051
12th-week follow-up parameters
K-MMSE-2_2	24.8±5.0	23.5±4.2	0.187
K-MoCA_2	22.9±6.1	19.6±5.0	0.032
sGDepS_2	4.7±4.6	5.5±4.1	0.359
BBS_2	54.1±2.0	51.1±5.3	0.098
6MWT_2	1.1±0.3	1.1±0.3	0.324
5xSTS_2	13.0±4.0	13.5±3.6	0.692
Change of parameters
ΔK-MMSE-2 (2_1)	0.3±2.3	-0.1±1.9	0.506
ΔK-MoCA (2_1)	2.3±2.2	0.2±2.6	0.008
ΔBBS (2_1)	0.3±1.7	0.4±5.3	0.723
Δ6MWT (2_1)	-0.0±0.3	-0.0±0.3	0.558
Δ5xSTS (2_1)	-0.1±4.1	-1.1±3.3	0.207