826 research outputs found
Novel Technological Solutions for Assessment, Treatment, and Assistance in Mild Cognitive Impairment
Efficacy and Moderators of Virtual Reality for Cognitive Training in People with Dementia and Mild Cognitive Impairment: A Systematic Review and Meta-Analysis
Background: Mild cognitive impairment (MCI) and dementia result in cognitive decline which can negatively impact everyday functional abilities and quality of life. Virtual reality (VR) interventions could benefit the cognitive abilities of people with MCI and dementia, but evidence is inconclusive. Objective: To investigate the efficacy of VR training on global and domain-specific cognition, activities of daily living and quality of life. To explore the influence of priori moderators (e.g., immersion type, training type) on the effects of VR training. Adverse effects of VR training were also considered. Methods: A systematic literature search was conducted on all major databases for randomized control trial studies. Two separate meta-analyses were performed on studies with people with MCI and dementia. Results: Sixteen studies with people with MCI and four studies with people with dementia were included in each meta-analysis. Results showed moderate to large effects of VR training on global cognition, attention, memory, and construction and motor performance in people with MCI. Immersion and training type were found to be significant moderators of the effect of VR training on global cognition. For people with dementia, results showed moderate to large improvements after VR training on global cognition, memory, and executive function, but a subgroup analysis was not possible. Conclusion: Our findings suggest that VR training is an effective treatment for both people with MCI and dementia. These results contribute to the establishment of practical guidelines for VR interventions for patients with cognitive decline
๊ฐ์ํ์ค ๋ด ์ ๋ณด ๋ถ์ผ์น๋ฅผ ํ์ฉํ ์ธ์ง๊ธฐ๋ฅ ํ๊ฐ: ํ์์ ๊ณ ์ฐฐ
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ์ธ๋ฌธ๋ํ ํ๋๊ณผ์ ์ธ์ง๊ณผํ์ ๊ณต, 2022.2. ์ด๊ฒฝ๋ฏผ.๋ณธ ๋ฐ์ฌ๋
ผ๋ฌธ์ ๋ชฉ์ ์ ๊ฐ์ํ์ค ๋ด์์ ๋ฐ์ํ๋ ์ ๋ณด๋ถ์ผ์น์ ๋ํด์ ์์๋ณด๊ณ , ์ ๋ณด ๋ถ์ผ์น๋ก ์ธํ ์ธ์ง์ ๋ฐ์์ ์ธ์ง๊ธฐ๋ฅ ํ๊ฐ์ ํ์ฉํ ์ ์๋ ๋ฐฉ์์ ๊ณ ์ฐฐํ๊ณ ์ ํจ์ด๋ค. ๊ฐ์ํ์ค ์ฃผ๋ฐฉ๊ณผ์ ๋ฅผ ๊ตฌํํ์ฌ ๊ณผ์ ์ํ ์ค ๋ํ๋๋ ์์ง์๊ณผ ์ธ์ง์์ฉ์ ํน์ฑ์ ์์๋ณด๊ณ ์ ํ์๋ค. ๋ํ VR์์ ๊ณผ์ ์ํ ์ ๋ํ๋๋ ์ธ์ง ๋ถํ์ ์์ธ์ ํ์ํ์๋ค. ํนํ, ๊ฐ๊ฐ์ด๋ ์กฐ์ ์ธก๋ฉด์์ ๊ฐ์ํ์ค ๋ด ๋ฐ์ํ๋ ์ ๋ณด๋ถ์ผ์น๋ก ์ธํ ์ธ์ง ๊ณผ๋ถํ๋ฅผ ์ดํด๋ณด์๋ค.
์ฒซ์งธ, ๊ฐ์ํ์ค๊ณผ ์ค์ ํ๊ฒฝ์์ ์๋ํ๋ ์ธ์ง๊ณผ์ ์ด ์ด๋ป๊ฒ ๋ค๋ฅธ์ง ์์๋ณด๊ธฐ ์ํด ๋ ํ๊ฒฝ ๊ฐ์ ๊ณผ์ ์ํ ์ฐจ์ด๋ฅผ ๋น๊ตํ์๋ค. ์ ์ ์ฑ์ธ ๊ทธ๋ฃน์์๋ ์ด๋ ค์ด ์ฃผ๋ฐฉ๊ณผ์ ์ํ ์ ๊ฐ์ํ์ค๊ณผ ์ค์ ํ๊ฒฝ ๊ฐ์ ์ํ์๊ฐ์ ์ ์ํ ์ฐจ์ด๊ฐ ์์์ง๋ง ์ฌ์ด ์ฃผ๋ฐฉ ๊ณผ์ ์์๋ ์ฐจ์ด๊ฐ ์์๋ค. ๋ฐ๋ฉด ๋
ธ์ธ ์ง๋จ์์๋ ๊ณผ์ ์ ๋์ด๋์ ๊ด๊ณ์์ด ๋ ํ๊ฒฝ ๊ฐ์ ์ํ ์๊ฐ์ ์๋นํ ์ฐจ์ด๊ฐ ์์๋ค. ๋
ธ์ธ์ ๊ฒฝ์ฐ ๊ฐ์ํ์ค์์ ๊ฐ๊ฐ์ด๋ ์กฐ์ ์ ์ด๋ ค์์ ๋ณด์๋ค. ์ฆ ๋
ธ์ธ์ ๊ฒฝ์ฐ ์ ์ ์ฑ์ธ์ ๋นํด ๊ฐ์ํ์ค ๋ด์์์ ๊ฐ๊ฐ์ด๋ ์กฐ์ ์ด ๋ ์ด๋ ต๊ธฐ ๋๋ฌธ์ ์ด๋ก ์ธํ ์ธ์ง์ ๋ถํ๊ฐ ๊ณผ์ ์ํ ์์ฒด์ ์ธ์ง์ ๋ถํ์ ๊ฐ์ค๋์ด ๊ณผ์ ๋์ด๋๊ฐ ์ด๋ ค์์ง๋ฉด ์ธ์ง์ฉ๋์ ํ๊ณ๋ฅผ ์ด๊ณผํ๊ฒ ๋๋ค.
๋์งธ, ๊ฐ์ ์ฃผ๋ฐฉ๊ณผ์ ์ํ ์ ์ธ์ง๊ธฐ๋ฅ์ด ์ ํ๋จ์ ๋ฐ๋ผ ๊ฐ์๊ธฐ ํ ์์ง์ด๋(jerky) ํจํด์ ๋ณด์ด๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค. ์ด๋ ์ธ์ง๊ธฐ๋ฅ์ด ์ ํ๋ ๋
ธ์ธ์ ๊ฒฝ์ฐ ํ๊ฒฝ์ ๋ํ ์์ธก๋ ฅ์ด ์ ํ๋์ด ์ต์ ์ ํฌ์ด๋ ์กฐ์ (minimal jerk movement control)์ ์ด๋ ค์์ด ์์์ ์์ฌํ๋ค. ๋ํ ์ธ์ง๊ธฐ๋ฅ์ด ๋์ ๊ทธ๋ฃน๋ณด๋ค ์ธ์ง๊ธฐ๋ฅ์ด ๋ฎ์ ๋
ธ์ธ ๊ทธ๋ฃน์ ๊ฒฝ์ฐ ๊ณผ์ ๊ฐ ์๋ฃ๋ ๋๊น์ง์ ์ผ๋ จ์ ์์ง์ ๋จ๊ณ๊ฐ ๋ ๋ง์๋ค. ์ธ์ง๊ธฐ๋ฅ์ด ์ ํ๋จ์ ๋ฐ๋ผ ๋นํจ์จ์ ์ด๊ณ ๋ถ์ฃผํ ์์ง์์ ๋ณด์ธ๋ค๊ณ ํ ์ ์๋ค. ๋ํ ๋ค์คํ๊ท๋ถ์ ๊ฒฐ๊ณผ, ๋
ธ์ธ์ด ๊ฐ์ํ์ค ์ฃผ๋ฐฉ๊ณผ์ ๋ฅผ ํจ์จ์ ์ผ๋ก ์ํํจ์ ์์ด ์ฐ๋ น ๋ฐ ํ๋ ฅ ๋ณด๋ค๋ ์ธ์ง๊ธฐ๋ฅ์ด ๊ฐ์ฅ ์ํฅ์ ๋ฏธ์น๋ ์์ธ์ผ๋ก ๋ํ๋ฌ๋ค. ์ฆ ๊ฐ์ํ์ค ๊ธฐ๋ฐ ๊ณผ์ ์ํ์ ์์ ์ธ์ง๊ธฐ๋ฅ๋ง์ ํ๊ฐํ๋ ์๋ก์ด ๋์์ผ๋ก ์ ์ํ ์ ์๋ค.
๋ง์ง๋ง์ผ๋ก ๊ฐ๊ฐ์ด๋ ํผ๋๋ฐฑ์ ์์ธก๋ถ๊ฐ๋ฅ์ฑ(unpredictability)์ด ๊ฐ์ํ์ค์์ ์ธ์ง๋ถํ๋ฅผ ์ ๋ฐํ๋ ๋ฐฉ์์ ์์๋ณด๊ณ ์ ํ์๋ค. ์ญ๋์ ์์ธก ๊ฐ๋ฅ์ฑ์ ๋ฐ๋ฅธ ๋ฐ์ ์๊ฐ๊ณผ ์ด๋ ์๋๋ฅผ ์๋ฌต์ 5ยฐ์ ๋ช
์์ 15ยฐ ์ญ๋ ์กฐ๊ฑด์์ ๊ฐ๊ฐ ์ธก์ ํ์๋ค. ๊ทธ ๊ฒฐ๊ณผ ์๋ฌต์ ์ด๋ ์ ์ด ์ ์ญ๋์ ๋ณํ๋ฅผ ์์ธกํ ์ ์์ ๋ ์์ง์์ ์ ํ๋๋ฅผ ๋์ด๊ธฐ ์ํด ์์ง์์ด ๋๋ ค์ง๋ ์ ๋ต(accuracy and speed trade-off)์ ์ฌ์ฉํ๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค. ์ฆ, ๊ฐ๊ฐ์ด๋์กฐ์ ๊ณผ์ ์์์ ์ ๋ณด ๋ถ์ผ์น๋ก ์ธํ ์์ธก ๋ถ๊ฐ๋ฅ์ฑ์ ๋ํด ์ฐ๋ฆฌ์ ๋๋ ๋ค๋ฅธ ์ธ์ง์ ๋ต์ ์ทจํ๋ค๊ณ ์ค๋ช
ํ ์ ์๋ค.
๊ฒฐ๋ก ์ ์ผ๋ก ๊ฐ์ํ์ค์ ๊ธฐ์ ์ ์ถฉ์ค๋(fidelity) ๋ฌธ์ ๋ก ์ธํด ๊ฐ๊ฐ ํผ๋๋ฐฑ์ด ์์ธก ๋ถ๊ฐ๋ฅํ๊ณ ๊ฐ๋ณ์ ์ด๊ธฐ ๋๋ฌธ์ ์ค์ ํ๊ฒฝ๋ณด๋ค ๋ ๋ง์ ์ธ์ง ๋ถํ๋ฅผ ์ ๋ฐํ๋ค. ํนํ ๊ฐ์ํ์ค์์์ ๊ฐ๊ฐ์ด๋ ์กฐ์ ์ ์ค์ ํ๊ฒฝ์์ ์ธ๊ฐ์ ์ด๋ ์์คํ
์ด ์ ์๋ ๋ฐฉ์๊ณผ๋ ๋ค๋ฅด๋ค๊ณ ๋ณผ ์ ์๋ค. ์ฆ ๊ฐ์ํ์ค ๋ด์์๋ ๊ฐ๊ฐ์ด๋ ์์คํ
์ด ์์ธกํ ์ ์๋ ํ๊ฒฝ์ ์ ์ํ๊ธฐ ์ํด ๋ค๋ฅธ ์ธ์ง ์ ๋ต์ ์ทจํ๊ฒ ๋๋ค. ํ๊ฒฝ์ ๋ฐ๋ฅธ ํจ์จ์ ์ธ ์ธ์ง์ ๋ต์ ์ ํ์ ์ค์ ์งํ๊ธฐ๋ฅ(central executive)๊ณผ ๊ด๋ จ ์์ผ๋ฉฐ, ์ด๋ฌํ ํน์ง์ ํ์ฉํ ๊ฐ์ํ์ค๊ธฐ๋ฐ ๊ณผ์ ๋ ์๋ก์ด ์ธ์ง๊ธฐ๋ฅ ํ๊ฐ์ ๋์์ผ๋ก ์ ์ํ ์ ์๋ค.The purpose of this dissertation was to investigate information mismatch in virtual reality (VR) and explore the possibility of using the cognitive reaction arising from information mismatch for cognitive evaluation. The virtual kitchen task was used to observe the subjectsโ behaviors while performing the task, and to investigate the characteristics of movement and cognitive processes appearing during the performance of the virtual task. In addition, an attempt was made to explore the factors of cognitive overload in VR that determine the difference compared to a performance in the real environment. In particular, this study aimed to investigate how information mismatch occurring in VR causes cognitive overload in terms of sensorimotor control.
First, it questioned how the cognitive process in VR differs from the real environment and also investigated the factors affecting the performance of tasks in VR. In the young adult group, while there was a significant difference between the execution time in VR and in the real environment in the difficult kitchen task, there was no such difference in the easy kitchen task. Meanwhile, among the elderly, there was a significant difference between the execution time in VR and in the real environment regardless of whether the task was difficult or easy. It was thought that cognitive load was caused due to difficulties in sensorimotor control in VR. It was found that the cognitive capacity is challenged when the task is difficult because the load of task performance itself and the load of sensorimotor control are doubling.
Second, it was found that as the cognitive function decreased, an abrupt and jerky movement pattern was exhibited during the virtual kitchen task. The number of sequences in movement until the task was completed was also busier in the elderly group with lower cognitive function in contrast with those with higher cognitive function. In the case of the elderly with deteriorated cognitive function, it is suggested that there is difficulty in minimal jerk movement control because the predictive ability responding to environment is decreased. In addition, according to the results of multiple regression, cognitive function of the elderly is the most influential factor in performing VR tasks, other than age and educational background, which means that purely evaluating cognitive function may be suggested.
Third, an attempt was made to verify how the unpredictability of sensorimotor feedback causes cognitive load in VR. The reaction time and speed of movement depending on the predictability of perturbation were measured in implicit 5 degrees and explicit 15 degrees perturbation. When the subject was unable to predict the variation of perturbation only in implicit motor control, reaching became slower and it took more time due to the accuracy and speed trade-off. In other words, unpredictability due to information mismatch leads to the use of different cognitive strategies in brain mechanisms.
In conclusion, VR induces more cognitive load than the real environment because the sensory feedback is unpredictable and variable due to technical fidelity problems. The sensorimotor control in VR is challenged by the way the human motor system is adapted. Further, it was found that an unpredictable environment requires different cognitive strategies for the sensorimotor system to adapt to it. The manner in which effective cognitive strategies are taken represents an efficient central executive function. From this perspective, VR-based cognitive evaluation, using such attributes, is thought to be an alternative method for early screening of cognitive decline.Chapter 1. Introduction 7
1.1 Research motivation and introductory overview 7
1.2 Research goal and questions 7
1.2.1 Overall research goal 7
1.2.2 Research questions 8
1.2.3 Research contributions 8
1.3 Thesis structure 8
Chapter 2. Literature Review 10
2.1 Virtual Reality (VR) as ecological method for cognitive evaluation 10
2.2 Sub-types of VR based tasks according to target cognitive function 12
2.2.1. VR task for spatial navigation 13
2.2.2. VR task for memory 14
2.2.3. VR task for executive function 16
2.3 Factors affecting on VR performance 19
2.3.1. General 19
2.3.2. Age effects on VR performance 20
2.3.3. Cognitive challenges in VR 21
2.3.4. Feasibility of VR task for dementia 22
2.4 Cognitive load in VR 23
2.4.1. Immersive versus non-immersive VR 23
2.4.2. Sense of presence and situated cognition 26
2.4.3. Sensorimotor adaptation in VR 28
2.5 Sensorimotor control in VR 29
2.5.1 Predictive brain and internal model for motor control 29
2.5.2 Explicit and implicit process in motor control 31
2.5.3 Accuracy & speed tradeoff in cognitive control 31
2.6 Executive control for information mismatch in information processing 32
Chapter 3. Differences in Cognitive Load Between Real and VR Environment 34
3.1 Introduction 34
3.2 Method 37
3.3 Results 40
3.4 Discussion 45
Chapter 4. The Efficiency of Movement Trajectory and Sequence in VR According to Cognitive Function in the Elderly 50
4.1 Introduction 50
4.2 Method 52
4.3 Results 53
4.4 Discussion 56
Chapter 5. Factors that Affect the Performance of Immersive Virtual Kitchen Tasks in the Elderly 59
5.1 Introduction 59
5.2 Method 62
5.3 Results 64
5.4 Discussion 70
Chapter 6. Effect of Predictability of Sensorimotor Feedback on Cognitive Load in VR 74
6.1 Introduction 74
6.2 Method 77
6.3 Results 79
6.4 Discussion 84
Chapter 7. Conclusion 88
7.1 Summary of findings 88
7.2 Future direction of research 90
References 92๋ฐ
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As the population ages and the number of people living with dementia or mild cognitive impairment (MCI) continues to increase, it is critical to identify creative and innovative ways to support and improve their quality of life. Motion-based technology has shown significant potential for people living with dementia or MCI by providing opportunities for cognitive stimulation, physical activity and participation in meaningful leisure activities, while simultaneously functioning as a useful tool for research and development of interventions. However, many of the current systems created using motion-based technology have not been designed specifically for people with dementia or MCI. Additionally, the usability and accessibility of these systems for these populations has not been thoroughly considered. This paper presents a set of system development guidelines derived from a review of the state of the art of motion-based technologies for people with dementia or MCI. These guidelines highlight three overarching domains of consideration for systems targeting people with dementia or MCI: (i) cognitive, (ii) physical, and (iii) social. We present the guidelines in terms of relevant design and use considerations within these domains and the emergent design themes within each domain. Our hope is that these guidelines will aid in designing motion-based software to meet the needs of people with dementia or MCI such that the potential of these technologies can be realized
Use of Immersive Virtual Reality in the Assessment and Treatment of Alzheimerโs Disease: A Systematic Review
Background:
Immersive virtual reality (iVR) allows seamless interaction with simulated environments and is becoming an established tool in clinical research. It is unclear whether iVR is acceptable to people with Alzheimerโs disease (AD) dementia or useful in their care. We explore whether iVR is a viable research tool that may aid the detection and treatment of AD.
Objectives:
This review examines the use of iVR in people with AD or mild cognitive impairment (MCI).
Methods:
Medline, PsycINFO, Embase, CINAHL, and Web of Science databases were searched from inception. PRISMA guidelines were used with studies selected by at least two researchers.
Results:
Nine studies were eligible for inclusion. None reported any issues with iVR tolerability in participants with MCI and AD on assessment or treatment tasks. One study demonstrated capability for detecting prodromal AD and correlated with neuroanatomical substrates. Two studies showed iVR to have high accuracy in differentiating participants with AD from controls but were not hypothesis driven or with adequate controls measures. In a small validation study and two longitudinal case studies, iVR cognitive training was positively rated but did not demonstrate reliable benefit.
Conclusion:
iVR is emerging as a viable method of assessing older adults and people with AD. Strongest benefits were seen when closely integrated with theoretical models of neurodegeneration and existing screening methods. Further randomized controlled trials integrated with clinical populations are required. This will consolidate the power of iVR for assessment of MCI and clarify treatment efficacy beyond current applications in physical rehabilitation
Use of Immersive Virtual Reality in the Assessment and Treatment of Alzheimer's Disease: A Systematic Review.
BACKGROUND: Immersive virtual reality (iVR) allows seamless interaction with simulated environments and is becoming an established tool in clinical research. It is unclear whether iVR is acceptable to people with Alzheimer's disease (AD) dementia or useful in their care. We explore whether iVR is a viable research tool that may aid the detection and treatment of AD. OBJECTIVES: This review examines the use of iVR in people with AD or mild cognitive impairment (MCI). METHODS: Medline, PsycINFO, Embase, CINAHL, and Web of Science databases were searched from inception. PRISMA guidelines were used with studies selected by at least two researchers. RESULTS: Nine studies were eligible for inclusion. None reported any issues with iVR tolerability in participants with MCI and AD on assessment or treatment tasks. One study demonstrated capability for detecting prodromal AD and correlated with neuroanatomical substrates. Two studies showed iVR to have high accuracy in differentiating participants with AD from controls but were not hypothesis driven or with adequate controls measures. In a small validation study and two longitudinal case studies, iVR cognitive training was positively rated but did not demonstrate reliable benefit. CONCLUSION: iVR is emerging as a viable method of assessing older adults and people with AD. Strongest benefits were seen when closely integrated with theoretical models of neurodegeneration and existing screening methods. Further randomized controlled trials integrated with clinical populations are required. This will consolidate the power of iVR for assessment of MCI and clarify treatment efficacy beyond current applications in physical rehabilitation
Measuring Memory in an Alzheimer's Treatment Trial Using a Visual Search Task
Alzheimerโs Disease (AD) is characterized by episodic memory deficits attributed to damage to the hippocampal formation. AD therapies specifically targeting hippocampal function may be best evaluated through the use of selective hippocampal tasks. I used a nonverbal hippocampal-dependent target-in-scene detection task to determine if task performance shows age-related decline and/or AD-related impairments. Participants located objects (โtargetsโ) that appeared/disappeared in flickering natural scenes, yielding faster search times for remembered targets than for forgotten ones. AD patients took longer and required more fixations to detect targets, indicating impaired memory. Furthermore, the AD and aged populations exhibited slower pupillary responses. As part of a clinical trial, I next asked whether deep-brain stimulation of the extended hippocampal circuit would modify memory performance in patients with early AD. The double-blind treatment trial is still underway, thus treatment efficacy is yet to be evaluated, however, trial participants showed a measurable, progressive memory impairment in this task
Cognitive stimulation and cognitive results in older adults: A systematic review and meta-analysis
Background and Purpose
The lack of cognitive activity accelerates age cognitive decline. Cognitive stimulation (CS) tries to enhance cognitive functioning. The purpose of this systematic review and meta-analysis was to evaluate the effects of CS on cognitive outcomes (general cognitive functioning and specific cognitive domains) in older adults (aged 65 years or older, cognitively healthy participants, or with mild cognitive impairment, or dementia).
Methods
PubMed, Scopus and Web of Science databases were examined from inception to October 2021. A total of 1,997 studies were identified in these databases, and. 33 studies were finally included in the systematic review and the meta-analysis. Raw means and standard deviations were used for continuous outcomes. Publication bias was examined by Egger's Regression Test for Funnel Plot Asymmetry and the quality assessment tools from the National Institutes of Health.
Results
CS significantly improves general cognitive functioning (mean difference=MD = 1.536, 95%CI, 0.832 to 2.240), memory (MD = 0.365, 95%CI, 0.300 to 0.430), orientation (MD = 0.428, 95%CI, 0.306 to 0.550), praxis (MD = 0.278, 95%CI, 0.094 to 0.462) and calculation (MD = 0.228, 95%CI, 0.112 to 0.343).
Conclusion
CS seems to increase general cognitive functioning, memory, orientation, praxis, and calculation in older adults
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