Musiquence – Design, Implementation and Validation of a Customizable Music and Reminiscence Cognitive Stimulation Platform for People with Dementia

Dementia is a neurodegenerative disease that affects millions of individuals worldwide and is challenging to diagnose as symptoms may only perceivable decades later. The disease leads to a gradual loss of memory, learning, orientation, language, and comprehension skills, which compromises activities of daily living. Health-related costs caused by dementia will continue to increase over the next few years; between the years 2005 and 2009, an increase of 34% (from $315 to$422 billion worldwide) was observed in treating dementia-related issues. Pharmaceutical approaches have been developed to treat dementia symptoms; unfortunately, the risk of side effects is high. For this reason, nonpharmaceutical methods such as music and reminiscence therapies have gained acceptance as patients with dementia positively respond to such approaches even at later stages of the disease. Nevertheless, further research is needed to understand how music and reminiscence therapy should be used and to quantify their impact on individuals with dementia. The development of serious games has gained attention as an alternative approach to stimulate patients. However, the clinical impact that serious games have on individuals with dementia is still unclear. In this dissertation, we contribute with new knowledge regarding the usage of music and reminiscence approaches in people with dementia through a theoretical model. Based on Baddeley’s working memory model, our model aims to explain how the therapeutic properties of music and reminiscence can have a beneficial effect. To test our model, we developed a novel interactive platform called Musiquence, in which healthcare professionals can create music and reminiscence based cognitive activities to stimulate people with dementia. In this dissertation, we present the results from several studies about the usage and effects that music and reminiscence have on such a population. We performed two studies using Musiquence to study the feasibility of a novel learning method based on musical feedback to aid people with dementia during task performance in virtual reality settings. Results show that participants relied more on music-based feedback during the task performance of virtual reality activities than in other forms of feedback. Also, data suggest that the music-based feedback system can improve task performance, compensating for some dementia-related deficits. We also used Musiquence in a longitudinal one-month-long pilot study to assess its efficacy when used for a cognitive stimulation intervention in dementia patients. The results of the study are promising. The 3 participants showed improvements in terms of general cognition, quality of life, mood, and verbal fluency

Future bathroom: A study of user-centred design principles affecting usability, safety and satisfaction in bathrooms for people living with disabilities

Research and development work relating to assistive technology 2010-11 (Department of Health) Presented to Parliament pursuant to Section 22 of the Chronically Sick and Disabled Persons Act 197

Role of Artificial Intelligence (AI) art in care of ageing society: focus on dementia

open access articleBackground: Art enhances both physical and mental health wellbeing. The health benefits include reduction in blood pressure, heart rate, pain perception and briefer inpatient stays, as well as improvement of communication skills and self-esteem. In addition to these, people living with dementia benefit from reduction of their noncognitive, behavioural changes, enhancement of their cognitive capacities and being socially active. Methods: The current study represents a narrative general literature review on available studies and knowledge about contribution of Artificial Intelligence (AI) in creative arts. Results: We review AI visual arts technologies, and their potential for use among people with dementia and care, drawing on similar experiences to date from traditional art in dementia care. Conclusion: The virtual reality, installations and the psychedelic properties of the AI created art provide a new venue for more detailed research about its therapeutic use in dementia

System development guidelines from a review of motion-based technology for people with MCI or dementia

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

Immersive Virtual Reality for the Management of Pain in Community-Dwelling Older Adults.

Immersive virtual reality (VR) can provide a high level of engagement and distraction analgesia to address pain. However, community-based applications of this technology for older adults have not been studied. The objective of this study was to examine the applicability and effectiveness of an immersive VR intervention for pain, depression, and quality of life (QOL) in older adults. This pretest–posttest, mixed-methods design included senior center members (n = 12) with pain that interfered with daily functioning. The outcomes included the Numeric Pain Rating Scale, Patient-Reported Outcomes Measurement Information System (PROMIS®) depression scale, World Health Organization Quality of Life Scale Brief Version (WHO QOL-BREF), and open-ended questions. The VR intervention (15- to 45-min sessions, 12 sessions over 6 weeks) was well accepted with no dropouts. There was a significant decrease in pain (p =.002, d = −1.54) with no effect on depression and QOL. There were no adverse effects, and positive perceptions of VR were reported. The 6-week immersive VR intervention was applicable and effective in reducing pain intensity for community-dwelling older adults

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials

가상현실 내 정보 불일치를 활용한 인지기능 평가: 탐색적 고찰

학위논문(박사) -- 서울대학교대학원 : 인문대학 협동과정 인지과학전공, 2022.2. 이경민.본 박사논문의 목적은 가상현실 내에서 발생하는 정보불일치에 대해서 알아보고, 정보 불일치로 인한 인지적 반응을 인지기능 평가에 활용할 수 있는 방안을 고찰하고자 함이다. 가상현실 주방과제를 구현하여 과제 수행 중 나타나는 움직임과 인지작용의 특성을 알아보고자 하였다. 또한 VR에서 과제수행 시 나타나는 인지 부하의 요인을 탐색하였다. 특히, 감각운동 조절 측면에서 가상현실 내 발생하는 정보불일치로 인한 인지 과부하를 살펴보았다. 첫째, 가상현실과 실제환경에서 작동하는 인지과정이 어떻게 다른지 알아보기 위해 두 환경 간의 과제 수행 차이를 비교하였다. 젊은 성인 그룹에서는 어려운 주방과제 수행 시 가상현실과 실제환경 간의 수행시간에 유의한 차이가 있었지만 쉬운 주방 과제에서는 차이가 없었다. 반면 노인 집단에서는 과제의 난이도와 관계없이 두 환경 간의 수행 시간에 상당한 차이가 있었다. 노인의 경우 가상현실에서 감각운동 조절의 어려움을 보였다. 즉 노인의 경우 젊은 성인에 비해 가상현실 내에서의 감각운동 조절이 더 어렵기 때문에 이로 인한 인지적 부하가 과제 수행 자체의 인지적 부하에 가중되어 과제 난이도가 어려워지면 인지용량의 한계를 초과하게 된다. 둘째, 가상 주방과제 수행 시 인지기능이 저하됨에 따라 갑자기 휙 움직이는(jerky) 패턴을 보이는 것으로 나타났다. 이는 인지기능이 저하된 노인의 경우 환경에 대한 예측력이 저하되어 최소 저크운동 조절(minimal jerk movement control)에 어려움이 있음을 시사한다. 또한 인지기능이 높은 그룹보다 인지기능이 낮은 노인 그룹의 경우 과제가 완료될 때까지의 일련의 움직임 단계가 더 많았다. 인지기능이 저하됨에 따라 비효율적이고 분주한 움직임을 보인다고 할 수 있다. 또한 다중회귀분석 결과, 노인이 가상현실 주방과제를 효율적으로 수행함에 있어 연령 및 학력 보다는 인지기능이 가장 영향을 미치는 요인으로 나타났다. 즉 가상현실 기반 과제수행은 순수 인지기능만을 평가하는 새로운 대안으로 제시할 수 있다. 마지막으로 감각운동 피드백의 예측불가능성(unpredictability)이 가상현실에서 인지부하를 유발하는 방식을 알아보고자 하였다. 섭동의 예측 가능성에 따른 반응 시간과 이동 속도를 암묵적 5°와 명시적 15° 섭동 조건에서 각각 측정하였다. 그 결과 암묵적 운동 제어 시 섭동의 변화를 예측할 수 없을 때 움직임의 정확도를 높이기 위해 움직임이 느려지는 전략(accuracy and speed trade-off)을 사용하는 것으로 나타났다. 즉, 감각운동조절 과정 상에서 정보 불일치로 인한 예측 불가능성에 대해 우리의 뇌는 다른 인지전략을 취한다고 설명할 수 있다. 결론적으로 가상현실은 기술적 충실도(fidelity) 문제로 인해 감각 피드백이 예측 불가능하고 가변적이기 때문에 실제 환경보다 더 많은 인지 부하를 유발한다. 특히 가상현실에서의 감각운동 조절은 실제환경에서 인간의 운동 시스템이 적응된 방식과는 다르다고 볼 수 있다. 즉 가상현실 내에서는 감각운동 시스템이 예측할 수 없는 환경에 적응하기 위해 다른 인지 전략을 취하게 된다. 환경에 따른 효율적인 인지전략의 전환은 중앙 집행기능(central executive)과 관련 있으며, 이러한 특징을 활용한 가상현실기반 과제는 새로운 인지기능 평가의 대안으로 제시할 수 있다.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 subjects’ 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 92박

Technology and Caregiving: Emerging Interventions and Directions for Research.

An array of technology-based interventions has increasingly become available to support family caregivers, primarily focusing on health and well-being, social isolation, financial, and psychological support. More recently the emergence of new technologies such as mobile and cloud, robotics, connected sensors, virtual/augmented/mixed reality, voice, and the evermore ubiquitous tools supported by advanced data analytics, coupled with the integration of multiple technologies through platform solutions, have opened a new era of technology-enabled interventions that can empower and support family caregivers. This paper proposes a conceptual framework for identifying and addressing the challenges that may need to be overcome to effectively apply technology-enabled solutions for family caregivers. The paper identifies a number of challenges that either moderate or mediate the full use of technologies for the benefit of caregivers. The challenges include issues related to equity, inclusion, and access; ethical concerns related to privacy and security; political and regulatory factors affecting interoperability and lack of standards; inclusive/human-centric design and issues; and inherent economic and distribution channel difficulties. The paper concludes with a summary of research questions and issues that form a framework for global research priorities

Review of innovative immersive technologies for healthcare applications

Immersive technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), can connect people using enhanced data visualizations to better involve stakeholders as integral members of the process. Immersive technologies have started to change the research on multidimensional genomic data analysis for disease diagnostics and treatments. Immersive technologies are highlighted in some research for health and clinical needs, especially for precision medicine innovation. The use of immersive technology for genomic data analysis has recently received attention from the research community. Genomic data analytics research seeks to integrate immersive technologies to build more natural human-computer interactions that allow better perception engagements. Immersive technologies, especially VR, help humans perceive the digital world as real and give learning output with lower performance errors and higher accuracy. However, there are limited reviews about immersive technologies used in healthcare and genomic data analysis with specific digital health applications. This paper contributes a comprehensive review of using immersive technologies for digital health applications, including patient-centric applications, medical domain education, and data analysis, especially genomic data visual analytics. We highlight the evolution of a visual analysis using VR as a case study for how immersive technologies step, can by step, move into the genomic data analysis domain. The discussion and conclusion summarize the current immersive technology applications’ usability, innovation, and future work in the healthcare domain, and digital health data visual analytics

A framework for AI-driven neurorehabilitation training: the profiling challenge

Cognitive decline is a common sign that a person is ageing. However, abnormal cases can lead to dementia, affecting daily living activities and independent functioning. It is a leading cause of disability and death. Its prevention is a global health priority. One way to address cognitive decline is to undergo cognitive rehabilitation. Cognitive rehabilitation aims to restore or mitigate the symptoms of a cognitive disability, increasing the quality of life for the patient. However, cognitive rehabilitation is stuck to clinical environments and logistics, leading to a suboptimal set of expansive tools that is hard to accommodate every patient’s needs. The BRaNT project aims to create a tool that mitigates this problem. The NeuroAIreh@b is a rehabilitation tool developed within a framework that combines neuropsychological assessments, neurorehabilitation procedures, artificial intelligence and game design, composing a tool that is easy to set up in a clinical environment and accessible to adapt to every patient’s needs. Among all the challenges within NeuroAlreh@b, one focuses on representing a cognitive profile through the aggregation of multiple neuropsychological assessments. To test this possibility, we will need data from patients currently unavailable. In the first part of this master’s project, study the possibility of aggregating neuropsychological assessments for the case of Alzheimer’s disease using the Alzheimer’s Disease Neuroimaging Initiative database. This database contains a vast collection of images and neuropsychological assessments that will serve as a baseline for the NeuroAlreh@b when the time comes. In the second part of this project, we set up a computational system to run all the artificial intelligence models and simulations required for the BRaNT project. The system allocates a database and a webserver to serve all the required pages for the project.O declínio cognitivo é um sinal comum de que uma pessoa está a envelhecer. No entanto, casos anormais podem levar à demência, afetando as atividades diárias e funcionamento independente. Demência é uma das principais causas de incapacidade e morte. Fazendo da sua prevenção uma prioridade para a saúde global. Uma forma de lidar com o declínio cognitivo é submeter-se à reabilitação cognitiva. A reabilitação cognitiva visa restaurar ou mitigar os sintomas de uma deficiência cognitiva, aumentando a qualidade de vida do paciente. No entanto, a reabilitação cognitiva está presa a ambientes clínicos e logística, levando a um conjunto sub-ideal de ferramentas com custos elevados e complicadas de acomodar as necessidades de cada paciente. O projeto BRaNT visa criar uma ferramenta que atenue este problema. O NeuroAIreh@b é uma ferramenta de reabilitação desenvolvida num quadro que combina avaliações neuropsicológicas, reabilitação, inteligência artificial e design de jogos, compondo uma ferramenta fácil de adaptar a um ambiente clínico e acessível para se adaptar às necessidades de cada paciente. Entre todos os desafios dentro de NeuroAlreh@b, foca-se em representar um perfil cognitivo através da agregação de múltiplas avaliações neuropsicológicas. Para testar esta possibilidade, precisaremos de dados de pacientes, que atualmente não temos. Na primeira parte do projeto deste mestrado, vamos testar a possibilidade de agregar avaliações neuropsicológicas para o caso da doença de Alzheimer utilizando a base de dados da Iniciativa de Neuroimagem da Doença de Alzheimer. Esta base de dados contém uma vasta coleção de imagens e avaliações neuropsicológicas que servirão de base para o NeuroAlreh@b quando chegar a hora. Na segunda parte deste projeto, vamos criar um sistema informático para executar todos os modelos e simulações de inteligência artificial necessários para o projeto BRaNT. O sistema também irá alocar uma base de dados e um webserver para servir todas as páginas necessárias para o projeto