Custom-designed motion-based games for older adults: a review of literature in human-computer interaction

Many older adults, particularly persons living in senior residences and care homes, lead sedentary lifestyles, which reduces their life expectancy. Motion-based video games encourage physical activity and might be an opportunity for these adults to remain active and engaged; however, research efforts in the field have frequently focused on younger audiences and little is known about the requirements and benefits of motion-based games for elderly players. In this paper, we present an overview of motion-based video games and other interactive technologies for older adults. First, we summarize existing approaches towards the definition of motion-based video games – often referred to as exergames – and suggest a categorization of motion-based applications into active video games, exergames, and augmented sports. Second, we use this scheme to classify case studies addressing design efforts particularly directed towards older adults. Third, we analyze these case studies with a focus on potential target audiences, benefits, challenges in their deployment, and future design opportunities to investigate whether motion-based video games can be applied to encourage physical activity among older adults. In this context, special attention is paid to evaluation routines and their implications regarding the deployment of such games in the daily lives of older adults. The results show that many case studies examine isolated aspects of motion-based game design for older adults, and despite the broad range of issues in motion-based interaction for older adults covered by the sum of all research projects, there appears to be a disconnect between laboratory-based research and the deployment of motion-based video games in the daily lives of senior citizens. Our literature review suggests that despite research results suggesting various benefits of motion-based play for older adults, most work in the field of game design for senior citizens has focused on the implementation of accessible user interfaces, and that little is known about the long-term deployment of video games for this audience, which is a crucial step if these games are to be implemented in activity programs of senior residences, care homes, or in therapy

Fuzzy adaptive cognitive stimulation therapy generation for Alzheimer’s sufferers: Towards a pervasive dementia care monitoring platform

In this paper, we present a novel system for cognitive stimulation therapy to progressively assess cognitive impairment and emotional well-being of dementia patients in social care settings. The system assesses patients interactions and computes performance scores for different areas of cognitive stimulation. Patient interactions are initially classified into predefined performance categories through clustering of a sampled population. New personalized stimulation plans tailored to match the patient’s changing level of impairment are generated automatically through a set of fuzzy rule based systems using quantitative attributes and the overall scores of patients interactions. Therapists can redefine, evaluate and adjust the rules governing difficulty and activity levels for different stimulation areas to fine tune generated activity plans. The system can also be combined with an Internet of Things (IoT) enabled patient dialogue system for determining the affective state of participants during therapy sessions that could be used as a pervasive condition monitoring platform. Experiments consisting of therapy sessions of patients interacting with the system were performed in which the activity plans were automatically generated. Initial results showed that the system outputs were in agreement with the therapists own assessment in most of the stimulation areas. Simulation experiments were also conducted to analyse the system performance over multiple sessions. The results suggest that the system is able to adapt therapy plans overtime in response to changing levels of impairment/performance while supporting therapists to tune and evaluate therapy plans more effectively

The Users' Perspective on the Privacy-Utility Trade-offs in Health Recommender Systems

Privacy is a major good for users of personalized services such as recommender systems. When applied to the field of health informatics, privacy concerns of users may be amplified, but the possible utility of such services is also high. Despite availability of technologies such as k-anonymity, differential privacy, privacy-aware recommendation, and personalized privacy trade-offs, little research has been conducted on the users' willingness to share health data for usage in such systems. In two conjoint-decision studies (sample size n=521), we investigate importance and utility of privacy-preserving techniques related to sharing of personal health data for k-anonymity and differential privacy. Users were asked to pick a preferred sharing scenario depending on the recipient of the data, the benefit of sharing data, the type of data, and the parameterized privacy. Users disagreed with sharing data for commercial purposes regarding mental illnesses and with high de-anonymization risks but showed little concern when data is used for scientific purposes and is related to physical illnesses. Suggestions for health recommender system development are derived from the findings.Comment: 32 pages, 12 figure

Biosignal controlled recommendation in entertainment systems

With the explosive growth of the entertainment contents and the ubiquitous access of them via fixed or mobile computing devices, recommendation systems become essential tools to help the user to find the right entertainment at the right time and location. I envision that by integrating the bio signal input into the recommendation process, it will help the users not only to find interesting contents, but also to increase one’s comfort level by taking into account the biosginal feedback from the users. The goal of this project was to develop a biosignal controlled entertainment recommendation system that increases the user’s comfort level by reducing the level of stress. As the starting point, this project aims to contribute to the field of recommendation systems with two points. The first is the mechanism of embedding the biosignal non-intrusively into the recommendation process. The second is the strategy of the biosignal controlled recommendation to reduce stress. Heart rate controlled in-flight music recommendation is chosen as its application domain. The hypothesis of this application is that, the passenger's heart rate deviates from the normal due to unusual long haul flight cabin environment. By properly designing a music recommendation system to recommend heart rate controlled personalized music playlists to the passenger, the passengers' heart rate can be uplifted, down-lifted back to normal or kept within normal, thus their stress can be reduced. Four research questions have been formulated based on this hypothesis. After the literature study, the project went mainly through three phases: framework design, system implementation and user evaluation to answer these research questions. During the framework design phase, the heart rate was firstly modeled as the states of bradycardia, normal and tachycardia. The objective of the framework is that, if the user's heart rate is higher or lower than the normal heart rate, the system recommends a personalized music playlist accordingly to transfer the user’s heart rate back to normal, otherwise to keep it at normal. The adaptive framework integrates the concepts of context adaptive systems, user profiling, and the methods of using music to adjust the heart rate in a feedback control system. In the feedback loop, the playlists were composed using a Markov decision process. Yet, the framework allows the user to reject the recommendations and to manually select the favorite music items. During this process, the system logs the interactions between the user and the system for later learning the user’s latest music preferences. The designed framework was then implemented with platform independent software architecture. The architecture has five abstraction levels. The lowest resource level contains the music source, the heart rate sensors and the user profile information. The second layer is for resource management. In this layer are the manager components to manage the resources from the first layer and to modulate the access from upper layers to these resources. The third layer is the database, acting as a data repository. The fourth layer is for the adaptive control, which includes the user feedback log, the inference engine and the preference learning component. The top layer is the user interface. In this architecture, the layers and the components in the layers are loosely coupled, which ensures the flexibility. The implemented system was used in the user experiments to validate the hypothesis. The experiments simulated the long haul flights from Amsterdam to Shanghai with the same time schedule as the KLM flights. Twelve subjects were invited to participate in the experiments. Six were allocated to the controlled group and others were allocated to the treatment group. In addition to a normal entertainment system for the control group, the treatment group was also provided with the heart rate controlled music recommendation system. The experiments results validated the hypothesis and answered the research questions. The passenger's heart rate deviates from normal. In our user experiments, the passenger's heart rate was in the bradycardia state 24.6% of time and was in the tachycardia state 7.3% of time. The recommended uplifting music reduces the average bradycardia state duration from 14.78 seconds in the control group to 6.86 seconds in the treatment group. The recommended keeping music increases the average normal state duration from 24.66 seconds in the control group to 29.79 seconds in the treatment group. The recommended down-lifting music reduces the average tachycardia state duration from 13.89 seconds in the control group to 6.53 seconds in the treatment group. Compared to the control group, the stress of the treatment group has been reduced significantly

Information Technologies for Cognitive Decline

Information technology (IT) is used to establish a diagnosis and provide treatment for people with cognitive decline. The condition affects many before it becomes clear that more permanent changes, like dementia, could be noticed. Those who search for information are exposed to lots of information and different technologies which they need to make sense of and eventually use to help themselves. In this research literature and information available on the Internet were systematically analyzed to present methods used for diagnosis and treatment. Methods used for diagnosis are self-testing, sensors, Virtual Reality (VR), and brain imaging. Methods used for treatment are games, websites with information and media, Virtual Reality (VR), sensors, and robots. The resulting concept of knowledge was the basis of an artifact whose main goal was to present the facts to the broad public. This implied that a user-friendly artifact was developed through three iterations using the Design Science framework. A total of nine users and IT usability experts have evaluated the artifact returning the SUS score of 85,83 for users and 87,5 for IT usability experts. Nielsen´s heuristics were assessed by IT usability experts only, returning an average score of 4,28. The general response was positive regarding both the content and the attempt to present methods used in cognitive decline. It reminds to be seen how to bring this knowledge to those who are most affected by the decline.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

A study of virtual reality-mediated affective state and cognitive decline in Alzheimer’s disease

NeuroscienceLa démence de type d’Alzheimer est la plus commune des démences. Elle entraîne un déclin dans les capacités cognitives et fonctionnelles, se traduisant dans des difficultés au niveau de la prise de décision, de l’accomplissement de tâches quotidiennes, de la communication ainsi qu’au niveau de la mémoire et de l’attention. On remarque également une diminution de l’état émotionnel et une apathie chez ces patients. Ce mémoire explore une nouvelle approche pour atténuer les effets psychologiques et cognitifs de la maladie. Les recherches effectuées dans ce mémoire explorent les impacts cognitifs et les effets sur le bien-être d'une intervention utilisant la réalité virtuelle sur les personnes souffrant de déclin cognitif subjectif. Deux environnements virtuels ont été testés : le premier étant un environnement dans lequel le participant voyage en train à travers différents climats, et le second étant un environnement de musicothérapie qui s’adapte en fonction de la réponse émotionnelle du participant. Pour mesurer les impacts sur l'état affectif, des lectures électroencéphalographiques ont été prises et analysées afin de déduire l'émotion ressentie par le participant avant, pendant et après l'expérience. Les résultats montrent une amélioration générale de l'état émotionnel pour les deux environnements. Quant à la mesure des effets sur les fonctions cognitives, des tâches d'attention et de mémoire ont été effectuées par les participants avant et après l'immersion. Les résultats montrent une légère amélioration des capacités d'attention et une meilleure amélioration de la mémoire. Nous approprions cet écart dans l'expérience de musicothérapie à l'activation musicale d'un réseau de structures cérébrales impliquées dans les expériences agréables : le circuit de récompense. Nous proposons que la musique facilite la rétention de la mémoire chez les personnes souffrant de démence. En effet, les résultats de l’amélioration des fonctions cognitives pour les deux expériences précédentes dépendent fortement de la précision de l'outil de mesure cognitive utilisé pour évaluer les performances d'attention et de mémoire avant et après l'intervention. Pour assurer cette précision, ce mémoire présente un outil de mesure des performances cognitives basé sur des tâches cognitives qui ont montré à plusieurs reprises leur fiabilité. Cet outil d’adresse aux personnes atteintes de la maladie d'Alzheimer pré-clinique et diagnostiquée.Alzheimer’s disease is an irreversible disease which causes progressive memory loss and cognitive decline, eventually leading to severe inability to perform basic day-to-day tasks. The urgency to find an effective cure to the disease is crucial, as the medical and economical spin-offs could be disastrous. The present thesis explores a novel approach to help attenuate the psychological and cognitive effects of the disease. The research carried out for this thesis explored cognitive effects and impacts on overall well-being of a virtual reality intervention on people suffering from subjective cognitive decline. Two virtual environments were tested: the first being an environment in which the participant travels through different climates by train, and the second being a music therapy environment modified as a function of emotional response. To measure the effects on affective state, electroencephalography readings were taken and analyzed to infer the emotion felt by the participant before, during the experiment. Results show a general improvement in emotional state. To measure the effects of the environments on cognitive functions, attention and memory tasks were carried out by the participants before and after the immersion. Results show a small improvement in attention skills and a more substantial improvement in memory skills. We appropriate this discrepancy in the music therapy experiment to the musical activation of a network of brain structures involved in rewarding and pleasurable experiences. We propose that music could facilitate memory retention in people sufferance for dementia. Importantly, the results of the previous experiments rely heavily on the accuracy of the cognitive measurement tool used to evaluate attention and memory performances before and after the intervention. To provide this accuracy, this thesis presents a cognitive performance measurement tool based on cognitive tasks which have repeatedly shown to output reliable results. This tool is created to serve for people with pre-clinical Alzheimer’s disease and diagnosed Alzheimer’s disease. Additionally, this tool is designed in such a way as to minimize the effects of repetition as well as varying levels of education and language. This thesis presents a novel and promising research in the realms of computer sciences and health care

Recommending video content for use in group-based reminiscence therapy

REMPAD is a semi-automated cloud-based system used to facilitate digital reminiscence therapy for patients with mild-to-moderate dementia, enacted in a group setting. REMPAD uses profiles for participants and groups to proactively recommend interactive video content from the Internet to match these profiles. In this chapter, we focus on the design of the system and then the system architecture, the system build, data curation, and usage scenarios. We also report a series of steps carried out as part of our user-centered design approach to system development, and a series of analyses on interaction logs which indicate various levels of effectiveness for different configurations of the recommendation algorithm we use. The results indicate high user satisfaction when using the system, and strong tendency towards repeated use in future