Intelligent sensing technologies for the diagnosis, monitoring and therapy of alzheimer’s disease:A systematic review

Alzheimer’s disease is a lifelong progressive neurological disorder. It is associated with high disease management and caregiver costs. Intelligent sensing systems have the capability to provide context-aware adaptive feedback. These can assist Alzheimer’s patients with, continuous monitoring, functional support and timely therapeutic interventions for whom these are of paramount importance. This review aims to present a summary of such systems reported in the extant literature for the management of Alzheimer’s disease. Four databases were searched, and 253 English language articles were identified published between the years 2015 to 2020. Through a series of filtering mechanisms, 20 articles were found suitable to be included in this review. This study gives an overview of the depth and breadth of the efficacy as well as the limitations of these intelligent systems proposed for Alzheimer’s. Results indicate two broad categories of intelligent technologies, distributed systems and self-contained devices. Distributed systems base their outcomes mostly on long-term monitoring activity patterns of individuals whereas handheld devices give quick assessments through touch, vision and voice. The review concludes by discussing the potential of these intelligent technologies for clinical practice while highlighting future considerations for improvements in the design of these solutions for Alzheimer’s disease

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Psychology, Learning, Technology

This open access book constitutes the refereed proceedings of 1st International Workshop on Psychology, Learning, Technology, PLT 2022, Foggia, Italy, during January 2022. The 8 full papers presented here were carefully reviewed and selected from 23 submissions. In addition, one invited paper is also included. Psychology, Learning, ad Technology Conference (PLT2022) aims to explore learning paths that incorporate digital technologies in innovative and transformative ways and the improvement of the psychological and relational life. The conference includes topics about the methodology of application of the ICT tools in psychology and education: from blended learning to the application of artificial intelligence in education; from the teaching, learning, and assessment strategies and practices to the new frontiers on Human-Computer Interaction

Persuasive Intelligence: On the Construction of Rhetor-Ethical Cognitive Machines

This work concerns the rhetorical and moral agency of machines, offering paths forward in machine ethics as well as problematizing the issue through the development and use of an interdisciplinary framework informed by rhetoric, philosophy of mind, media studies and historical narrative. I argue that cognitive machines of the past as well as those today, such as rapidly improving autonomous vehicles, are unable to make moral decisions themselves foremost because a moral agent must first be a rhetorical agent, capable of persuading and of being persuaded. I show that current machines, artificially intelligent or otherwise, and especially digital computers, are primarily concerned with control, whereas persuasive behavior requires an understanding of possibility. Further, this dissertation connects rhetorical agency and moral agency (what I call a rhetor-ethical constitution) by way of the Heraclitean notion of syllapsis ( grasping ), a mode of cognition that requires an agent to practice analysis and synthesis at once, cognizing the whole and its parts simultaneously. This argument does not, however, indicate that machines are devoid of ethical or rhetorical activity or future agency. To the contrary, the larger purpose of developing this theoretical framework is to provide avenues of research, exploration and experimentation in machine ethics and persuasion that have been overlooked or ignored thus far by adhering to restricted disciplinary programs; and, given the ontological nature of the ephemeral binary that drives digital computation, I show that at least in principle, computers share the syllaptic operating principle required for rhetor-ethical decisions and action