Autonomic nervous activity of patient with schizophrenia during Pepper CPGE-led upper limb range of motion exercises

Compassionate Care with Autonomous AI Humanoid Robots in Future Healthcare Delivery: A Multisensory Simulation of Next-Generation Models

The integration of AI and robotics in healthcare raises concerns, and additional issues regarding autonomous systems are anticipated. Effective communication is crucial for robots to be seen as "caring", necessitating advanced mechatronic design and natural language processing (NLP). This paper examines the potential of humanoid robots to autonomously replicate compassionate care. The study employs computational simulations using mathematical and agent-based modeling to analyze human-robot interactions (HRIs) surpassing Tetsuya Tanioka's TRETON. It incorporates stochastic elements (through neuromorphic computing) and quantum-inspired concepts (through the lens of Martha Rogers' theory), running simulations over 100 iterations to analyze complex behaviors. Multisensory simulations (visual and audio) demonstrate the significance of "dynamic communication", (relational) "entanglement", and (healthcare system and robot's function) "superpositioning" in HRIs. Quantum and neuromorphic computing may enable humanoid robots to empathetically respond to human emotions, based on Jean Watson's ten caritas processes for creating transpersonal states. Autonomous AI humanoid robots will redefine the norms of "caring". Establishing "pluralistic agreements" through open discussions among stakeholders worldwide is necessary to align innovations with the values of compassionate care within a "posthumanist" framework, where the compassionate care provided by Level 4 robots meets human expectations. Achieving compassionate care with autonomous AI humanoid robots involves translating nursing, communication, computer science, and engineering concepts into robotic care representations while considering ethical discourses through collaborative efforts. Nurses should lead the design and implementation of AI and robots guided by "technological knowing" in Rozzano Locsin's TCCN theory.

The impact of a mixed reality technology-driven health enhancing physical activity program among community-dwelling older adults: a study protocol

Background

Physical inactivity and a sedentary lifestyle among community-dwelling older adults poses a greater risk for progressive physical and cognitive decline. Mixed reality technology-driven health enhancing physical activities such as the use of virtual coaches provide an emerging and promising solution to support healthy lifestyle, but the impact has not been clearly understood.

Methods and analysis

An observational explanatory sequential mixed-method research design was conceptualized to examine the potential impact of a user-preferred mixed reality technology-driven health enhancing physical activity program directed toward purposively selected community-dwelling older adults in two senior centers in the Philippines. Quantitative components of the study will be done through a discreet choice experiment and a quasi-experimental study. A total of 128, or 64 older adults in each center, will be recruited via posters at community senior centers who will undergo additional screening or health records review by a certified gerontologist to ensure safety and proper fit. Treatments (live coaching with video-based exercise and mixed reality technology-driven exercise) will be assigned to each of the two senior center sites for the quasi-experiment. The participants from the experimental group shall be involved in the discreet choice experiment, modeling, and usability evaluations. Finally, a qualitative sample of participants (n = 6) as key informants shall be obtained from the experimental group using purposive selection.

Discussion

This study protocol will examine the health impact of a promising mixed reality program in health promotion among older adults. The study utilizes a human-centered mixed method research design in technology development and evaluation in the context of developing nations.Clinical trial registration: ClinicalTrials.gov, identifier NCT06136468.

An empirical investigation into the preferences of the elderly for user interface design in personal electronic health record systems

Background

With the continuous advancement of digital technologies, electronic Personal Health Records (ePHR) offer end-users greater control and convenience over their health data. Although ePHR are perceived as innovative tools in medical services that provide patient-centered care and disease prevention, many system interfaces are inclined toward younger users, overlooking investigations pertinent to elderly users. Our objective is to uncover the preferences of the elderly for an ideal ePHR system interface.

Materials and methods

Relying on a literature review, we identified six interface attributes. Utilizing conjoint analysis, we constructed 16 representative design scenarios based on orthogonal design by combining different attribute levels. We invited 187 elderly participants to evaluate these scenarios. Data analysis was performed using SPSS 26.0. The results indicate that among the ePHR interface design attributes, the elderly prioritize color attributes, followed by the notification method. Designs with contrasting color schemes, skeuomorphic design approaches, and icon-centric menu navigation with segmented layouts, and voice notifications when a message is received, are the most preferred interface design choices.

Discussion

This research elucidates the ideal interface design elements for ePHR as perceived by the elderly, offering valuable references for age-friendly design considerations in ePHR systems.

Results

Implementing these insights can aid in promoting mobile health services among the elderly demographic, enhancing their user experience in health management interfaces. This, in turn, fosters the widespread adoption of mobile health service technologies, further advancing the development of a healthy aging society.

Nursing and human-computer interaction in healthcare robots for older people: An integrative review

Objectives

This study examined the published works related to healthcare robotics for older people using the attributes of health, nursing, and the human-computer interaction framework.

Design

An integrative literature review.

Methods

A search strategy captured 55 eligible articles from databases (CINAHL, Embase, IEEE Xplore, and PubMed) and hand-searching approaches. Bibliometric and content analyses grounded on the health and nursing attributes and human-computer interaction framework were performed using MAXQDA. Finally, results were verified using critical friend feedback by a second reviewer.

Results

Most articles were from multiple authorship, published in non-nursing journals, and originating from developed economies. They primarily focused on applying healthcare robots in practice settings, physical health, and communication tasks. Using the human-computer interaction framework, it was found that older adults frequently served as the primary users while nurses, healthcare providers, and researchers functioned as secondary users and operators. Research articles focused on the usability, functionality, and acceptability of robotic systems. At the same time, theoretical papers explored the frameworks and the value of empathy and emotion in robots, human-computer interaction and nursing models and theories supporting healthcare practice, and gerontechnology. Current robotic systems are less anthropomorphic, operated through real-time direct and supervisory inputs, and mainly equipped with visual and auditory sensors and actuators with limited capability in performing health assessments.

Conclusion

Results communicate the need for technological competency among nurses, advancements in increasing healthcare robot humanness, and the importance of conscientious efforts from an interdisciplinary research team in improving robotic system usability and utility for the care of older adults.

Usefulness of 2D Video Analysis for Evaluation of Shoulder Range of Motion during Upper Limb Exercise in Patients with Psychiatric Disorders

Aging and its associated problems related to movement impacts the care of people with psychiatric disorders. This study sought to clarify the usefulness of 2D video analysis for evaluating shoulder range of motion (ROM) during upper limb exercises in patients with psychiatric disorders. Subjects (N=54) were patients with psychiatric disorders categorized as the following:having either a high or low activities of daily living (ADL) score using the Barthel Index;experiencing shoulder ROM limitation, and whether or not compensatory movements were exhibited. Compensatory movement was also considered in patients with Parkinsonism, cerebrovascular disease, and cognitive dysfunction. Shoulder joint ROM was measured using a goniometer and active ROM was captured using ImageJ. No significant difference between passive ROM measured by a goniometer and active ROM measured by ImageJ considering disease groups, ADL level, and shoulder ROM limitation was found. Factoring in compensatory movements, however, significant differences were found between passive and active ROM:existence compensatory movement group, left side (z=-2.30, p=0.02);nonexistence compensatory movement group, right side (z=-2.63, p<0.001). Image-evaluating devices help assess ROM in patients with psychiatric disorders, enhancing the development of physical rehabilitation programs to regain critical ADL, sustaining self-care capabilities. J. Med. Invest. 69 : 70-79, February, 2022.

Intentional Observational Clinical Research Design: Innovative Design for Complex Clinical Research Using Advanced Technology

The growing use of robots in nursing and healthcare facilities has prompted increasing research on human–robot interactions. However, specific research designs that can guide researchers to conduct rigorous investigations on human–robot interactions are limited. This paper aims to discuss the development and application of a new research design—the Intentional Observational Clinical Research Design (IOCRD). Data sources to develop the IOCRD were derived from surveyed literature of the past decade, focusing on clinical nursing research and theories relating robotics to nursing and healthcare practice. The distinction between IOCRD and other research design is the simultaneous data generation collected using advanced technological devices, for example, the wireless Bonaly-light electrocardiogram (ECG) to track heart rate variability of research subjects, robot application programs on the iPad mini to control robot speech and gestures, and Natural Language Processing programs. Even though IOCRD was developed for human–robot research, there remain vast opportunities for its use in nursing practice and healthcare. With the unique feature of simultaneous data generation and analysis, an interdisciplinary collaborative research team is strongly suggested. The IOCRD is expected to contribute guidance for researchers in conducting clinical research related to robotics in nursing and healthcare.

Intelligent humanoid robots expressing artificial humanlike empathy in nursing situations

Intelligent humanoid robots (IHRs) are becoming likely to be integrated into nursing practice. However, a proper integration of IHRs requires a detailed description and explanation of their essential capabilities, particularly regarding their competencies in replicating and portraying emotive functions such as empathy. Existing humanoid robots can exhibit rudimentary forms of empathy; as these machines slowly become commonplace in healthcare settings, they will be expected to express empathy as a natural function, rather than merely to portray artificial empathy as a replication of human empathy. This article works with a twofold purpose: firstly, to consider the impact of artificial empathy in nursing and, secondly, to describe the influence of Affective Developmental Robotics (ADR) in anticipation of the empathic behaviour presented by artificial humanoid robots. The ADR has demonstrated that it can be one means by which humanoid nurse robots can achieve expressions of more relatable artificial empathy. This will be one of the vital models for intelligent humanoid robots currently in nurse robot development for the healthcare industry. A discussion of IHRs demonstrating artificial empathy is critical to nursing practice today, particularly in healthcare settings dense with technology.