Use of a Humanoid Robot in Supporting Dementia Care: A Qualitative Analysis.

Introduction: Cognitive impairment significantly affects independence in persons with dementia, and consistent supervision is often needed. While interest has arisen in using humanoid robots, such as Pepper, to assist with daily caregiving activities, little is known about the perceptions of using Pepper to assist people with dementia. Objective: This study aimed to explore the perceptions of nonhealthcare workers, care partners, and healthcare workers on the use of a Pepper robot in dementia care. Methods: This was a secondary qualitative analysis. Data were collected from a pilot study conducted from November 2020 to March 2021 using an online survey. The survey consisted of quantitative and qualitative questions; this study only focused on the qualitative responses. The detailed procedures and the quantitative results were published elsewhere. Participants included nonhealthcare workers, care partners, and healthcare workers. Results: A total of 194 participants responded to the open-ended question. Participants described potential benefits of Pepper including assisting with daily activities, monitoring safety and medication use, initiating reminders, and promoting activities and social interactions. Participants had concerns about privacy, cost, poor acceptance/trust, Pepper making mistakes, limitations in environmental navigation and responding to emergencies, misuse of Pepper, and Pepper replacing humans. Participants suggested that Pepper should be tailored to each individual's background, preferences, and functions and recommended improving the logistics of using Pepper, offering more emotional support and responses, and using a more natural appearance and voice. Conclusion: Pepper may support dementia care; yet some concerns need to be addressed. Future research should consider incorporating these comments when designing robots for dementia care.

Short: Causal structural learning of conversational engagement for socially isolated older adults.

Social isolation has become a growing public health concern in older adults and older adults with mild cognitive impairment. Coping strategies must be developed to increase social contact for socially isolated older adults. In this paper, we explored the conversational strategy between trained conversation moderators and socially isolated adults during a conversational engagement clinical trial (Clinicaltrials.gov: NCT02871921). We carried out structural learning and causality analysis to investigate the conversation strategies used by the trained moderators to engage socially isolated adults in the conversation and the causal effects of the strategy on engagement. Causal relations and effects were inferred between participants' emotions, the dialogue strategies used by moderators, and participants' following emotions. The results found in this paper may be used to support the development of cost-efficient, trustworthy AI- and/or robot-based platform to promote conversational engagement for older adults to address the challenges in social interaction.

Cognitive Exercise for Persons with Alzheimer's Disease and Related Dementia Using a Social Robot.

Reminiscence therapy (RT) can improve the mood and communication of persons living with Alzheimer's Disease and Alzheimer's Disease related dementias (PLWD). Traditional RT requires professionals' facilitation, limiting its accessibility to PLWD. Social robotics has the potential to facilitate RT, enabling accessible, home-based RT. However, studies are needed to investigate how PLWD would perceive a robot-mediated RT (RMRT) and how to develop RMRT for positive user experience and successful adoption. In this paper, we developed a prototype of RMRT using a humanoid social robot and tested it with 12 participants (7 PLWD, 2 with mild cognitive impairment, and 3 informal caregivers). The robot automatically displayed a memory trigger on its tablet and engaged participants in a relatable conversation during RMRT. A mixed-method approach was employed to assess its acceptability and usability. Our results showed that PLWD had an overall positive user experience with the RMRT. Participants laughed and sang along with the robot during RMRT and demonstrated intention to use it. We additionally discussed robot control method and several critical problems for RMRT. The RMRT can facilitate both verbal and nonverbal social interaction for PLWD and holds promise for engaging, personalized, and efficient home-based cognitive exercises for PLWD.

A simulated experiment to explore robotic dialogue strategies for people with dementia.

Introduction: Persons with dementia (PwDs) often show symptoms of repetitive questioning, which brings great burdens on caregivers. Conversational robots hold promise of helping cope with PwDs' repetitive behavior. This paper develops an adaptive conversation strategy to answer PwDs' repetitive questions, follow up with new questions to distract PwDs from repetitive behavior, and stimulate their conversation and cognition. Methods: We propose a general reinforcement learning model to interact with PwDs with repetitive questioning. Q-learning is exploited to learn adaptive conversation strategy (from the perspectives of rate and difficulty level of follow-up questions) for four simulated PwDs. A demonstration is presented using a humanoid robot. Results: The designed Q-learning model performs better than random action selection model. The RL-based conversation strategy is adaptive to PwDs with different cognitive capabilities and engagement levels. In the demonstration, the robot can answer a user's repetitive questions and further come up with a follow-up question to engage the user in continuous conversations. Conclusions: The designed Q-learning model demonstrates noteworthy effectiveness in adaptive action selection. This may provide some insights towards developing conversational social robots to cope with repetitive questioning by PwDs and increase their quality of life.

Image transmission using Airy array beam.

An approach for image transmission based on the Airy array beam is proposed and demonstrated. The Airy array beam is generated by employing the product of a special cubic phase and a shift function at its Fourier plane. The image can be modulated into this Airy array beam by overlapping it at the Fourier plane of this beam. After passing through a certain distance, the image information can be recovered from the modulated Airy array beam by Fourier transform. Compared to the existing Airy array beam, higher integrity and image information quality can be achieved by increasing the width of the obstacle that blocks the propagation of these beams. The capability mentioned above is experimentally verified. Moreover, to research the diffraction of this Airy array beam in the scattering environment, the propagation process of this Airy array beam in a scattering medium is theoretically derived and numerically studied. The corresponding experiment demonstrates that the propagation process matches well with the numerical study and simulation.

A Systematic Review of Robotic Rehabilitation for Cognitive Training.

A large and increasing number of people around the world experience cognitive disability. Rehabilitation robotics has provided promising training and assistance approaches to mitigate cognitive deficits. In this article, we carried out a systematic review on recent developments in robot-assisted cognitive training. We included 99 articles in this work and described their applications, enabling technologies, experiments, and products. We also conducted a meta analysis on the articles that evaluated robot-assisted cognitive training protocol with primary end users (i.e., people with cognitive disability). We identified major limitations in current robotics rehabilitation for cognitive training, including the small sample size, non-standard measurement of training and uncontrollable factors. There are still multifaceted challenges in this field, including ethical issues, user-centered (or stakeholder-centered) design, the reliability, trust, and cost-effectiveness, personalization of the robot-assisted cognitive training system. Future research shall also take into consideration human-robot collaboration and social cognition to facilitate a natural human-robot interaction.

Gauging Working Memory Capacity From Differential Resting Brain Oscillations in Older Individuals With A Wearable Device.

Working memory is a core cognitive function and its deficits is one of the most common cognitive impairments. Reduced working memory capacity manifests as reduced accuracy in memory recall and prolonged speed of memory retrieval in older adults. Currently, the relationship between healthy older individuals' age-related changes in resting brain oscillations and their working memory capacity is not clear. Eyes-closed resting electroencephalogram (rEEG) is gaining momentum as a potential neuromarker of mild cognitive impairments. Wearable and wireless EEG headset measuring key electrophysiological brain signals during rest and a working memory task was utilized. This research's central hypothesis is that rEEG (e.g., eyes closed for 90 s) frequency and network features are surrogate markers for working memory capacity in healthy older adults. Forty-three older adults' memory performance (accuracy and reaction times), brain oscillations during rest, and inter-channel magnitude-squared coherence during rest were analyzed. We report that individuals with a lower memory retrieval accuracy showed significantly increased alpha and beta oscillations over the right parietal site. Yet, faster working memory retrieval was significantly correlated with increased delta and theta band powers over the left parietal sites. In addition, significantly increased coherence between the left parietal site and the right frontal area is correlated with the faster speed in memory retrieval. The frontal and parietal dynamics of resting EEG is associated with the "accuracy and speed trade-off" during working memory in healthy older adults. Our results suggest that rEEG brain oscillations at local and distant neural circuits are surrogates of working memory retrieval's accuracy and processing speed. Our current findings further indicate that rEEG frequency and coherence features recorded by wearable headsets and a brief resting and task protocol are potential biomarkers for working memory capacity. Additionally, wearable headsets are useful for fast screening of cognitive impairment risk.