Older adults' communication with an interactive humanoid robot : Expectations and experiences of older adults in verbal and nonverbal communication with a socially interactive humanoid robot: a mixed methods design in Germany.

BACKGROUND AND OBJECTIVE: One possible approach to counter singularization and loneliness of older adults is the development and implementation of socially interactive robots. Little is known about the expectations and experiences of older adults with socially interactive humanoid robots. MATERIAL AND METHODS: In a mixed-methods design study, user expectations before interaction and the experience and evaluation of verbal and non-verbal communication after interaction with a robot were assessed. Semi-structured interviews were conducted after the interaction. RESULTS: The majority of older adults expected verbal communication. After the interaction the evaluation of the quality of verbal communication differed. Participants did not expect any form of nonverbal communication. Nonverbal communication was highlighted as particularly positive. Gestures, facial expressions, and body movements were described as confidence building. CONCLUSION: The robot's ability to communicate nonverbally might positively influence older adults' experience of communication with the robot. In the development of socially interactive robots non-verbal communication should be given more consideration in order to contribute to successful human-robot interaction.

Evaluation and intention to use the interactive robotic kitchen system AuRorA in older adults.

BACKGROUND: The number of older adults in need of care and living at home is increasing in Europe. At the same time, the number of professional caregivers is decreasing. This development reinforces the need for assistive technology to support care recipients in their own homes and promote their independence. One of the main challenges of independent living is the preparation of food. Interactive robots could assist older adults with difficulties performing physically demanding tasks. Within the project AuRorA (full German project title: Wiederverwendbare, interaktive Verhalten für proaktive Roboter im Smart Home), an interactive voice-controlled robot arm was developed as an assistance system in the kitchen. OBJECTIVE: The aim of the study was to assess how older adults evaluate the AuRorA system and to collect data on actual willingness to use the technology. Older adults were asked to evaluate the system in terms of usefulness, usability, accessibility and intention to use. MATERIAL AND METHODS: Due to the ongoing coronavirus disease 2019 (COVID-19) pandemic, the older adults evaluated the system via an online survey. The validated questionnaire Technology Usage Inventory (short: TUI) was used in conjunction with self-developed questionnaires to collect data on study population characteristics. RESULTS: A total of 106 participants were included in the analysis. The acceptance, usability and usefulness of the system were rated as medium, while the intention to use was rated as low. A significant strong correlation was found between the TUI subscales intention to use and usefulness. CONCLUSION: It can be assumed that the actual need of the individual participant for such a robotic assistive system had an influence on the evaluation of the system. The perceived usefulness may have been a crucial influence on the intention to use and the overall assessment of the system.

[Use of technology in old age: associations between acceptance, competence, control, interest and social indicators in individuals over 60 years old]. / Technologienutzung im Alter: Zusammenhänge zwischen Akzeptanz, Kompetenz, Kontrolle, Interesse und sozialen Indikatoren bei Personen über 60 Jahre.

BACKGROUND: In addition to sociodemographic factors, action-theoretical constructs, such as technology acceptance and competence play an important role in technology use. OBJECTIVE: This study aimed to examine the associations between technology use, sociodemographic factors, action-theoretical constructs, and technology interest. MATERIAL AND METHODS: Data were collected from 585 study participants aged over 60 years from 14 surveys conducted between 2014 and 2020. A structural equation model was used to explain the relationships. RESULTS: The structural equation model with covariates of survey year, age, gender, and education (n = 585) yielded the following fit indices: comparative fit index (CFI) = 0.918, Tucker-Lewis index (TLI) = 0.894, Root Mean Square Error of Approximation (RMSEA) = 0.056 [95 % confidence interval: 0.050-0.063], Standardized Root Mean Square Residual (SRMR) = 0.079, χ2 = 3051.936 (p < 0.001), χ2/degrees of freedom (df) = 18.499. The strongest associations with technology use were found for technology acceptance and competence. Additionally, technology competence showed a significant association with technology interest. Gender and technology interest were not related to technology use but it was observed that men had higher levels of technology acceptance, control, competence, and interest. DISCUSSION: Taking technology competence beliefs into account plays a crucial role in understanding the technology usage and interest of older individuals. Additionally, gender-specific differences in the theoretical constructs of action and interest in technology have been revealed in the context of the digital divide.

Contraction assessment of abdominal muscles using automated segmentation designed for wearable ultrasound applications.

PURPOSE: Wearable ultrasound devices can be used to continuously monitor muscle activity. One possible application is to provide real-time feedback during physiotherapy, to show a patient whether an exercise is performed correctly. Algorithms which automatically analyze the data can be of importance to overcome the need for manual assessment and annotations and speed up evaluations especially when considering real-time video sequences. They even could be used to present feedback in an understandable manner to patients in a home-use scenario. The following work investigates three deep learning based segmentation approaches for abdominal muscles in ultrasound videos during a segmental stabilizing exercise. The segmentations are used to automatically classify the contraction state of the muscles. METHODS: The first approach employs a simple 2D network, while the remaining two integrate the time information from the videos either via additional tracking or directly into the network architecture. The contraction state is determined by comparing measures such as muscle thickness and center of mass between rest and exercise. A retrospective analysis is conducted but also a real-time scenario is simulated, where classification is performed during exercise. RESULTS: Using the proposed segmentation algorithms, 71% of the muscle states are classified correctly in the retrospective analysis in comparison to 90% accuracy with manual reference segmentation. For the real-time approach the majority of given feedback during exercise is correct when the retrospective analysis had come to the correct result, too. CONCLUSION: Both retrospective and real-time analysis prove to be feasible. While no substantial differences between the algorithms were observed regarding classification, the networks incorporating the time information showed temporally more consistent segmentations. Limitations of the approaches as well as reasons for failing cases in segmentation, classification and real-time assessment are discussed and requirements regarding image quality and hardware design are derived.

Effectiveness of a mobile application for independent computerized cognitive training in patients with mild cognitive impairment: study protocol for the NeNaE Study, a randomized controlled trial.

BACKGROUND: Mild cognitive impairment (MCI) involves cognitive decline beyond typical age-related changes, but without significant daily activity disruption. It can encompass various cognitive domains as the causes of MCI are diverse. MCI as well as frequent comorbid neuropsychiatric conditions like depression and anxiety affect individuals' quality of life. Early interventions are essential, and computerized cognitive training (cCT) is an established treatment method. This paper presents the protocol for the NeuroNation MED Effectiveness Study, evaluating the self-administered mobile cCT intervention ("NeuroNation MED") in individuals with MCI to assess training effects on cognitive domains, health competence, neuropsychiatric symptoms, psychological well-being, and the general application usability. METHODS: This study protocol presents a single-blinded multicenter randomized controlled trial that will be carried out in six study centers in Germany and Luxembourg. We included adults with MCI (existing F06.7 ICD-10-GM diagnosis and TICS ≥ 21 and ≤ 32). The intervention group will use a mobile, multi-domain cCT ("NeuroNation MED") for 12 weeks. Meanwhile, the wait list control group will receive standard medical care or no care. The eligibility of volunteers will be determined through a telephone screening. After completion of the baseline examination, patients will be randomly assigned to one of the experimental conditions in a 2:1 ratio. In total, 286 participants will be included in this study. The primary outcome is the change of cognitive performance measured by the index score of the screening module of the Neuropsychological Assessment Battery. Secondary outcomes are changes in the Cognitive Failures Questionnaire, Hospital Anxiety and Depression Scale, Health-49, Health Literacy Questionnaire, among others. All of the primary and secondary outcomes will be assessed at baseline and after the 12-week post-allocation period. Furthermore, the intervention group will undergo an assessment of the System Usability Scale, and the training data of the NeuroNation MED application will be analyzed. DISCUSSION: This study aims to assess the effectiveness of a mobile self-administered cCT in enhancing cognitive abilities among individuals diagnosed with MCI. Should the findings confirm the effectiveness of the NeuroNation MED app, it may confer possible benefits for the care management of patients with MCI, owing to the accessibility, cost-effectiveness, and home-based setting it provides. Specifically, the cCT program could provide patients with personalized cognitive training, educational resources, and relaxation techniques, enabling participants to independently engage in cognitive training sessions at home without further supervision. TRIAL REGISTRATION: German Clinical Trials Register DRKS00025133. Registered on November 5, 2021.

Evaluation of the quality and the provision process of wheelchairs in Germany. Results from an online survey.

BACKGROUND: Restrictions in mobility can lead to social and health-related issues. Assistive technologies and devices can help to sustain or regain mobility in affected persons. One of the most commonly used devices is the wheelchair. Many wheelchair users experience difficulties within the provision process and with the device itself. The presented study investigated the satisfaction with the wheelchair and the corresponding provision process. METHODOLOGY: A comprehensive online survey was conducted. The questionnaire surveyed the quality of wheelchairs and the corresponding provision process among wheelchair users in Germany. Descriptive methods were used to analyse the results. Sub-groups were classified according to age, sex, waiting time for wheelchair, financing and type of wheelchair. RESULTS: After cleaning the data, 110 datasets remained for analysis. The predominant reasons for wheelchair acquisition were independence and the replacement for a defective wheelchair. Wheelchair quality aspects as well as the corresponding provision process were rated medium. Issues were found regarding waiting times, repair services and communication between service providers. DISCUSSION: The presented results reflect issues in the quality of wheelchairs and their provision process. Inequality between different sub groups is evident. Although some results should be considered with caution due to unequal group sizes, clear trends can be seen which confirm results from other studies throughout the literature. CONCLUSION: The presented cross-sectional study results give an important overview about the user satisfaction with the quality and provision process of wheelchairs. A longitudinal study accompanying users during the provision process is being recommended as a more in-depth study.IMPLICATIONS FOR REHABILITATIONLow durability and adaptability were identified as main issues regarding wheelchair quality.Waiting times for wheelchairs were perceived as too long by the users and make up the main factor for low satisfaction with the wheelchair provision process.Reduced waiting times for wheelchairs (especially for electric wheelchairs) can improve overall satisfaction with the assistive device.Waiting times could be reduced by a more efficient application and provision process.

Needs and Attitudes of Older Chronic Back Pain Patients towards a Wearable for Ultrasound Biofeedback during Stabilization Exercises: A Qualitative Analysis.

Chronic back pain has a high prevalence, especially in older adults, and seriously affects sufferers' quality of life. Segmental stabilization exercise (SSE) is often used during physiotherapy to enhance core stability. The execution of SSE requires the selective contraction of deep abdominal and back muscles. Motor learning can be supported using ultrasound imaging as visual biofeedback. ULTRAWEAR is a mobile ultrasound system that provides deep learning-based biofeedback on SSE execution, which is currently under development. We interviewed 15 older chronic back pain patients (CBPPs) to investigate their pain management behavior, experience with SSE, as well as their needs and requirements for ULTRAWEAR. We also gathered information about future-usage scenarios. CBPPs reported a high willingness to use the system as a feedback tool both in physiotherapeutic practices and at home. The automated detection and evaluation of muscle contraction states was highlighted as a major benefit of the system compared to the more subjective feedback provided by traditional methods such as palpation. The system to be developed was perceived as a helpful solution to support learning about SSE.