Corrigendum: Assimilation of socially assistive robots by older adults: an interplay of uses, constraints and outcomes.

[This corrects the article DOI: 10.3389/frobt.2024.

Assimilation of socially assistive robots by older adults: an interplay of uses, constraints and outcomes.

By supporting autonomy, aging in place, and wellbeing in later life, Socially Assistive Robots are expected to help humanity face the challenges posed by the rapid aging of the world's population. For the successful acceptance and assimilation of SARs by older adults, it is necessary to understand the factors affecting their Quality Evaluations Previous studies examining Human-Robot Interaction in later life indicated that three aspects shape older adults' overall QEs of robots: uses, constraints, and outcomes. However, studies were usually limited in duration, focused on acceptance rather than assimilation, and typically explored only one aspect of the interaction.

Comparison of proactive and reactive interaction modes in a mobile robotic telecare study.

Mobile robotic telepresence systems require that information about the environment, the task, and the robot be presented to a remotely located user (operator) who controls the robot for a specific task. In this study, two interaction modes, proactive and reactive, that differ in the way the user receives information from the robot, were compared in an experimental system simulating a healthcare setting. The users controlled a mobile telepresence robot that delivered and received items (medication, food, or drink), and also obtained metrics (vital signs) from a simulated patient while the users performed a secondary healthcare-related task (they compiled health records which were displayed to them on the screen and answered related questions).

Automatic Root Length Estimation from Images Acquired In Situ without Segmentation.

Image-based root phenotyping technologies, including the minirhizotron (MR), have expanded our understanding of the in situ root responses to changing environmental conditions. The conventional manual methods used to analyze MR images are time-consuming, limiting their implementation. This study presents an adaptation of our previously developed convolutional neural network-based models to estimate the total (cumulative) root length (TRL) per MR image without requiring segmentation.

Evaluating levels of automation with different feedback modes in an assistive robotic table clearing task for eldercare.

This paper focuses on how the autonomy level of an assistive robot that offers support for older adults in a daily task and its feedback affect the interaction. Identifying the level of automation (LOA) that prioritizes older adults' preferences while avoiding passiveness and sedentariness is challenging. The feedback mode should match the cognitive and perceptual capabilities of older adults and the LOA.