Infants at risk for developmental delays such as Cerebral Palsy, can often be distinguished through observation of their motion and postural stability. In an effort to provide more accessible and quantitative metrics for the early detection of such impairments, this study focuses on the development of a 6-degree of freedom (DOF) robotic infant simulator. The robotic simulator provides insight into the relationship between infant motion and center of pressure (COP), a common measure that is capable of distinguishing impaired infants through quantification of postural stability. We focus on the impact of a 2 DOF motion in the trunk on COP through two experiments where we 1) Compare the impacts on COP of the limbs and the trunk, and 2) Compare the robot's COP to a real infant's. Our results indicate that motion in the trunk plays a strong part in replicating an infant's COP. Additionally, we can observe that changes in COP exhibit clear and repeatable patterns with respect to motion in each DOF. Future directions suggest a look at how different motions in the trunk affect infant COP.

This work investigates the deployment of an affordable socially assistive robot (SAR) at an older adult day care setting for the screening of COVID-19 symptoms and exposure. Despite the focus on older adults, other stakeholders (clinicians and caregivers) were included in the study due to the need for daily COVID-19 screening. The investigation considered which aspects of human-robot-interaction (HRI) are relevant when designing social agents for patient screening. The implementation was based upon the current screening procedure adopted by the deployment facility, and translated into robot dialogues and gesturing motion. Post-interaction surveys with participants informed their preferences for the type of interaction and system usability. Observer surveys evaluated users’ reaction, verbal and physical engagement. Results indicated general acceptance of the social agent and possible improvements to the current version of the robot to encourage a broader adoption by the stakeholders.

In this paper a novel telescopic manipulator was adapted to a mobile robotic base to perform manipulation tasks in an elder care facility. As indicated by our previous work, leisure activities and engagement in socialization were desirable among elders, and a physical game assisted by the robot was chosen to investigate both its acceptance and interaction with the older adults. The robot was deployed at an assisted living center and performed multiple interactions. The manipulator was able to successfully retrieve items from different heights as part of the game and results from post-interaction surveys with elders indicated high perceived usefulness and comfort in having the robot as an assistant in the game.

This paper presents findings from two deployments of an autonomous mobile robot in older adult low income Supportive Apartment Living (SAL) facilities. Design guidelines for the robot hardware and software were based on query of clinicians, caregivers and older adults through focus groups, member checks and surveys, to identify what each group believed to be the most important daily activities for older adults to accomplish physically, mentally and socially. After data analysis, hydration and walking encouragement were found to be critical daily activities, becoming the focus of our deployments. The aim of the deployments was to understand the efficacy of human-robot interaction and identify ways to enhance the robot design and programming. Through observation of older adults interacting with the robot and post-interaction surveys filled out by the older adults, conclusions were drawn for further advancement of the robot development to be tested in future deployments. Results overall indicated high perceived usefulness and growing acceptance of the robot by older adults with increased interactions.

The 16 papers in this special section have been logically organized into four different groups: enabling technologies for rehabilitation robotics; two robotic systems used for assisted diagnosis of pathologies of interest in the rehabilitation domain; different robotic systems applied to assisted physical rehabilitation; and robotic systems used for assisted psychophysiological rehabilitation.

A task-oriented robot-assisted therapy environment to support activities of daily living tasks was developed with the goals of addressing some of the shortcomings of current robotic therapy systems. An important aspect of making these environments work is the implementation of trajectory planning algorithms that support the naturally curving wrist movement seen in real life functional tasks. We explore the challenge of naturally supporting the positioning of the wrist for activities of daily living tasks such as drinking and feeding. In this paper, we examine the minimum jerk model often used to define trajectory planning routines to automatically position the wrist and present the results of fitting these two models to natural wrist movements for a drinking task. Also, we present a case study to examine how an able-bodied experienced the two models as implemented on the ADLER, task-oriented robot-assisted therapy environment.

The need for effective and low-cost ways of facilitating upper limb therapy for individuals recovering from stroke has led to the Driver's Simulation Environment for Arm Therapy (Driver's SEAT). This assistive device is an upper limb one-degree-of-freedom robotic therapy device that incorporates a modified PC-based driving simulator. This paper describes the novel use of a driving simulator to implement an upper limb bimanual exercise task and presents control algorithms that use torque feedback as a method of encouraging the preferential use of one limb over another. The key feature is a split steering wheel, which allows us to measure the tangential forces applied to the wheel by the subjects' impaired and unimpaired upper limbs independently. We present experimental results to show Driver's SEAT's ability to measure bilateral forces and quantify tracking performance.