Information Security in Medical Robotics: A Survey on the Level of Training, Awareness and Use of the Physiotherapist

Cybersecurity is becoming an increasingly important aspect to investigate for the adoption and use of care robots, in term of both patients’ safety, and the availability, integrity and privacy of their data. This study focuses on opinions about cybersecurity relevance and related skills for physiotherapists involved in rehabilitation and assistance thanks to the aid of robotics. The goal was to investigate the awareness among insiders about some facets of cybersecurity concerning human–robot interactions. We designed an electronic questionnaire and submitted it to a relevant sample of physiotherapists. The questionnaire allowed us to collect data related to: (i) use of robots and its relationship with cybersecurity in the context of physiotherapy; (ii) training in cybersecurity and robotics for the insiders; (iii) insiders’ self-assessment on cybersecurity and robotics in some usage scenarios, and (iv) their experiences of cyber-attacks in this area and proposals for improvement. Besides contributing some specific statistics, the study highlights the importance of both acculturation processes in this field and monitoring initiatives based on surveys. The study exposes direct suggestions for continuation of these types of investigations in the context of scientific societies operating in the rehabilitation and assistance robotics. The study also shows the need to stimulate similar initiatives in other sectors of medical robotics (robotic surgery, care and socially assistive robots, rehabilitation systems, training for health and care workers) involving insiders.

Social Robots for the Care of Persons with Dementia

Intelligent assistive robots can enhance the quality of life of people with dementia and their caregivers. They can increase the independence of older adults, reduce tensions between a person with dementia and their caregiver, and increase social engagement. This article provides a review of assistive robots designed for and evaluated by persons with dementia. Assistive robots that only increased mobility or brain-computer interfaces were excluded. Google Scholar, IEEE Digital Library, PubMed, and ACM Digital Library were searched. A final set of 53 articles covering research in 16 different countries are reviewed. Assistive robots are categorized into five different applications and evaluated for their effectiveness, as well as the robots’ social and emotional capabilities. Our findings show that robots used in the context of therapy or for increasing engagement received the most attention in the literature, whereas the robots that assist by providing health guidance or help with an activity of daily living received relatively limited attention. PARO was the most commonly used robot in dementia care studies. The effectiveness of each assistive robot and the outcome of the studies are discussed, and particularly, the social/emotional capabilities of each assistive robot are summarized. Gaps in the research literature are identified and we provide directions for future work.

Are Preferences Useful for Better Assistance?

Assistive Robots have an inherent need of adapting to the user they are assisting. This is crucial for the correct development of the task, user safety, and comfort. However, adaptation can be performed in several manners. We believe user preferences are key to this adaptation. In this article, we evaluate the use of preferences for Physically Assistive Robotics tasks in a Human-Robot Interaction user evaluation. Three assistive tasks have been implemented consisting of assisted feeding, shoe-fitting, and jacket dressing, where the robot performs each task in a different manner based on user preferences. We assess the ability of the users to determine which execution of the task used their chosen preferences (if any). The obtained results show that most of the users were able to successfully guess the cases where their preferences were used even when they had not seen the task before. We also observe that their satisfaction with the task increases when the chosen preferences are employed. Finally, we also analyze the user’s opinions regarding assistive tasks and preferences, showing promising expectations as to the benefits of adapting the robot behavior to the user through preferences.

Assistive Robots for Patients with ALS: An Exploratory Study with an Early Stage Demonstrator (Preprint)

BACKGROUND Although robotic manipulators have great potential in promoting motor independence of people with motor impairments, only few systems are currently commercially available. In addition to technical, economic and normative barriers, a key challenge for their diffusion is the current lack of evidence regarding usefulness, acceptance and user-specific requirements. OBJECTIVE Against this background, a semi-autonomous robot system was developed in the R&D project ROBINA to support people with amyotrophic lateral sclerosis (ALS) in various everyday activities. METHODS The developed early stage demonstrator was evaluated in a task-based laboratory study with eleven ALS patients. Based on a mixed-methods design consisting of standardized questionnaires, observation protocols, and semi-structured interviews, participants were asked about usability, acceptance, and design requirements. RESULTS The majority of the participants considered the system provide relevant support within the test scenarios and perceived it as easy to use. Technical requirements consisted in precise object manipulation, reliable autonomous robot actions, and an intuitive GUI. In addition, the adaptability of the system to the abilities and disease-related limitations of the users, as well as a higher degree of intervention in the control and autonomous robot actions, was highlighted. Finally, the need for a holistic concept of robotic assistance in order to adequately address user-specific needs, was emphasized. CONCLUSIONS In summary, it can be stated that robotic manipulators can contribute to the compensation of motor impairments and increase both the autonomy and the psychological well-being of those affected. In this context, further opportunities to relieve the burden on the care network can be expected, especially regarding repetitive actions. CLINICALTRIAL The study is registered in the German Clinical Trials Registry (DRKS00016554).

Designing Socially Assistive Robots for People With Alzheimer’s and Related Dementia

Alzheimer’s disease (AD) is the most common form of dementia and is associated with memory loss and cognitive impairments that affect daily life. Approximately 5.8 million older adults in the U.S. are living with AD. People with AD often require high levels of care and assistance to maintain daily activities. The majority of care provided to a person living with AD or other forms of dementia is from a family caregiver, representing 18.6 billion hours of unpaid care valued at $244 billion. The long duration, time-intensive nature of caregiving imposes high burdens on caregivers. We designed a socially assistive robot to engage in conversation with people with AD, by engaging in conversation, helping them conduct simple daily tasks, and relieving caregivers of some of their responsibilities. Using design-thinking methodology, a prototype social robot has been created using 3-d printing technology and a single board computer based on raspberry Pi. Interaction between human and robot is implemented using the Mycroft open source voice assistant. The authors demonstrated that the robot is able to have natural conversations with human users. The overall cost of the robot is estimated to be less than $300, rendering it possible for wide distribution among the public. Future research includes further implementation of various cognitive assessment and cognitive training programs using the social robot to improve the quality of life for people living with AD.

Exploring Social and Assistive Domestic Robots for Older Adults: Robot Sociability, Trust, and Acceptance

Older adults prefer to age in place, to live independently while maintaining social connection and engagement with the community. Though older adults can encounter barriers to these goals, social and assistive domestic robots hold promise for promoting independence and online/offline social engagement. However, social robots must be designed to meet their needs and preferences. Open questions remain regarding how to facilitate the development of trust and acceptance in robot support. We investigated the associations between robot social characteristics, sociability, trust, and acceptance for instrumental activities of daily living. We used an online survey to assess older adults’ perceptions towards social and assistive robots. Robots with more social abilities were rated as more acceptable and trustworthy across different task types. We discuss design implications that may promote the development of robot trust and acceptance by older adults, and ultimately help enable aging in place and social engagement.

Research on the Application of Machine Learning Algorithm and Fuzzy Logic in Eating Assistive Robot

More than 110 million people in this world are facing some kind of disability, for which they experience difficulty while eating food. Eating Assistive Robots could meet the needs of the elderly and people with upper limb disabilities or dysfunctions in gaining independence in eating. We are researching making a robot, which can assist the disabled in eating their meals. Our Eating Assistive Robot will detect the face of the disabled and process it for whether his/her mouth is opened or closed. Our robot will put a pre-prepared replaceable spoon of food in his/her mouth iteratively until the food lasts in the food container. The methodology we used for it i.e. firstly there is a live camera feed through which we are detecting human faces, after this, a library of Affectiva calculates how much mouth is open. We have set a certain threshold after which the program starts the stepper motor which brings the pre-filled spoon of food into the mouth of the disabled.

Comply with Me: Using Design Manipulations to Affect Human–Robot Interaction in a COVID-19 Officer Robot Use Case

This study examines the effect of a COVID-19 Officer Robot (COR) on passersby compliance and the effects of its minor design manipulations on human–robot interaction. A robotic application was developed to ensure participants entering a public building comply with COVID restrictions of a green pass and wearing a face mask. The participants’ attitudes toward the robot and their perception of its authoritativeness were explored with video and questionnaires data. Thematic analysis was used to define unique behaviors related to human–COR interaction. Direct and extended interactions with minor design manipulation of the COR were evaluated in a public scenario setting. The results demonstrate that even minor design manipulations may influence users’ attitudes toward officer robots. The outcomes of this research can support manufacturers in rapidly adjusting their robots to new domains and tasks and guide future designs of authoritative socially assistive robots (SARs).