An Intelligent Socially Assistive Robot for Health Care

Health Care Applications

As the first round of baby boomers turn 65 in 2011, we must be prepared for the largest demographic group in history that could need long term care from nursing homes and home health providers. The development of socially assistive robots for health care applications can provide measurable improvements in patient safety, quality of care, and operational efficiencies by playing an increasingly important role in patient care in the fast pace of crowded clinics, hospitals and nursing/veterans homes. However, there are a number of research issues that need to be addressed in order to design such robots. In this paper, we address one of the main limitations to the development of intelligent socially assistive robots for health care applications: Robotic control architecture design and implementation with explicit social and assistive task functionalities. In particular, we present the design of a unique learning-based multi-layer decision making control architecture for utilization in determining the appropriate behavior of the robot. Herein, we explore and compare two different learning-based techniques that can be utilized as the main decision-making module of the controller. Preliminary experiments presented show the potential of the integration of the aforementioned techniques into the overall design of such robots intended for assistive scenarios.

Volume 3: ASME/IEEE 2009 International Conference on Mechatronic and Embedded Systems and Applications; 20th Reliability, Stress Analysis, and Failure Prevention Conference ◽

Human Affective State Recognition and Classification During Human-Robot Interaction Scenarios

10.1115/detc2009-87647 ◽

2009 ◽

Cited By ~ 3

Author(s):

Zhe Zhang ◽

Goldie Nejat

Keyword(s):

Affective State ◽

Human Robot Interaction ◽

Affective States ◽

Robot Interaction ◽

Research Issues ◽

Assistive Robots ◽

Main Challenge ◽

Fast Pace ◽

Health Care Applications

A new novel breed of robots known as socially assistive robots is emerging. These robots are capable of providing assistance to individuals through social and cognitive interaction. The development of socially assistive robots for health care applications can provide measurable improvements in patient safety, quality of care, and operational efficiencies by playing an increasingly important role in patient care in the fast pace of crowded clinics, hospitals and nursing/veterans homes. However, there are a number of research issues that need to be addressed in order to design such robots. In this paper, we address one main challenge in the development of intelligent socially assistive robots: The robot’s ability to identify, understand and react to human intent and human affective states during assistive interaction. In particular, we present a unique non-contact and non-restricting sensory-based approach for identification and categorization of human body language in determining the affective state of a person during natural real-time human-robot interaction. This classification allows the robot to effectively determine its taskdriven behavior during assistive interaction. Preliminary experiments show the potential of integrating the proposed gesture recognition and classification technique into intelligent socially assistive robotic systems for autonomous interactions with people.

DESIGNING INTELLIGENT SOCIALLY ASSISTIVE ROBOTS AS EFFECTIVE TOOLS IN COGNITIVE INTERVENTIONS

International Journal of Humanoid Robotics ◽

10.1142/s0219843611002423 ◽

2011 ◽

Vol 08 (01) ◽

pp. 103-126 ◽

Cited By ~ 9

Author(s):

JEANIE CHAN ◽

GOLDIE NEJAT ◽

JINGCONG CHEN

Keyword(s):

Cognitive Stimulation ◽

Human Robot Interaction ◽

Control Architecture ◽

Cognitive Interventions ◽

Training Interventions ◽

Assistive Robots ◽

Assistive Robot ◽

Term Basis ◽

Recently, there has been a growing body of research that supports the effectiveness of using non-pharmacological cognitive and social training interventions to reduce the decline of or improve brain functioning in individuals suffering from cognitive impairments. However, implementing and sustaining such interventions on a long-term basis is difficult as they require considerable resources and people, and can be very time-consuming for healthcare staff. Our research focuses on making these interventions more accessible to healthcare professionals through the aid of robotic assistants. The objective of our work is to develop an intelligent socially assistive robot with abilities to recognize and identify human affective intent to determine its own appropriate emotion-based behavior while engaging in assistive interactions with people. In this paper, we present the design of a novel human-robot interaction (HRI) control architecture that allows the robot to provide social and cognitive stimulation in person-centered cognitive interventions. Namely, the novel control architecture is designed to allow a robot to act as a social motivator by encouraging, congratulating and assisting a person during the course of a cognitively stimulating activity. Preliminary experiments validate the effectiveness of the control architecture in providing assistive interactions during a HRI-based person-directed activity.

Towards a communication model for a sociable companion robot

10.32920/ryerson.14668440.v1 ◽

2021 ◽

Author(s):

Lauren Dwyer

Keyword(s):

Human Robot Interaction ◽

Communication Model ◽

Robot Interaction ◽

The Public ◽

Assistive Robots ◽

Technical Requirements ◽

Long Term Study ◽

Robot Evaluation ◽

Anxiety has a lifetime prevalence of 31% of Canadians (Katzman et al. 2014). In Canada, psychological services are only covered by provincial health insurance if the psychologist is employed in the public sector; this means long wait times in the public system or expensive private coverage (Canadian Psychological Association). Currently, social robots and Socially Assistive Robots (SAR) are used in the treatment of elderly individuals in nursing homes, as well as children with autism (Feil-Seifer & Matarić, 2011; Tapus et al., 2012). The following MRP is the first step in a long-term project that will contend with the issues faced by individuals with anxiety using a combined communications, social robotics, and mental health approach to develop an anxiety specific socially assistive robot companion. The focus of this MRP is the development of a communication model that includes three core aspects of a social robot companion: Human-Robot Interaction (HRI), anxiety disorders, and technical design. The model I am developing will consist of a series of suggestions for the robot that could be implemented in a long-term study. The model will include suggestions towards the design, communication means, and technical requirements, as well as a model for evaluating the robot from a Human-Robot- Interaction perspective. This will be done through an evaluation of three robots, Sphero’s BB-8 App Enabled Droid, Aldebaran’s Nao, and the Spin Master Zoomer robot. Evaluation measures include modified versions of Shneiderman’s (1992) evaluation of human-factors goals, Feil-Seifer et al.’s (2007) SAR evaluative questions, prompts for the description of both the communication methods and the physical characteristics, and a record of the emotional response of the user when interacting with the robot.

Towards a communication model for a sociable companion robot

10.32920/ryerson.14668440 ◽

2021 ◽

Author(s):

Lauren Dwyer

Keyword(s):

Human Robot Interaction ◽

Communication Model ◽

Robot Interaction ◽

The Public ◽

Assistive Robots ◽

Technical Requirements ◽

Long Term Study ◽

Robot Evaluation ◽

Anxiety has a lifetime prevalence of 31% of Canadians (Katzman et al. 2014). In Canada, psychological services are only covered by provincial health insurance if the psychologist is employed in the public sector; this means long wait times in the public system or expensive private coverage (Canadian Psychological Association). Currently, social robots and Socially Assistive Robots (SAR) are used in the treatment of elderly individuals in nursing homes, as well as children with autism (Feil-Seifer & Matarić, 2011; Tapus et al., 2012). The following MRP is the first step in a long-term project that will contend with the issues faced by individuals with anxiety using a combined communications, social robotics, and mental health approach to develop an anxiety specific socially assistive robot companion. The focus of this MRP is the development of a communication model that includes three core aspects of a social robot companion: Human-Robot Interaction (HRI), anxiety disorders, and technical design. The model I am developing will consist of a series of suggestions for the robot that could be implemented in a long-term study. The model will include suggestions towards the design, communication means, and technical requirements, as well as a model for evaluating the robot from a Human-Robot- Interaction perspective. This will be done through an evaluation of three robots, Sphero’s BB-8 App Enabled Droid, Aldebaran’s Nao, and the Spin Master Zoomer robot. Evaluation measures include modified versions of Shneiderman’s (1992) evaluation of human-factors goals, Feil-Seifer et al.’s (2007) SAR evaluative questions, prompts for the description of both the communication methods and the physical characteristics, and a record of the emotional response of the user when interacting with the robot.

A pilot Project Exploring the Utility and Acceptability of a Socially-assistive Robot in an Assessment Unit for People with Neuropsychiatric Symptoms

European Psychiatry ◽

10.1016/j.eurpsy.2017.01.321 ◽

2017 ◽

Vol 41 (S1) ◽

pp. S104-S104

Author(s):

S. Loi ◽

R. Khosla ◽

K. Nguyen ◽

N. Lautenschlager ◽

D. Velakoulis

Keyword(s):

Neuropsychiatric Symptoms ◽

Well Being ◽

Pilot Project ◽

Future Directions ◽

Assistive Robots ◽

Assistive Robot ◽

Potential Benefits ◽

Competing Interest ◽

ObjectivesSocially-assistive robots have been used with older adults with cognitive impairment in residential care, and found to improve mood and well-being. However, there is little known about the potential benefits in adults with other neuropsychiatric symptoms.AimsThe aim of this project was explore the utility and acceptability of a socially-assistive robot in engaging adults with a variety of neuropsychiatric symptoms.MethodsBetty, a socially-assistive robot was installed in a unit which specialises in the assessment and diagnosis of adults presenting with neuropsychiatric symptoms. She is 39 cm tall, has a baby-face appearance and has the ability to engage individuals through personalised services which can be programmed according to individuals’ preferences. These include singing songs and playing games. Training for the nursing staff who were responsible for incorporating Betty into the unit activities was provided. The frequency, duration and type of activity which Betty was involved in was recorded. Patients admitted who could provide informed consent were able to be included in the project. These participants completed pre- and post-questionnaires.ResultsEight patients (mean age 54.4 years, SD 13.6) who had diagnoses ranging from depression and schizophrenia participated. Types of activities included singing songs, playing Bingo and reading the news. Participants reported that they were comfortable with Betty and did not feel concerned in her presence. They enjoyed interacting with her.ConclusionsThis pilot project demonstrated that participants found Betty to be acceptable and she was useful in engaging them in activities. Future directions would involve larger sample sizes and different settings.Disclosure of interestThe authors have not supplied their declaration of competing interest.

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

Multimodal Technologies and Interaction ◽

10.3390/mti5110071 ◽

2021 ◽

Vol 5 (11) ◽

pp. 71

Author(s):

Ela Liberman-Pincu ◽

Amit David ◽

Vardit Sarne-Fleischmann ◽

Yael Edan ◽

Tal Oron-Gilad

Keyword(s):

Thematic Analysis ◽

Face Mask ◽

Human Robot Interaction ◽

Use Case ◽

Robot Interaction ◽

Public Building ◽

Assistive Robots ◽

Robotic Application

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).

Effects of Assistive Robot Behavior on Impressions of Patient Psychological Attributes: Vignette-Based Human-Robot Interaction Study

Journal of Medical Internet Research ◽

10.2196/13729 ◽

2019 ◽

Vol 21 (6) ◽

pp. e13729 ◽

Cited By ~ 3

Author(s):

Meia Chita-Tegmark ◽

Janet M Ackerman ◽

Matthias Scheutz

Keyword(s):

Health Care ◽

Health Care Providers ◽

Health Management ◽

Human Robot Interaction ◽

Care Providers ◽

Patient Centered ◽

Human Relationships ◽

Assistive Robots ◽

Assistive Robot ◽

Health Care Context

Background As robots are increasingly designed for health management applications, it is critical to not only consider the effects robots will have on patients but also consider a patient’s wider social network, including the patient’s caregivers and health care providers, among others. Objective In this paper we investigated how people evaluate robots that provide care and how they form impressions of the patient the robot cares for, based on how the robot represents the patient. Methods We have used a vignette-based study, showing participants hypothetical scenarios describing behaviors of assistive robots (patient-centered or task-centered) and measured their influence on people’s evaluations of the robot itself (emotional intelligence [EI], trustworthiness, and acceptability) as well as people’s perceptions of the patient for whom the robot provides care. Results We found that for scenarios describing a robot that acts in a patient-centered manner, the robot will not only be perceived as having higher EI (P=.003) but will also cause people to form more positive impressions of the patient that the robot cares for (P<.001). We replicated and expanded these results to other domains such as dieting, learning, and job training. Conclusions These results imply that robots could be used to enhance human-human relationships in the health care context and beyond.

The Role of Socially Assistive Robots in the Care of Older People: To Assist in Cognitive Training, to Remind or to Accompany?

Sustainability ◽

10.3390/su131810394 ◽

2021 ◽

Vol 13 (18) ◽

pp. 10394

Author(s):

Sylwia Łukasik ◽

Sławomir Tobis ◽

Julia Suwalska ◽

Dorota Łojko ◽

Maria Napierała ◽

...

Keyword(s):

Older People ◽

New Technologies ◽

Rapid Development ◽

Age Groups ◽

Traditional Role ◽

Social Interventions ◽

Assistive Robots ◽

The rapid development of new technologies has caused interest in the use of socially assistive robots in the care of older people. These devices can be used not only to monitor states of health and assist in everyday activities but also to counteract the deterioration of cognitive functioning. The aim of the study was to investigate the attitudes and preferences of Polish respondents towards interventions aimed at the preservation/improvement of cognitive functions delivered by a socially assistive robot. A total of 166 individuals entered the study. Respondents completed the User’s Needs, Requirements and Attitudes Questionnaire; items connected to cognitive and physical activity and social interventions were analyzed. Perceptions and attitudes were compared by gender and age groups (older adults ≥ 60 years old and younger adults 20–59). Women showed a more positive attitude towards robots than men and had a significantly higher perception of the role of the robots in reminding about medications (p = 0.033) as well as meal times and drinks (p = 0.018). There were no significant differences between age groups. Respondents highly valued both the traditional role of the robot—a reminding function—as well as the cognitive interventions and guided physical exercises provided by it. Our findings point to the acceptance of the use of socially assistive robots in the prevention of cognitive deterioration in older people.

Volume 3: 2011 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications, Parts A and B ◽

A Socially Assistive Robot That Can Interpret Body Language

10.1115/detc2011-48031 ◽

2011 ◽

Cited By ~ 2

Author(s):

Derek McColl ◽

Goldie Nejat

Keyword(s):

Cognitive Disorder ◽

Body Language ◽

Upper Body ◽

Language Recognition ◽

Research Issues ◽

Assistive Robots ◽

Main Challenge ◽

Physical Abilities ◽

Cognitive Therapies

Socially assistive robots can engage in assistive human-robot interactions (HRI) by providing rehabilitation of cognitive, social, and physical abilities after a stroke, accident or diagnosis of a social, developmental or cognitive disorder. However, there are a number of research issues that need to be addressed in order to design such robots. In this paper, we address one main challenge in the development of intelligent socially assistive robots: A robot’s ability to identify human non-verbal communication during assistive interactions. In this paper, we present a unique non-contact automated sensory-based approach for identification and categorization of human upper body language in determining how accessible a person is to a robot during natural real-time HRI. This classification will allow a robot to effectively determine its own reactive task-driven behavior during assistive interactions. The types of interactions envisioned include providing reminders, health monitoring, and social and cognitive therapies. Preliminary experiments show the potential of integrating the proposed body language recognition and classification technique into socially assistive robotic systems partaking in HRI scenarios.