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Technological advancements have led to the use of robots as prospective partners to complement understaffing and deliver effective care to patients. This article discusses relevant concepts on robots from the perspective of nursing theories and robotics in nursing and examines the distinctions between human beings and healthcare robots as partners and robot development examples and challenges. Robotics in nursing is an interdisciplinary discipline that studies methodologies, technologies, and ethics for developing robots that support and collaborate with physicians, nurses, and other healthcare workers in practice. Robotics in nursing is geared toward learning the knowledge of robots for better nursing care, and for this purpose, it is also to propose the necessary robots and develop them in collaboration with engineers. Two points were highlighted regarding the use of robots in health care practice: issues of replacing humans because of human resource understaffing and concerns about robot capabilities to engage in nursing practice grounded in caring science. This article stresses that technology and artificial intelligence are useful and practical for patients. However, further research is required that considers what robotics in nursing means and the use of robotics in nursing.
Citation: Soriano, G.P.; Yasuhara, Y.;
Ito, H.; Matsumoto, K.; Osaka, K.;
Kai, Y.; Locsin, R.; Schoenhofer, S.;
Tanioka, T. Robots and Robotics in
Nursing. Healthcare 2022,10, 1571.
Academic Editor: Chaoyang Chen
Received: 26 July 2022
Accepted: 16 August 2022
Published: 18 August 2022
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Robots and Robotics in Nursing
Gil P. Soriano 1,2 ,* , Yuko Yasuhara 3, Hirokazu Ito 3, Kazuyuki Matsumoto 4, Kyoko Osaka 5, Yoshihiro Kai 6,
Rozzano Locsin 3,7, Savina Schoenhofer 8and Tetsuya Tanioka 3
1Department of Nursing, College of Allied Health, National University, Manila 1008, Philippines
2Graduate School of Health Sciences, Tokushima University, Tokushima 770-8509, Japan
3Department of Nursing, Institute of Biomedical Sciences, Tokushima University, Tokushima 770-8509, Japan
4Graduate School of Sciences and Technology for Innovation, Tokushima University,
Tokushima 770-8506, Japan
5Department of Psychiatric Nursing, Nursing Course of Kochi Medical School, Kochi University,
Kochi 783-8505, Japan
6Department of Mechanical System Engineering, Tokai University, Hiratsuka 259-1292, Japan
7Christine E. Lynn College of Nursing, Florida Atlantic University, Boca Raton, FL 33431, USA
8Independent Researcher at Nursing As Caring, Jackson, MS 39202, USA
*Correspondence: or
Technological advancements have led to the use of robots as prospective partners to comple-
ment understaffing and deliver effective care to patients. This article discusses relevant concepts on
robots from the perspective of nursing theories and robotics in nursing and examines the distinctions
between human beings and healthcare robots as partners and robot development examples and
challenges. Robotics in nursing is an interdisciplinary discipline that studies methodologies, tech-
nologies, and ethics for developing robots that support and collaborate with physicians, nurses, and
other healthcare workers in practice. Robotics in nursing is geared toward learning the knowledge
of robots for better nursing care, and for this purpose, it is also to propose the necessary robots and
develop them in collaboration with engineers. Two points were highlighted regarding the use of
robots in health care practice: issues of replacing humans because of human resource understaffing
and concerns about robot capabilities to engage in nursing practice grounded in caring science.
This article stresses that technology and artificial intelligence are useful and practical for patients.
However, further research is required that considers what robotics in nursing means and the use of
robotics in nursing.
Keywords: artificial intelligence; robots; robotics in nursing
1. Introduction
According to the World Health Organization (WHO) [
], between 2015 and 2050, the
percentage of the global population aged 60 years old and above will nearly double, from
12% to 22%. This shows that the aging population is increasing at a rate considerably greater
than in the past. Thus, many countries face significant issues concerning the healthy living
of older persons, ensuring that health and social systems are prepared to take advantage
of this demographic shift. For this reason, some countries have developed the integration
of technologies capable of human interaction, such as robots with artificial intelligence
(AI) [
]. These technologies are particularly useful in hospital settings, in which demands
for healthcare, in general, can result in a shortage of healthcare workers [3].
When the system application involves sophisticated technologies such as robotics
in nursing, Frazier et al. [
] declared that with nurses constituting 45% of all healthcare
professionals in healthcare practice, understaffing continues to be evident as a priority
problem today. Thus, the application and deployment of complex technologies as systems
of care, such as healthcare robots, are becoming more important [
]. The use of robots
may also potentially provide enhanced patient outcomes due mainly to the usage of
Healthcare 2022,10, 1571.
Healthcare 2022,10, 1571 2 of 11
technologies in healthcare. The aging population demands competencies with technologies
as crucial to attaining, maintaining, and sustaining human health and well-being [
]. The
expected outcomes involve increased efficiency and provide supporting and supplementing
of understaffing [
]. With nursing practice grounded in caring science paving the way
towards transcending dependency with technologies [
], healthcare workers are made
increasingly aware of the anticipated outcomes of technological dependency, exacerbated
by the emergence of a pandemic [9].
Advancements in technology have led to robot development for nursing practice
as potential partners to supplement understaffing and to provide efficient health care to
persons with disabilities, older persons, or vulnerable persons [
]. Since the use of
technologies helps and assists with procedures such as surgery, these technologies have
been improved and are being used in other aspects of healthcare, from treatments to
rehabilitation care. The potential use of robots in nursing and other health care disciplines
could be for improving the accuracy and speed of the detection of illnesses to improving
end-of-life care by helping persons maintain their independence for a longer period of time.
As the development of technology progresses, anticipated expressions of complex
processes are expected. Becoming a progressively complex system is evidenced in the
management of health care practices, especially in the strategies invoked in the usage of
management systems [13].
Our insights are informed by nursing theoretical perspectives such as Boykin and
Schoenhofer’s theory of Nursing As Caring [14], Locsin’s theory of Technological Compe-
tency as an Expression of Caring in Nursing and Healthcare [
], and Tanioka’s Transactive
Relationship Theory of Nursing [16], as well as extensive research and analysis.
This article aims to discuss relevant concepts on robots and robotics in nursing and
examine the distinctions between human beings and healthcare robots as partners and
robot development examples and challenges.
2. Robots and Robotics in Nursing
2.1. What Are Robots in Nursing?
Due to the progressive increase in the aging population globally, estimated at
703 million
aged 65 years old and above, the demands for older person care have also been height-
ened [
]. For this reason, an opportunity is being realized for the design and devel-
opment of healthcare robots in nursing, fitted with artificial super intelligence (ASI) and
capable of delivering nursing interventions and menial tasks in hospital settings. To bestow
care for patients, specifically aging patients [
], with efficiency and accuracy, robots in
nursing were defined by von Gerich et al. [
] following the definition of the International
Organization for Standardization 8373 as “systems of mechanical, electrical, and control
mechanisms used by trained operators in a professional health care setting that perform
tasks in direct interaction with patients, nurses, doctors, and other health care professionals
and which can modify their behavior based on what they sense in their environment”.
Similarly, Christoforou et al. [
] have also indicated that nursing robots can “serve
as supplemental healthcare workers in hospitals, older-person care facilities, and at home.
Robots in nursing can perform logistical and laborious physical tasks, combat loneliness
and inactivity in the older population, or can be assigned to routine tasks such as measuring
patients’ vital signs”. Additionally, other hospital technologies can also be integrated with
robotic technologies, such as electronic health record systems that facilitate the recording of
a patient’s healthcare history to ensure the continuity of care [
]. This assistive robotics can
promote patient and nurse communication as care time may be enhanced by such robotic
technology [10].
Meanwhile, according to Frazier et al. [
], robots are often programmed with so-
phisticated sensors, transmitters, and receivers as essential components. Moreover, robot
computer systems are integrated with a display device, which has data sensing programs
generated through the patient’s condition. A robot functions in such a way that when it
senses (recognizes) patient physiological conditions in specific situations, the transmitter
Healthcare 2022,10, 1571 3 of 11
will communicate the data to the display device and be stored in the patient database. This
healthcare robot functions through an ASI, which has different systems and sensors and de-
livers nursing care services efficiently [
]. These efficient and accurate functionalities have
become the priority operational functions desired for developing robots in nursing [
2.2. Robotics in Nursing
The inclusion of advancements in technologies is heightened by the demands of
healthcare in a highly technological world. The preference for a reimagined landscape fully
determined by a humanizing care environment, as emphasized in Locsin’s theory in which
technology, caring, and nursing have become inseparable, coexisting as conceptual models
of humanizing care [21].
Robotics [
] is the engineering and operation of machines that can autonomously
or semi-autonomously perform physical tasks on behalf of a human. Typically, robots
perform tasks that are either highly repetitive or too dangerous for humans to conduct
safely. Mechanical robots use sensors, actuators, and data processing to interact with the
physical world. Someone who makes their living in robotics must have a strong background
in mechanical engineering, electrical engineering, and computer programming. Recently,
the field of robotics has begun to overlap with machine learning and AI.
Robotics in nursing practice continues to be a challenge to ethical deployment to
ensure safe, secure, competent, and emotive functions of healthcare robots. Pivotal to the
recognition of robots as partners in nursing is their continued proficiency, continuously de-
liberated with future policies and regulations in mind [
]. As stated by
Maalouf et al. [24]
distinct functional foci are represented by various types of healthcare robot applications in
the diversified subject of robotics in nursing. Assistive robots and socially assistive robots
were the main categories. The field of robotics in nursing is evolving fast to cope with the
need for help in caregiving, especially for the elderly and individuals with disabilities. The
future development of robotics in nursing depends on a series of improvements in theory
and applications.
In ISO 8373:2021 (en) Robotics–Vocabulary [
], Robot is defined as follows: “Robot is
a programmed actuated mechanism with a degree of autonomy to perform locomotion,
manipulation, or positioning (3.1)”. In other words, things such as devices for disease
management and symptom control of patients, and robotics houses in which the building
itself is robotized, are all included in the robots.
However, this definition will change (rather actively) according to the times, and
even if something is not strictly according to the ISO definition now, it could become a
robot in the future if many people start calling it a robot. The research field of robotics in
nursing deals with robotics to improve the quality of nursing care, beginning with the use of
technology, a major concept to enable nurses to provide beneficial care to
nursing subjects.
For nurses, incorporating robotics into nursing means working to improve the quality
of nursing care and reduce workload. For patients, the robot can be effective in maintaining
or treating their healthcare needs or improving their QOL or physical functions. Robotics
in Nursing is an interdisciplinary discipline that studies the methodology, technology,
and ethics for developing and using robots that support and collaborate with nurses
in the nursing field. Robotics in Nursing is an interdisciplinary discipline that studies
methodologies, technologies, and ethics for developing robots that support and collaborate
with physicians, nurses, and other healthcare workers in practice.
Robotics in nursing is geared toward learning the knowledge of robots for better
nursing care (including safety, functions, and effects of robots, and how to use them), and
for this purpose, it is also to propose the necessary robots and develop them in collaboration
with engineers. However, nurses are not typically educated to understand all systems and
machines using mathematics and physics as engineers do. Robotics in nursing aims to
help nurses use robotics to provide the latest and most effective care to nursing patients
by having an affinity for engineering and always working closely with engineers and
engineering researchers.
Healthcare 2022,10, 1571 4 of 11
When introducing a developed robot, it is important to create an environment for
the effective use of that robot. Specifically, it is necessary to clarify how the robot should
function as a team member with caregivers who connect the robot and patients, such as
doctors and nurses, evaluate the results of better nursing care by patients and nurses, and
provide feedback for developing new robots. This is necessary to better robot-assisted
nursing care.
Nursing researchers who play the role of advocating the rights of robot users should
not only promote development but also sometimes decide to stop or change the way the
robots are used. This includes knowledge of content related to AI technologies that control
the autonomous actions, statements, and decisions of robots to communicate with patients
and nurses.
In robotics in healthcare, it is important to think of the three-party relationship between
patients, nurses (healthcare professionals), and robots and to effectively use robots and AI
as tools and technologies in this relationship. In this context, it is important to effectively
use robots and AI as tools and technologies:
To study the knowledge of robots (including safety, functions, and effects of robots
and methods of use) for better nursing care.
To propose robots necessary for better nursing care and to develop such robots in
cooperation with engineers.
To develop an environment for effective use of robots when robots are introduced for
better nursing care.
To examine the use of robots and AI from ethical and moral viewpoints.
To model how doctors, nurses, other healthcare workers, and robots should function
as a team for better care.
To evaluate the results of better care by patients, doctors, and nurses, and to provide
feedback for developing new and improved robots.
3. Distinctions between Humans and Robots
3.1. Nursing Viewpoint
In the nursing setting, Rogers [
] stated that human beings are pandimensional
energy fields that cannot be reduced to parts or divided, in which patterns manifest to have
specific characteristics of being whole. Therefore, they are unpredictable beings from the
knowledge of the parts. Fawcett and De Santo-Madeya [
] supported this definition in
that person cannot be predicted by viewing, labeling, or summarizing them as they are
considered unitary wholes with unique features. Furthermore, attributes of persons as
caring can contribute to the possibility that robots can manifest caring [
]. Boykin and
Schoenhofer [
] have expressed that people are caring by virtue of their humanness. As
the manifestation of caring is substantiated by philosophical, theoretical, and theological
views, the manifestation may be appropriated as caring.
3.2. Behavior of Robots-Like Humans
Contemporary healthcare robots will require robotics engineering programming in or-
der to simulate caring practices, which can eventually be likened to human caring practices.
Concerns about theocratic and philosophic perspectives remain critical determinants in
assuming the possible similarities between humanoid robots and human beings’ expression
of “caring” practices, particularly reflective of caring attributes.
Robots can be programmed by humans to act as human-like as it is currently possible
to attend persons’ healthcare. While the possibility of intended acts by humanoid robots
is to engender activities much like human nurses, this possibility depends on the tech-
nological advances of the times. In collaboration with persons expressing human caring
practice, robots can or may be able to render functions that can simulate those of the human
nurse. Locsin et al. [
] explained that caring in nursing refers to the relationship that exists
between nurses and the persons being cared for. Caring encompasses empathy for and
connection with people [
]. Nonetheless, if one refers to the theological and philosophical
Healthcare 2022,10, 1571 5 of 11
concepts of the humanness of persons as primary determinants of humanness, then robots
have yet to be identified as equally the same as human beings; otherwise, humanoid robots
can simply be functional technologies—instruments that facilitate human nurses’ expres-
sions of caring. However, based on humanoid robot acceptance by humans in healthcare,
the development of humanoid robots to express human caring as an “autonomous” being
may create a heightened awareness of the issue of sentience, creating additional concerns
that may help, or not, in advancing human science and human care in a world dense
with technologies.
4. Physical Attributes and the Aspect of Expressing Humanness
4.1. Physical Aspects and Characteristics That Express Humanness
Understanding the differences between humans and robots in terms of their capability
to care can be divided into two aspects: physical aspects and the aspect of expressing
humanness. Today, the physical differences between humans and robots are obvious yet
may not be as distinctive in the future. Current advances in researching human skin-like
prostheses have become popular [
]. As stated by Liu et al. [
], tactile sensing plays a
vital role that will develop the cognition and intelligence of robots as it becomes easier for
the robots to explore their surroundings autonomously. For example, humans deprived of
reliable tactile information, such as being numb or having cold fingers, may become clumsy
and can create accidents. Robotic systems should have the feature of being able to sense
touch to safely interact in uncertain environments, such as offering care for human beings.
It is said that human nurses are considered resources for health, yet there is a crisis in
their numbers due to human aging and vulnerability to diseases as organic beings. It is
inevitable that human resources would be scarce because of limitations of life expectancy
and the physical capabilities of human beings as organic beings. Furthermore, decline
of human births with the increasing rate of the aging population and developed medical
technology and/or complex medical systems altogether bring concerning situations for
the future availability of human resources for healthcare [
]. Corollary to these concerns
of human resource allocation is the proximity of human beings to diseases and illnesses.
The American Nurses Association [
] has recognized these limitations, adding personal
risks of harming nurses. Robots and robotics in nursing settings would be able to address
the resource problems because robots are mechanical and inorganic, and therefore, robots
do not succumb to diseases and other consequences of being organic. As sophisticated
technologies as these are, robots have their inherent problems such as sensory fidelity,
the potential for being “hacked”, and mechanical deterioration, thus potential inability to
ensure safe, secure, and precise activities of healthcare practice.
The advantages of having robots in healthcare facilities have produced the idea that
they may outperform humans in some tasks, and replacing human nurses with robots could
be a welcome possibility [
]. However, issues concerning robot capabilities of expressing
human-like compassion [
] and empathy [
] are contemporary discourse topics. van
Wynsberghe [
] also stated that healthcare robots do not currently have the competencies
to express “caring in nursing” that is expected of a human nurse. Other critical topics
regarding robot sentience [37] are popular themes of discourse as well.
4.2. Argument on whether Robots Are Capable of Having a “Soul”
Topics on the capability of robots to experience feelings and sensations refer to the
argument that the current generation of humanoid and android robots already have the
look and behavior that allows the robots to be accepted by people as peers. Another
critiqued view is the acceptance as a form of deception in which robots pretend to be
sentient through their behavior [
]. However, the argument on whether robots are capable
of having a “soul”, arguing that the soul allows human beings to be able to manifest caring
and “be with” persons, will introduce various concepts relating to the human soul. That
correlates with beliefs about God and how the idea of the humans’ unique capability of
caring is endowed by a god as the human soul is said to be reflected in a god’s being [39].
Healthcare 2022,10, 1571 6 of 11
From an Islamic perspective, human beings are the best creation of God, and from
a Judeo-Christian viewpoint, a person or a human is created with God’s own image,
including his ability to be good [
]. However, human beings have no permanent existence
and are always changing, according to a Buddhist perspective. Though in Shinto, which is
a Japanese god spirit that is a good being, people become “kami” or God-like after dying.
Despite the concepts allowing for evolving explicatory discourse on Nursing, the topics
are still a delicate issue to be questioned when there is an alteration to the wholeness of a
person to attain something beyond the limitations of a human [
]. Some philosophical
and theoretical views of persons, such as the oneness and co-existence of the soul and body,
are asserted as material to the understanding of human beings as persons.
Wilson [
] confers individuality and humanity to humans, emphasizing the duality of
the mind and body. This means that it is not necessarily the soul that is the essential compo-
nent of being human. Additionally, there are popular discussions on altering the wholeness
of the person, creating a debate about whether it affects the beliefs about the human being
as a perfect image of God. Terms such as Transhumanism and Posthumanism give the idea
that the wholeness of a human can still go beyond its limits and evolve while it is still part
of its growth to perfection. Transhumanism is the concept of human evolution that will
lead to us being better humans by combining technology and biology [
]. Posthumanism
refers to the use of AI, which allows evolution in humans genetically or bionically [
Such concepts are argued to be the final stage for humans to reach transcendence as a being.
This further creates the idea of how far and complex it would take to conclude what allows
a human to care as such, just by multiple concepts and issues.
For the question of whether robots can have a soul, they do not, as the concept of a
soul focuses on the theological basis of the philosophical truth of the existence of a soul,
while having the “mind” is another neuro-physiological and biological concept [44].
4.3. Robots May Communicate in Human-Like Manner
Robots may be able to communicate with their beings in a human-like manner, mimick-
ing persons through natural language processing. Ren and Matsumoto [
] and Wagoner
and Matson [
] support this probability, as they have also explained the capabilities of the
process in their studies. Moreover, there have already been instances where robots mim-
icking animal-like behavior and communication have been achieved. Zhakypov et al. [
designed small robots that were programmed to emulate how ants worked, from their
structure within the colonies and how they work with one another through the usage
of communication. This development can eventually progress into human-like behavior.
This was similar to studies such as Nishio et al. [
], which explored the effectiveness
of prolonged conversations with older persons through twin robots, finding that it was
effective for more than half of the participants. These robots can emulate the behavior and
even social hierarchies to a certain degree. Through this, they may have the capabilities of
transcending from emulation of human-like manners to that of a simulation between two
(2) robots.
5. Robot Development Examples and Challenges
Japan has been implementing the “Japanese Robot Strategy”, a program that encom-
passes the use of communication robots for older persons who have low levels of social
participation. This strategy is pivotal in preventing dementia and delaying chronicity while
promoting positive therapeutic effects [
]. An illustration of this strategy is the use of
service robots. One popular robot used in industry, entertainment, and patient care is the
humanoid robot called Pepper. It is a service robot programmed to engage persons who
have certain conditions in therapeutic activities, such as monitoring their performance of
tasks that help improve their physical functions as well as the extent of their interactive
communication [
]. A similar robot is the Telenoid, a robot teleoperated with the intent to
communicate with older persons who are diagnosed with Alzheimer’s disease [50].
Healthcare 2022,10, 1571 7 of 11
Taking the situation during the COVID-19 pandemic as an example, several robotics
companies developed their robots to contribute to the medical field. As mentioned by
EHL (Ecole hôtelière de Lausanne) Faculty [
], companies such as UVD (Ultraviolet
Disinfection) robots, PAL Robots [
], and TIAGo (Take It And Go) had their robots used
in hospitals to perform various tasks that would otherwise place staff in danger due to
their exposure to the virus; functions such as disinfection of areas by UVD robots in Italian
hospitals, PAL’s ‘Ari’ robots to increase social stimulation, and TIAGo’s dual purpose
robots of disinfecting and delivering medicine and food to patients. What was more
interesting was the mention of Boston Dynamics’ work in developing a robot, their dog-
like robot called ‘Spot’ that could take vital signs from a distance of two (2) meters from
the patient by developing algorithms that can aid in such measurements [
]. Although
the latter example is still being worked upon, the potential of robots in aiding healthcare
professionals, especially nurses, can come to fruition once the technology becomes available
to allow these concepts/plans to be part of the field.
5.1. Experiments Exploring Robots and Their Interactions with Humans
One study by Betriana et al. [
] explored the characteristics of the interactive com-
munication between Pepper, patients with schizophrenia, and healthy persons. What
transpired were exercises performed for both human groups where similarities and differ-
ences in their experiences were identified. The study results showed that Pepper the robot
could successfully provide effective communication for both patients with mental health
conditions and those who were healthy. However, due to the nature of how Pepper was
operated (remotely), certain characteristics such as the response time during conversations,
gaze, and entertainment functions would need to be improved.
Another study by Yamazaki et al. [
] explored the use of AHOBO, a frail care robot, to
assist older adults living at home. In the study, two support systems were used, blood pres-
sure measurement for the physical aspect and reminiscent coloring as a recreational activity
for the psychological aspect. Based on the subjective evaluation, the results confirmed that
the suggested robot has no effect on blood pressure readings and is satisfactory in terms of
simplicity of use. Subjective evaluation of the reminiscent interaction was conducted on
two older adults using the verbal fluency task, and it was confirmed that the interaction can
be employed in daily life. The use of robots that currently exist in the field, such as Pepper
and AHOBO, are still being improved upon, as the technology is still in its early stages.
Therefore, the potential improvements that they can realize, especially with the addition of
AI, can greatly improve their functions and be used in the realm of nursing. The potential
of robots and AIs in the field of nursing and medicine can be endless, especially with the
technological advancements that have been made in the past century that have opened up
to devices such as self-driving cars, facial recognition, and many more.
5.2. Robots with Natural Language Expression by AI
The viewpoints on robots and AI are discussed to enable nurses to work more effec-
tively and securely while providing patient care [
], but in doing so, robots with AI must
first discover nursing situations occurring based on data previously stored in an envisioned
“Nursing Situation Database”. The appropriate nursing response must be recognized from
the “Nursing Response Database”. For example, if a patient has a hallucination, the AI will
find a nursing response for that patient from the database, and the nursing robot will re-
spond appropriately (appropriate actions and natural language expressions). However, not
all nursing situations are stored in the database. Therefore, it is necessary to collect big data
on nursing situations and nursing responses that the nursing robots have actually faced.
A mechanism is needed for the “nursing situation database and its response database” to
self-learn and evolve. This, in turn, would require nurses to be trained to work alongside
the technology to provide the best treatment and experience for the patients.
Most studies involving robots and AIs would concern themselves with assistive
functions in general, though there have also been studies that explore the potential
Healthcare 2022,10, 1571 8 of 11
nursing robots (as well as other robots) could have in the near future. According to
Christoforou et al.
], the functions of nursing robots can serve as supplemental health-
care workers, whether at home or in hospitals, as they can be assigned to perform the
logistical and laborious aspects of nursing, whereas remote-controlled telerobots can take
over the interactive caretaker duties. It should be taken note that even in this study, the
functions of nursing robots are limited to that of their human counterpart’s guidance when
it comes to interactions with patients. These robots can be further used when there are cases
where interacting with patients could be dangerous for the staff, such as outbreaks. For
instance, Yamazaki et al. [
] studied the use of Telenoid (teleoperated robots) in a residen-
tial care facility to examine how the older adults with dementia reacted to it. The findings
revealed that an affectionate bond may grow between the older adults and the android,
allowing the operator to communicate easily with older individuals and elicit answers.
With the advancement of AI technology, natural language interaction with patients
can become a reality. However, because natural language dialogue requires advanced
processing, many issues exist that need to be resolved. For example, there is the problem
of omission. When people interact with robots using natural language, they sometimes
omit important words that impact the comprehension of the sentence, such as subjects and
objects. Matching analysis technology is indispensable. Ambiguous expressions without
antecedents due to poor memory or poor judgment are also a problem in understanding
meaning and intention.
Approaches to deepening understanding by having a robot repeatedly ask questions
in response to unintended utterances [
] and methods to perform moral reasoning to
resolve the ambiguity without asking questions [
] have also been studied. However, it
is difficult for robots to make judgments that humans can make from context. Alterna-
tively, an accurate understanding of intentions may not necessarily be necessary when
miscommunication in dialog does not have serious consequences.
It is not difficult to imagine that an AI-powered robot that understands human emo-
tions and can engage in chit-chat would not only reduce the burden of caregiving and
nursing but would also be friendly and have a positive impact on patient health. In care-
giving and nursing chats with patients, emotional understanding is more important than
an accurate understanding of the intent of the speech. It is also possible to understand the
health status of the patient through chatting [60].
6. Conclusions
Technology and AI are useful and practical for patients. Robotics in nursing is an
interdisciplinary discipline that studies methodologies, technologies, and ethics for devel-
oping robots that support and collaborate with physicians, nurses, and other healthcare
workers in practice. Robotics in nursing is geared toward learning the knowledge of robots
for better nursing care, and for this purpose, it is also to propose the necessary robots and
develop them in collaboration with engineers. However, further research is required that
considers what robotics in nursing means and the use of robotics in nursing. There is still a
lack of study on whether they are capable of replacing humans due to human nurses’ ability
to manifest caring relates to their humanness or their unpredictable nature. One of the
most important, in our opinion, would be to work on the Nursing Situation and Response
Databases. The empathic capacities that robotics and AI can demonstrate for humans can
exist through programmed activities. The knowledge generated will bring information
to engage in relationships between empathy and AI and contribute to understanding its
usefulness and impacting nursing/caring theories.
Author Contributions:
Conceptualization, T.T.; developed the initial idea and put together the
first draft, G.P.S. and T.T.; writing—review and editing, G.P.S., Y.Y., H.I., K.M., K.O., Y.K., R.L., S.S.
and T.T.; project administration, T.T. All authors have read and agreed to the published version of
the manuscript.
Funding: This study was supported by JSPS KAKENHI Grant Number JP17H01609.
Healthcare 2022,10, 1571 9 of 11
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement:
The data presented in this study are available on request from the
corresponding author. The data are not publicly available due to privacy and ethical restrictions.
Conflicts of Interest:
The authors declare that the research was conducted in the absence of any
commercial or financial relationships that could be construed as a potential conflict of interest.
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... My article (Locsin et al. 2018) on If Humanoid Robots Replace Human Nurses is a frequently read article. Actually, I have been involved in writing several articles about robots and nurses (Betriana et al., 2022;Locsin & Schoenhofer, 2019;Macalm & Locsin, 2020;Soriano et al., 2022). Hopefully people are reading these articles carefully and meaningfully because it can be misconstrued. ...
There are many nursing scholars who have contributed to nursing knowledge. Dr. Rozzano Locsin is one of those scholars. His many contributions to nursing knowledge include his middle-range theory technological competency as caring in nursing. In this scholarly dialogue Dr. Locsin talks about nursing and his contributions to its knowledge development.
Purpose: To analyze the AI research in the field of nursing, to explore the current situation, hot topics, and prospects of AI research in the field of nursing, and to provide a reference for researchers to carry out related studies. Methods: We used the VOSviewer 1.6.17, SciMAT, and CiteSpace 5.8.R3 to generate visual cooperation network maps for the country, organizations, authors, citations, and keywords and perform burst detection, theme evolution, and so forth. Findings: A total of 9318 articles were obtained from the Web of Science Core Collection database. Four hundred and thirty-one AI research related to the field of nursing was published by 855 institutions from 54 countries. CIN-Computers Informatics Nursing was the top productive journal. The United States was the dominant country. The transnational cooperation between authors from developed countries was closer than that between authors from developing countries. The main hot topics included nurse rostering, nursing diagnosis, nursing decision support, disease risk factor prediction, nursing big data management, expert system, support vector machine, decision tree, deep learning, natural language processing, and nursing education. Machine learning represented one of the cutting-edge and most applicable branches of artificial intelligence in the field of nursing, and deep learning was the hottest technology among many machine learning methods in recent years. One of the most cited papers was published by Burke in 2004 and cited 500 times, which critically evaluated AI methods to deal with nurse scheduling problems. Conclusions: Although AI has been paid more and more attention to the field of nursing, there is still a lack of high-yielding authors who have been engaged in this field for a long time. Most of the high contribution authors and institutions came from developed countries; therefore, more transnational and multi-disciplinary cooperation is needed to promote the development of AI in the nursing field. This bibliometric analysis not only provided a comprehensive overview to help researchers to understand the important articles, journals, potential collaborators, and institutions in this field but also analyzed the history, hot spots, and future trends of the research topic to provide inspiration for researchers to choose research directions.
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We examine the implementation of social robots in real-world settings during the COVID-19 pandemic. In particular, we analyze the areas in which social robots are being adopted, the roles and tasks being fulfilled, and the robot models being implemented. For this, we traced back and analyzed 240 deployment cases with 86 different social robots worldwide that have been adopted since the coronavirus outbreak. We found that social robot adoption during this period was strongly related to the use of this technology for crisis management. The social robots’ capacity to perform the roles of liaison to minimize direct contact among humans, safeguard to ensure contagion risk-free environments, and well-being coach to protect mental and physical health, is key to explaining adoption within this context. The results of the study offer a complete overview of social robots' utilization in real life settings during the pandemic.
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Background: Expressing enjoyment when conversing with healthcare robots is an opportunity to enhance the value of human robots with interactive capabilities. In clinical practice, it is common to find verbal dysfunctions in patients with schizophrenia. Thus, interactive communication characteristics may vary between Pepper robot, persons with schizophrenia, and healthy persons. Objective: Two case studies aimed to describe the characteristics of interactive communications, 1) between Pepper as a healthcare robot and two patients with schizophrenia, and 2) between Pepper as a healthcare robot and two healthy persons. Case report: The "Intentional Observational Clinical Research Design" was used to collect data. Using audio-video technology, the conversational interactions between the four participants with the Pepper healthcare robot were recorded. Their interactions were observed, with significant events noted. After their interactions, the four participants were interviewed regarding their experience and impressions of interacting with the Pepper healthcare robot. Audio-video recordings were analyzed following the analysis and interpretation protocol, and the interview data were transcribed, analyzed, and interpreted. Discussion: There were similarities and differences in the interactive communication characteristics between the Pepper robot and the two participants with schizophrenia and between Pepper and the two healthy participants. The similarities were experiences of human enjoyment while interacting with the Pepper robot. This enjoyment was enhanced with the expectancy of the Pepper robot as able to entertain, and possessing interactive capabilities, indicating two-way conversational abilities. However, different communicating characteristics were found between the healthy participants' impressions of the Pepper robot and the participants with schizophrenia. Healthy participants understood Pepper to be an automaton, with responses to questions often constrained and, on many occasions, displaying inaccurate gaze. Conclusion: Pepper robot showed capabilities for effective communication pertaining to expressing enjoyment. The accuracy and appropriateness of gaze remained a critical characteristic regardless of the situation or occasion with interactions between persons with schizophrenia, and between healthy persons. It is important to consider that in the future, for effective use of healthcare robots with multiple users, improvements in the areas of the appropriateness of gaze, response time during the conversation, and entertaining functions are critically observed.
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The design of current natural language oriented robot architectures enables certain architectural components to circumvent moral reasoning capabilities. One example of this is reflexive generation of clarification requests as soon as referential ambiguity is detected in a human utterance. As shown in previous research, this can lead robots to (1) miscommunicate their moral dispositions and (2) weaken human perception or application of moral norms within their current context. We present a solution to these problems by performing moral reasoning on each potential disambiguation of an ambiguous human utterance and responding accordingly, rather than immediately and naively requesting clarification. We implement our solution in the DIARC robot architecture, which, to our knowledge, is the only current robot architecture with both moral reasoning and clarification request generation capabilities. We then evaluate our method with a human subjects experiment, the results of which indicate that our approach successfully ameliorates the two identified concerns.
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To achieve continuous frail care in the daily lives of the elderly, we propose AHOBO, a frail care robot for the elderly at home. Two types of support systems by AHOBO were implemented to support the elderly in both physical health and psychological aspects. For physical health frailty care, we focused on blood pressure and developed a support system for blood pressure measurement with AHOBO. For psychological frailty care, we implemented reminiscent coloring with the AHOBO as a recreational activity with the robot. The usability of the system was evaluated based on the assumption of continuous use in daily life. For the support system in blood pressure measurement, we performed a qualitative evaluation using a questionnaire for 16 subjects, including elderly people under blood pressure measurement by the system. The results confirmed that the proposed robot does not affect the blood pressure readings and is acceptable in terms of ease of use based on subjective evaluation. For the reminiscent coloring interaction, subjective evaluation was conducted on two elderly people under the verbal fluency task, and it has been confirmed that the interaction can be used continuously in daily life. The widespread use of the proposed robot as an interface for AI that supports daily life will lead to a society in which AI robots support people from the cradle to the grave.
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The number of isolated elderly people with few opportunities to talk to other people is currently increasing. Research is ongoing to develop talking robots for addressing the situation. The aim of the present study was to develop a talking robot that could converse with elderly people over an extended period. To enable long-duration conversation, we added a previously proposed active listening function for twining the robot dialogue system to prompt the user to say something. To verify the effectiveness of this function, a comparative experiment was performed using the proposed robot system and a control system with identical functions except the active listening function. The results showed that the conversation of the elderly subjects with the proposed robot system was significantly more than that with the control system. The capability of the developed robot system was further demonstrated in a nursing home for the elderly, where its conversation durations with different residents were measured. The results revealed that the robot could converse for more than 30 min with more than half of the elderly subjects. These results indicate that the additional function of the proposed talking robot system would enable elderly people to talk over longer periods of time.
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Although progress is being made in affective computing, issues remain in enabling the effective expression of compassionate communication by healthcare robots. Identifying, describing and reconciling these concerns are important in order to provide quality contemporary healthcare for older adults with dementia. The purpose of this case study was to explore the development issues of healthcare robots in expressing compassionate communication for older adults with dementia. An exploratory descriptive case study was conducted with the Pepper robot and older adults with dementia using high-tech digital cameras to document significant communication proceedings that occurred during the activities. Data were collected in December 2020. The application program for an intentional conversation using Pepper was jointly developed by Tanioka's team and the Xing Company, allowing Pepper's words and head movements to be remotely controlled. The analysis of the results revealed four development issues, namely, (1) accurate sensing behavior for "listening" to voices appropriately and accurately interacting with subjects; (2) inefficiency in "listening" and "gaze" activities; (3) fidelity of behavioral responses; and (4) deficiency in natural language processing AI development, i.e., the ability to respond actively to situations that were not pre-programmed by the developer. Conversational engagements between the Pepper robot and patients with dementia illustrated a practical usage of technologies with artificial intelligence and natural language processing. The development issues found in this study require reconciliation in order to enhance the potential for healthcare robot engagement in compassionate communication in the care of older adults with dementia.
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Robots in healthcare are being developed rapidly, as they offer wide-ranging medical applications and care solutions. However, it is quite challenging to develop high-quality, patient-centered, communication-efficient robots. This can be attributed to a multitude of barriers such as technology maturity, diverse healthcare practices, and humanizing innovations. In order to engineer an ideal Humanoid-Nurse Robots (HNRs), a profound integration of artificial intelligence (AI) and information system like nursing assessment databases for a better nursing care delivery model is required. As a specialized nursing database in psychiatric hospitals, the Psychiatric Nursing Assessment Classification System and Care Planning System (PsyNACS©) has been developed by Ito et al., to augment quality and safe nursing care delivery of psychiatric health services. This chapter describes the nursing landscape in Japan, PsyNACS© as a specialized nursing database, the HNRs of the future, and the future artificial brain for HNRs linking PsyNACS© with AI through deep learning and Natural Language Processing (NLP).
Flesh encodes a variety of haptic information including deformation, temperature, vibration, and damage stimuli using a multisensory array of mechanoreceptors distributed on the surface of the human body. Currently, soft sensors are capable of detecting some haptic stimuli, but whole-body multimodal perception at scales similar to a human adult (surface area ~17,000 square centimeters) is still a challenge in artificially intelligent agents due to the lack of encoding. This encoding is needed to reduce the wiring required to send the vast amount of information transmitted to the processor. We created a robotic flesh that could be further developed for use in these agents. This engineered flesh is an optical, elastomeric matrix "innervated" with stretchable lightguides that encodes haptic stimuli into light: temperature into wavelength due to thermochromic dyes and forces into intensity due to mechanical deformation. By exploiting the optical properties of the constitutive materials and using machine learning, we infer spatiotemporal, haptic information from light that is read by an image sensor. We demonstrate the capabilities of our system in various assemblies to estimate temperature, contact location, normal and shear force, gestures, and damage from temporal snapshots of light coming from the entire haptic sensor with errors <5%.
Touch is a complex sensing modality owing to large number of receptors (mechano, thermal, pain) nonuniformly embedded in the soft skin all over the body. These receptors can gather and encode the large tactile data, allowing us to feel and perceive the real world. This efficient somatosensation far outperforms the touch-sensing capability of most of the state-of-the-art robots today and suggests the need for neural-like hardware for electronic skin (e-skin). This could be attained through either innovative schemes for developing distributed electronics or repurposing the neuromorphic circuits developed for other sensory modalities such as vision and audio. This Review highlights the hardware implementations of various computational building blocks for e-skin and the ways they can be integrated to potentially realize human skin-like or peripheral nervous system-like functionalities. The neural-like sensing and data processing are discussed along with various algorithms and hardware architectures. The integration of ultrathin neuromorphic chips for local computation and the printed electronics on soft substrate used for the development of e-skin over large areas are expected to advance robotic interaction as well as open new avenues for research in medical instrumentation, wearables, electronics, and neuroprosthetics.
Background Research on technologies based on artificial intelligence in healthcare has increased during the last decade, with applications showing great potential in assisting and improving care. However, introducing these technologies into nursing can raise concerns related to data bias in the context of training algorithms and potential implications for certain populations. Little evidence exists in the extant literature regarding the efficacious application of many artificial intelligence -based health technologies used in healthcare. Objectives To synthesize currently available state-of the-art research in artificial intelligence -based technologies applied in nursing practice. Design Scoping review Methods PubMed, CINAHL, Web of Science and IEEE Xplore were searched for relevant articles with queries that combine names and terms related to nursing, artificial intelligence and machine learning methods. Included studies focused on developing or validating artificial intelligence -based technologies with a clear description of their impacts on nursing. We excluded non-experimental studies and research targeted at robotics, nursing management and technologies used in nursing research and education. Results A total of 7610 articles published between January 2010 and March 2021 were revealed, with 93 articles included in this review. Most studies explored the technology development (n=55, 59.1%) and formation (testing) (n=28, 30.1%) phases, followed by implementation (n=9, 9.7%) and operational (n=1, 1.1%) phases. The vast majority (73.1%) of studies provided evidence with a descriptive design (level VI) while only a small portion (4.3 %) were randomised controlled trials (level II). The study aims, settings and methods were poorly described in the articles, and discussion of ethical considerations were lacking in 36.6% of studies. Additionally, one-third of papers (33.3%) were reported without the involvement of nurses. Conclusions Contemporary research on applications of artificial intelligence -based technologies in nursing mainly cover the earlier stages of technology development, leaving scarce evidence of the impact of these technologies and implementation aspects into practice. The content of research reported is varied. Therefore, guidelines on research reporting and implementing artificial intelligence -based technologies in nursing are needed. Furthermore, integrating basic knowledge of artificial intelligence -related technologies and their applications in nursing education is imperative, and interventions to increase the inclusion of nurses throughout the technology research and development process is needed.