Healthcare Robots Research Articles

Use of humor by a healthcare robot positively affects user perceptions and behavior.

As we approach a time in which social robots will be used in home and healthcare settings, there is a critical need to research robot behaviors that can increase user acceptance and comfort. The use of humor by physicians during patient interactions is associated with a number of positive patient health outcomes. However, no research to date has examined the effect of humor on user outcomes when used by a healthcare robot. This study examined the use of humor by a healthcare robot in a scripted interaction in a simulated medical setting. An experiment was conducted with 91 healthy participants (73 female, mean age 25 years). Participants were randomly allocated to interact with either a humorous or neutral robot in a flu vaccination scenario. Perceptions of the robot were assessed using the Godspeed questionnaire, an empathy questionnaire, and Asch personality scale, at two time points (before and after the interaction). Participant laughing was observed during the interaction. Repeated measures between group ANOVA showed that robot use of humor resulted in significantly greater perceptions of the robot’s likeability and safety. The humorous robot was also rated as having significantly more empathy, and a more sociable personality. Participants in the humorous condition were also more likely to rate the robot’s personality as happy, talkative, and frivolous, compared to participants in the neutral condition. Significantly more participants laughed during the interaction with the humorous robot, than with the neutral robot. Together, these findings suggest that the use of humor by a healthcare robot may increase positive user evaluations. This research has implications for both theory and clinical applications.

Supplemental Material for Use of humor by a healthcare robot positively affects user perceptions and behavior.

As we approach a time in which social robots will be used in home and healthcare settings, there is a critical need to research robot behaviors that can increase user acceptance and comfort. The use of humor by physicians during patient interactions is associated with a number of positive patient health outcomes. However, no research to date has examined the effect of humor on user outcomes when used by a healthcare robot. This study examined the use of humor by a healthcare robot in a scripted interaction in a simulated medical setting. An experiment was conducted with 91 healthy participants (73 female, mean age 25 years). Participants were randomly allocated to interact with either a humorous or neutral robot in a flu vaccination scenario. Perceptions of the robot were assessed using the Godspeed questionnaire, an empathy questionnaire, and Asch personality scale, at two time points (before and after the interaction). Participant laughing was observed during the interaction. Repeated measures between group ANOVA showed that robot use of humor resulted in significantly greater perceptions of the robot’s likeability and safety. The humorous robot was also rated as having significantly more empathy, and a more sociable personality. Participants in the humorous condition were also more likely to rate the robot’s personality as happy, talkative, and frivolous, compared to participants in the neutral condition. Significantly more participants laughed during the interaction with the humorous robot, than with the neutral robot. Together, these findings suggest that the use of humor by a healthcare robot may increase positive user evaluations. This research has implications for both theory and clinical applications.

Improving Interactions with Healthcare Robots: A Review of Communication Behaviours in Social and Healthcare Contexts

A growing shortfall exists between the number of older individuals who require healthcare support and the number of qualified healthcare professionals who can provide this. Robots offer the potential to provide healthcare support to patients both at home and in healthcare settings. However, in order for robots to be successfully implemented in these environments, they need to behave in ways that are appropriate and acceptable to human users. One way to identify appropriate social behaviours for healthcare robots is to model their behaviour on interactions between healthcare professionals and patients. This literature review aimed to inform healthcare robotics research by highlighting communication behaviours that are important within the context of healthcare. The review focussed on relevant research in human clinical interactions, followed by a review of similar factors in social robotics research. Three databases were searched for terms relating to healthcare professional communication behaviours associated with patient outcomes. The results identified key communication behaviours that can convey clinical empathy, including humour, self-disclosure, facial expressions, eye gaze, body posture, and gestures. A further search was conducted to identify research examining these key behaviours within the context of social and healthcare robotics. Research into these factors in human–robot interaction in healthcare is limited to date, and this review provides a useful guide for future research.

Factors of healthcare robot adoption by medical staff in Thai government hospitals

The patients increasing number and growing shortage of medical staff are acute problems that face the healthcare industry today. Healthcare robots are being installed to solve this problem, since they have sufficient potential to solve the problems. The healthcare robot initiative success is not only based on the executives’ decisions and robot designers but also on medical staff members’ willingness to adopt healthcare robots. Nowadays, there are gaps in our understanding about the evaluation of staff changes in using robots. This study investigated the factors involved in the robots using in Thai government hospitals based on the results of 466 questionnaire respondents. The medical staff was selected randomly for data collection. The Confirmatory factor analysis (CFA) and a structural equation modeling (SEM) are tools used in data analysis. The findings confirmed that all four UTAUT constructs of the study, namely, the facilitating conditions, social influence, effort expectancy, performance expectancy, and concerns about safety, significantly predicted the use of robots (p < .01). Medical practitioners under 35 years of age tended to accept the technology better than their more senior counterparts. The staff’s intentions and facilitation of support played a key role in adopting and using robots. Lack of technical knowledge was perceived as a barrier to technology adoption. The results also indicate a significant negative effect in the relationship between the medical staff’s behavioral intention and barrier/resistance to the healthcare robot using. This study also identifies key factors for medical staff to make acceptance decisions in relation to healthcare robots.

Calming Effects of Touch in Human, Animal, and Robotic Interaction-Scientific State-of-the-Art and Technical Advances.

Small everyday gestures such as a tap on the shoulder can affect the way humans feel and act. Touch can have a calming effect and alter the way stress is handled, thereby promoting mental and physical health. Due to current technical advances and the growing role of intelligent robots in households and healthcare, recent research also addressed the potential of robotic touch for stress reduction. In addition, touch by non-human agents such as animals or inanimate objects may have a calming effect. This conceptual article will review a selection of the most relevant studies reporting the physiological, hormonal, neural, and subjective effects of touch on stress, arousal, and negative affect. Robotic systems capable of non-social touch will be assessed together with control strategies and sensor technologies. Parallels and differences of human-to-human touch and human-to-non-human touch will be discussed. We propose that, under appropriate conditions, touch can act as (social) signal for safety, even when the interaction partner is an animal or a machine. We will also outline potential directions for future research and clinical relevance. Thereby, this review can provide a foundation for further investigations into the beneficial contribution of touch by different agents to regulate negative affect and arousal in humans.

Smoking Cessation by Electronic Cigarettes and Applied Artificial Intelligence

Numerous fields and administrations are embracing smart robotics. Despite the vast advancements in robotics for health care, there is limited practice and examination on utilizing electronic cigarettes (e-cigarettes, e-cigs, ENDS) and applied artificial intelligence (AI) to aid tobacco consumers to quit smoking. E-cigs and AI are certainly significant tools that have the potential in helping Americans reduce smoking. It can be valuable for society to determine if e-smoking (smoking e-cigs) is much safer and cleaner than traditional smoking.

Physical Sensors Based on Laser-Induced Graphene: A Review

Physical sensors form the fundamental building blocks of a multitude of advanced applications that detect and monitor the surroundings and communicate the acquired physical data. The everlasting need for more compliant, low-cost, and energy-efficient sensor solutions has led to considerable interest in enhancing their features and operation limits even further. While graphene has emerged as a promising candidate material, due to its outstanding electrical and mechanical properties, it is still not available in large volumes for practical applications. Meanwhile, Laser-Induced Graphene has opened new perspectives for a versatile, durable, printed physical sensing platform capable of detecting various physical parameters across a range of conditions and subjects. In this review, LIG physical sensors were categorized into four broad types based on their transduction mechanism: mechanical, thermal, magnetic, and electromagnetic. We summaries various design strategies established for preparing reliable physical sensors without the involvement of chemical treatments, synthesis, and multi-step fabrication processes. The review considers the effects of laser choice, lasing environment, and parameters on graphene properties. We also discuss a broad spectrum of applications of LIG physical sensors in fields ranging from healthcare, tactile sensing, environmental monitoring, energy harvesting, and soft robotics to desalination and THz modulation.

Service design method for both non-human and human actors: What kinds of jobs should be assigned to service robots?

A variety of healthcare robots for elderly care have been developed. However, as the elderly and caregivers experience psychological resistance towards not only new technologies but specifically to robots, the adoption of healthcare robots has scarcely progressed. This article aims to develop a service design method, which consists of a design process including design tools to identify jobs in an elderly care facility and to reveal what kinds of jobs to assign to service robots and to caregivers. This article develops a design method which is composed of six steps and adopts original design tools to identify jobs needed in elderly care facilities and assign them to human and non-human actors, including service robots. The tools include an actor map to visualize the Actor to Actor (A2A) network, a current jobs to be done (JTBD) worksheet to visualize existing jobs, a new JTBD worksheet to visualize new jobs, and an actor worksheet to summarize information about each actor including their philosophy. With this design method, we conducted a series of workshops with the aim to develop a service fulfilled by humans and non-humans at an elderly care facility in Shizuoka prefecture in Japan. The results of questionnaires administered to the workshop participants demonstrated the effectiveness of all the tools except the new JTBD worksheet. Also, the results of interviews with employees in the elderly care facility indicated the effectiveness of the approach, which reveals visible and invisible regulative, normative and cultural-cognitive elements through interviews with human actors, and embeds them in the service design process. The design method including the original design tools proposed in this article contribute to a service design method for the use of robots in elderly care facilities by allocating jobs to human actors and non-human actors appropriately, and it also contributes to the issue of psychological resistance to the adoption of service robots in these facilities, which brings efficiencies to society. The contribution of this article is to reframe the issue of resistance to the adoption of service robots in elderly care facilities to the issue of what kinds of jobs in an elderly care facility should be assigned to service robots or caregivers, and the development of a service design process including original design tools.

Problemas ético-jurídicos concernentes aos danos causados por robôs autónomos na saúde: algumas definições conceptuais

Objetivo: subsidiar a compreensão filosófica-especulativa dos conceitos de dano e autonomia no amplo e profícuo pensamento publicado sobre robôs. Metodologia: foi realizada uma análise da literatura mais relevante e uma definição conceptual prévia, para depois argumentar e definir noções fundamentais sobre o problema da programação ética de forma integrada. Resultados: dano e autonomia são conceitos acrítica e recorrentemente utilizados na literatura, porém, o convívio com robôs autónomos exige uma reflexão que tome em conta a agentividade ética de robôs em contraponto com humanos. Foram identificados três princípios como essenciais na procura de um consenso conceptual: o respeito pela recusa em ser tratado por um robô; a proteção da liberdade humana face a um robô; e a manutenção do tecido social. Conclusão: a programação ética de robôs autónomos, longe de ser um exercício utilitarista abstrato, exige um consenso transdisciplinar, ético-jurídico, que permita abranger diferentes categorias de dano e de autonomia.

Privacy in Pandemic: Law, Technology, and Public Health in the COVID-19 Crisis

The COVID-19 pandemic has caused millions of deaths and disastrous consequences around the world, with lasting repercussions for every field of law, including privacy and technology. The unique characteristics of this pandemic have precipitated an increase in use of new technologies, including remote communications platforms, healthcare robots, and medical AI. Public and private actors are using new technologies, like heat sensing, and technologically-influenced programs, like contact tracing, alike in response, leading to a rise in government and corporate surveillance in sectors like healthcare, employment, education, and commerce. Advocates have raised the alarm for privacy and civil liberties violations, but the emergency nature of the pandemic has drowned out many concerns. This Article is the first comprehensive account of privacy impacts related to technology and public health responses to the COVID-19 crisis. Many have written on the general need for better health privacy protections, education privacy protections, consumer privacy protections, and protections against government and corporate surveillance. However, this Article is the first comprehensive article to examine these problems of privacy and technology specifically in light of the pandemic, arguing that the lens of the pandemic exposes the need for both widescale and small-scale reform of privacy law. This Article approaches these problems with a focus on technical realities and social salience, and with a critical awareness of digital and political inequities, crafting normative recommendations with these concepts in mind.Understanding privacy in this time of pandemic is critical for law and policymaking in the near future and for the long-term goals of creating a future society that protects both civil liberties and public health. It is also important to create a contemporary scholarly understanding of privacy in pandemic at this moment in time, as a matter of historical record. By examining privacy in pandemic, in the midst of pandemic, this Article seeks to create a holistic scholarly foundation for future work on privacy, technology, public health, and legal responses to global crises.

Empathetic Speech Synthesis and Testing for Healthcare Robots

One of the major factors that affect the acceptance of robots in Human-Robot Interaction applications is the type of voice with which they interact with humans. The robot’s voice can be used to express empathy, which is an affective response of the robot to the human user. In this study, the aim is to find out if social robots with empathetic voice are acceptable for users in healthcare applications. A pilot study using an empathetic voice spoken by a voice actor was conducted. Only prosody in speech is used to express empathy here, without any visual cues. Also, the emotions needed for an empathetic voice are identified. It was found that the emotions needed are not only the stronger primary emotions, but also the nuanced secondary emotions. These emotions are then synthesised using prosody modelling. A second study, replicating the pilot test is conducted using the synthesised voices to investigate if empathy is perceived from the synthetic voice as well. This paper reports the modelling and synthesises of an empathetic voice, and experimentally shows that people prefer empathetic voice for healthcare robots. The results can be further used to develop empathetic social robots, that can improve people’s acceptance of social robots.

Skin-Like Stretchable Fuel Cell Based on Gold-Nanowire-Impregnated Porous Polymer Scaffolds.

Skin-like energy devices can be conformally attached to the human body, which are highly desirable to power soft wearable electronics in the future. Here, a skin-like stretchable fuel cell based on ultrathin gold nanowires (AuNWs) and polymerized high internal phase emulsions (polyHIPEs) scaffolds is demonstrated. The polyHIPEs can offer a high porosity of 80% yet with an overall thickness comparable to human skin. Upon impregnation with electronic inks containing ultrathin (2 nm in diameter) and ultrahigh aspect-ratio (>10 000) gold nanowires, skin-like strain-insensitive stretchable electrodes are successfully fabricated. With such designed strain-insensitive electrodes, a stretchable fuel cell is fabricated by using AuNWs@polyHIPEs, platinum (Pt)-modified AuNWs@polyHIPEs, and ethanol as the anode, cathode, and fuel, respectively. The resulting epidermal fuel cell can be patterned and transferred onto skin as "tattoos" yet can offer a high power density of 280 µW cm-2 and a high durability (>90% performance retention under stretching, compression, and twisting). The results presented here demonstrate that this skin-thin, porous, yet stretchable electrode is essentially multifunctional, simultaneously serving as a current collector, an electrocatalyst, and a fuel host, indicating potential applications to power future soft wearable 2.0 electronics for remote healthcare and soft robotics.

Relating Mori's Uncanny Valley in generating conversations with artificial affective communication and natural language processing.

Human beings express affinity (Shinwa-kan in Japanese language) in communicating transactive engagements among healthcare providers, patients and healthcare robots. The appearance of healthcare robots and their language capabilities often feature characteristic and appropriate compassionate dialogical functions in human-robot interactions. Elements of healthcare robot configurations comprising its physiognomy and communication properties are founded on the positivist philosophical perspective of being the summation of composite parts, thereby mimicking human persons. This article reviews Mori's theory of the Uncanny Valley and its consequent debates, and examines "Uncanny" relations with generating healthcare robot conversational content with artificial affective communication (AAC) using natural language processing. With healthcare robots provoking influential physical composition and sensory expressions, the relations in human-healthcare robot transactive engagements are argued as supportive of the design and development in natural language processing. This implies that maintaining human-healthcare robot interaction and assessing the eeriness situations explained in the Uncanny Valley theory are crucial positions for healthcare robot functioning as a valuable commodity in health care. As such, physical features, language capabilities and mobility of healthcare robots establish the primacy of the AAC with natural language processing as integral to healthcare robot-human healthcare practice.

Special issue on “Advances in Robotics for Healthcare”

Special issue on “Advances in Robotics for Healthcare”

Full-color active-matrix organic light-emitting diode display on human skin based on a large-area MoS2 backplane.

Electronic applications are continuously developing and taking new forms. Foldable, rollable, and wearable displays are applicable for human health care monitoring or robotics, and their operation relies on organic light-emitting diodes (OLEDs). Yet, the development of semiconducting materials with high mechanical flexibility has remained a challenge and restricted their use in unusual format electronics. This study presents a wearable full-color OLED display using a two-dimensional (2D) material-based backplane transistor. The 18-by-18 thin-film transistor array was fabricated on a thin MoS2 film that was transferred to Al2O3 (30 nm)/polyethylene terephthalate (6 μm). Red, green, and blue OLED pixels were deposited on the device surface. This 2D material offered excellent mechanical and electrical properties and proved to be capable of driving circuits for the control of OLED pixels. The ultrathin device substrate allowed for integration of the display on an unusual substrate, namely, a human hand.

Home-Based Cognitively Assistive Robots: Maximizing Cognitive Functioning and Maintaining Independence in Older Adults Without Dementia.

Promoting health and prolonging independence in the home is a priority for older adults, caregivers, clinicians, and society at large. Rapidly developing robotics technology provides a platform for interventions, with the fields of physically and socially assistive robots expanding in recent years. However, less attention has been paid to using robots to enhance the cognitive health of older adults. The goal of this review is to synthesize the current literature on home-based cognitively assistive robots (CAR) in older adults without dementia and to provide suggestions to improve the quality of the scientific evidence in this subfield. First, we set the stage for CAR by: a) introducing the field of robotics to improve health, b) summarizing evidence emphasizing the importance of home-based interventions for older adults, c) reviewing literature on robot acceptability in older adults, d) highlighting important ethical issues in healthcare robotics, and e) reviewing current findings on socially assistive robots, with a focus on translating findings to the CAR context. With this foundation in place, we then review the literature on CAR, identifying gaps and limitations of current evidence, and proposing future directions for research. We conclude that CAR is promising and feasible and that there is a need for more methodologically rigorous evaluations of CAR to promote prolonged home-based independence in older adults.

Humanoid Nurse Robots and Compassion: Dialogical Conversation with Rozzano Locsin

It is important that in the future, nursing practice is framed with the humanoid nurse robot (HNR) functionality as a sure partner capable of expressing compassion that mimics human persons. Sr. Trecella May Macalam, SPC, a member of the Sisters of St. Paul of Chartres congregation, and doctoral student of St. Paul University Philippines and Dr. Rozzano Locsin, nurse theorist and author of the theory of Technological Competency as Caring in Nursing (TCCN) discuss the futurist idea of HNR’s capability to express compassion in nursing. Locsin’s theory has inspired the utility of advancing machine technologies in health care practice. Framing explanations and descriptions between human persons and HNRs as intelligent healthcare robots (IHRs) stimulate future nursing care in many ways. The theory of TCCN inspired “knowing persons as caring” as a process of nursing. In the future, this theory will most likely influence the inevitability and dependency of nursing through compassion in nursing by HNRs.

Social Robots for Elderly Care: An Inventory of Promising Use Cases and Business Models.

This paper discusses a study that aimed to elicit promising application areas and potential business models for social robotics in healthcare. For this goal, we conducted focus groups with care professionals and the management of elderly care organizations in the Netherlands and Germany. Three use cases were mentioned as the most promising: the robot as a ubiquitous aid, the robot as a helper in the room, and the robot as a guide. Finally, we discuss the implications of the medical device and privacy legislation for these three use cases.

The Future of Artificial Intelligence in International Healthcare: An Index

The currently ongoing COVID-19 crisis has challenged healthcare around the world. The call for global solutions in international healthcare pandemic outbreak monitoring and crisis risk management has reached unprecedented momentum. Digitalization, Artificial Intelligence (AI) and big data-derived inferences are supporting human decision making as never before in the history of medicine. In today’s healthcare sector and medical profession, AI, algorithms, robotics and big data are used as essential healthcare enhancements. These new technologies allow monitoring of large-scale medical trends and measuring individual risks based on big data-driven estimations. This article provides a snapshot of the current state-of-the-art of AI, algorithms, big data-derived inferences and robotics in healthcare. Examining medical responses to COVID-19 on a global scale makes international differences in the approaches to combat global pandemics with technological solutions apparent. Empirically, the article answers what countries have favourable conditions to provide AI-driven global healthcare solutions. First, an index based on internet connectivity – as a proxy for digitalization and AI advancement – as well as Gross Domestic Product (GDP) – as indicator for economic productivity – is calculated to outline global healthcare innovation hubs with economic impetus around the world. The parts of the world that feature internet connectivity and high GDP are likely to lead on AI-driven big data insights for pandemic prevention. When comparing countries worldwide, AI advancement is found to be positively correlated with anti-corruption. AI thus springs from non-corrupt territories of the world. Second, a novel anti-corruption artificial healthcare index is therefore presented that highlights those countries in the world that have vital AI growth in a non-corrupt environment. These non-corrupt AI centres hold comparative advantages to lead on global artificial healthcare solutions against COVID-19 and serve as pandemic crisis and risk management innovators of the future. Anti-corruption is also positively related with better general healthcare. Therefore, finally, a third index that combines internet connectivity, anti-corruption as well as healthcare access and quality is presented. The countries that score high on AI, anti-corruption and healthcare excellence are promoted as ultimate innovative global pandemic alleviation leaders. The advantages but also potential shortfalls and ethical boundaries in the novel use of monitoring Apps, big data inferences and telemedicine to prevent pandemics are discussed.

ARE INDONESIAN NURSES READY FOR HEALTHCARE ROBOTS DURING THE COVID-19 PANDEMIC?

Healthcare robots are used in Indonesia and other countries to combat COVID-19 pandemic. This article was aimed to describe a perspective about healthcare robots, and to recommend ways for Indonesian nurses to engage with healthcare robots during the COVID-19 pandemic. One view hindering healthcare robot appreciation as partners of nurses is its threat to their practice. However, with the current environment of COVID-19 ‘frontline’ situations, increasing infections of patients with SARS COV2, limited personal protective equipment, and the fastidious nature of maintaining social distancing and mask-wearing, it may be best to view healthcare robots as significant partners to facilitate safety, and ease the demands of nursing care activities in order to safeguard human lives while enhancing human well-being. Educating healthcare practitioners about healthcare robot programming and assurance of its safe and secure use can advance robot appreciation as partners in healthcare. These goals, challenges, and recommendations can provide Indonesian nurses some pathways-to-readiness towards a partnership involving healthcare robots, particularly during this COVID-19 pandemic, and in the future.