Tanvir Mahmud

1.Social Robot Interventions in Mental Health Care and Their Outcomes, Barriers, and Facilitators: Scoping Review

The integration of social robots into therapeutic settings has emerged as a promising area of exploration in mental health care. With the growing demand for alternative therapeutic modalities, especially for patients with chronic conditions, social robots have been recognized for their potential to assist in providing emotional support, improving engagement, and facilitating social interaction. This review aims to synthesize existing literature on social robot interventions in mental health care, exploring their outcomes, barriers, and facilitators to implementation.

Social Robots in Mental Health Care

Social robots are defined as robotic systems that can engage in social interaction, designed to provide companionship, support, or assistance. These robots are increasingly used in various therapeutic contexts, particularly with populations that experience conditions such as dementia, depression, schizophrenia, autism spectrum disorder (ASD), and intellectual disabilities. The key feature of these interventions is their ability to create a non-threatening, interactive environment where patients can engage in social activities that promote emotional well-being.

Outcomes of Social Robot Interventions

The outcomes of social robot interventions in mental health care have been widely studied, though they tend to focus on several key areas: engagement, social interaction, emotional state, behavior, and quality of life.

1. Engagement: Several studies reported increased patient engagement with social robots compared to traditional therapeutic methods. These robots offer a novel and stimulating way for patients to interact, often leading to more active participation in activities that are designed to improve cognitive and emotional health.

2. Social Interaction: Social robots have shown promise in improving social interactions, particularly in populations where social withdrawal is a common symptom, such as patients with schizophrenia and dementia. The robots serve as a neutral and non-judgmental interaction partner, fostering communication and reducing feelings of isolation.

3. Emotional State: Many studies highlighted that social robot interventions had a positive impact on patients' emotional states. For instance, patients with dementia exhibited less agitation and distress when interacting with robots. Similarly, the presence of robots has been linked to enhanced mood and decreased anxiety, especially in patients with autism and ADHD.

4. Behavioral Improvements: The use of robots has also been associated with behavioral improvements. In the case of patients with ASD and intellectual disabilities, robots have helped to reduce disruptive behaviors and encourage positive actions. The consistent and predictable nature of the robots may be beneficial in managing behaviors that are often difficult to control in therapeutic settings.

5. Quality of Life: While the data on quality of life outcomes remain inconclusive, many studies suggest that social robots contribute positively to patients' overall quality of life. By providing companionship and fostering interactions, robots appear to help improve the overall well-being of patients, although long-term effects remain unclear.

Barriers to Implementation

Despite the promising outcomes, several barriers to the implementation of social robot interventions have been identified. These include:

1. Technical Problems: One of the most significant challenges faced by mental health facilities is the technical issues associated with robots, such as malfunctions, difficulties in programming, and limitations in adaptability. The need for continuous updates and maintenance of the robots may create significant operational hurdles.

2. Unsuitable Environments: Many therapeutic environments are not equipped to accommodate social robots, particularly in terms of space and infrastructure. Ensuring that robots can be successfully integrated into diverse settings, such as residential care facilities or outpatient clinics, remains a challenge.

3. Staff Resistance: Mental health professionals may resist the implementation of social robots, particularly if they perceive them as a threat to their role or if they lack confidence in the technology. Staff training and education about the benefits of social robots are essential to overcoming this barrier.

Facilitators to Implementation

Several factors have been identified as facilitators to the successful implementation of social robots in mental health care:

1. Staff Buy-In: Having staff members who are supportive of the technology and willing to engage with it is crucial to the success of robot interventions. When staff are properly trained and understand the benefits of robots, their involvement in the therapy process is more likely to enhance patient outcomes.

2. Customization: The ability to tailor robots to meet the specific needs of individual patients has been identified as a key facilitator. Customization allows robots to adapt to various conditions, providing more personalized and effective support.

3. Collaborations with Technologists: Effective collaboration between healthcare providers and robotic technologists is essential for overcoming technical challenges. Working closely with engineers and developers ensures that the robots are appropriately designed, functional, and capable of addressing the unique needs of the patients.

2.Potential Applications of Social Robots in Robot-Assisted Interventions for Social Anxiety 

Social anxiety disorder (SAD), also known as social phobia, is a prevalent mental health condition characterized by intense fear of negative evaluation in social situations, leading to avoidance behaviors and significant distress. Conventional treatments for social anxiety, such as cognitive-behavioral therapy (CBT), have been shown to be effective. However, treatment adherence and engagement are often poor, with high rates of avoidance and attrition, particularly in vulnerable populations. To address these challenges, the use of assistive technologies, such as social robots, has gained attention as a promising tool in enhancing treatment accessibility, engagement, and effectiveness. This review explores the potential applications of social robots in robot-assisted interventions for social anxiety, focusing on their integration into existing behavioral and cognitive therapies.

Social Anxiety Disorder and Treatment Approaches

Social anxiety disorder is one of the most common psychiatric disorders, with a global lifetime prevalence of approximately 12%. It significantly impairs an individual’s ability to function in everyday social settings, such as work, school, and interpersonal relationships. Traditional treatments for SAD primarily include cognitive-behavioral therapy (CBT), which aims to modify dysfunctional thoughts and behaviors related to social situations. CBT has demonstrated strong efficacy, yet many individuals with SAD either do not seek treatment or drop out early due to fear, stigma, or discomfort in face-to-face interactions. Moreover, there are barriers to accessing high-quality therapy, particularly in underserved populations or regions with limited resources.

Given these challenges, there is growing interest in innovative therapeutic approaches that can supplement or enhance conventional treatments. One promising avenue is the use of social robots, which can serve as accessible, low-cost, and engaging tools for facilitating therapy and overcoming treatment barriers.

Social Robots in Mental Health Interventions

Social robots are designed to interact with humans in ways that resemble human-to-human communication, often through verbal and non-verbal cues. These robots can provide companionship, deliver therapeutic interventions, and act as a bridge between patients and mental health professionals. In the context of social anxiety, social robots have been used to simulate social situations, engage patients in social interactions, and offer feedback on social behaviors.

Several studies have demonstrated the feasibility and effectiveness of using social robots in clinical interventions for various psychological disorders, including autism, depression, and anxiety. For example, robots have been successfully used to facilitate exposure therapy by simulating social encounters in a controlled and non-threatening environment. The robot’s predictable behavior helps patients gradually confront their social fears without the overwhelming anxiety associated with human interaction.

Integration of Social Robots in Behavioral and Cognitive Therapies for Social Anxiety

The integration of social robots into conventional behavioral and cognitive therapies offers an innovative approach to treating social anxiety. We propose several therapeutic roles that social robots can play in activities related to symptom reduction, social skills development, and overall quality of life improvement for individuals with SAD. These roles include:

1. Simulation of Social Interactions: Social robots can simulate various social situations, allowing patients to practice social interactions in a safe and controlled environment. This can be particularly useful in exposure therapy, where patients gradually face feared social situations. The robot’s non-judgmental presence offers a comfortable space for individuals to rehearse social skills and receive immediate, constructive feedback.

2. Guided Cognitive Behavioral Exercises: Social robots can facilitate CBT-based exercises, such as cognitive restructuring, by guiding patients through thought-recording tasks, identifying irrational beliefs, and offering alternative coping strategies. Robots can also use natural language processing to engage patients in dialogue, providing cognitive challenges that help modify maladaptive thought patterns associated with social anxiety.

3. Enhancing Social Skills: For individuals with SAD, a core therapeutic goal is the development of social competence and confidence. Social robots can help patients practice verbal and non-verbal communication skills, such as maintaining eye contact, starting conversations, and interpreting body language. Through role-playing scenarios, robots can act as conversation partners and provide real-time feedback to help improve social competence.

4. Behavioral Reinforcement and Motivation: Robots can provide positive reinforcement for patients’ efforts in overcoming social anxiety. By offering praise, encouragement, and rewards for progress, robots can help motivate patients to continue engaging in therapy and applying learned skills in real-world situations. The robot’s consistent and reliable feedback may also contribute to building self-efficacy, a critical component of overcoming anxiety.

Scenarios for Robot-Assisted Interventions

The following four scenarios illustrate potential applications of social robots in clinical practice for social anxiety:

1. Self-Exposure Training: Patients use robots to simulate socially anxiety-inducing scenarios, such as public speaking or group discussions. The robot acts as the audience, allowing the patient to practice without the overwhelming fear of judgment from real people.

2. Therapeutic Conversations: Patients engage in one-on-one conversations with a robot to practice interpersonal skills, reduce avoidance behaviors, and receive feedback on their communication style. This scenario is particularly beneficial for patients who struggle with initiating or maintaining conversations in real-life social situations.

3. Cognitive Restructuring Exercises: Robots guide patients through structured CBT exercises, such as identifying automatic negative thoughts and replacing them with more rational alternatives. This scenario leverages the robot’s ability to guide patients through repetitive tasks and provide reinforcement for cognitive changes.

4. Social Skills Group Training: In a group setting, social robots can be used to simulate group interactions, helping patients practice group dynamics, active listening, and empathy. Robots can also mediate group discussions, ensuring that all participants are heard and respected.

Risks and Concerns

While social robots offer promising benefits, their integration into clinical practice raises several concerns. First, there is the risk of over-reliance on robots, leading to a reduction in human therapist involvement. It is essential that robots complement, rather than replace, human therapists. Additionally, the ethical implications of using robots in mental health treatment must be considered, particularly in terms of privacy, security, and emotional dependence on non-human entities. The potential for social robots to exacerbate isolation or reinforce avoidance behaviors in patients must also be carefully monitored.

3.A Brief Wellbeing Training Session Delivered by a Humanoid Social Robot: A Pilot Randomized Controlled Trial 

Mental health issues, including stress, anxiety, and depression, have become a growing concern globally, particularly in adults. The demand for effective, accessible mental health interventions has led to the exploration of innovative approaches that can enhance wellbeing. Social robots, particularly humanoid robots, are emerging as promising tools in delivering health and wellbeing programs, offering a novel method to support individuals in managing mental health. These robots can provide interactive, consistent, and non-judgmental environments that may encourage engagement and participation in mental health interventions. This literature review discusses the potential of humanoid social robots to deliver wellbeing training, focusing on the specific application of a mindfulness technique, and highlights the findings and implications of a pilot randomized controlled trial (RCT) that tested the feasibility of such interventions.

Social Robots in Mental Health Interventions

The use of robots in healthcare is a rapidly growing field, with applications spanning from elderly care to mental health support. Social robots, designed to interact with humans through social cues such as speech, body language, and gestures, have been particularly explored in contexts where human-like interactions are beneficial. Research on social robots has demonstrated their effectiveness in a variety of therapeutic domains, such as autism spectrum disorder, dementia, and anxiety management. These robots have the potential to provide support in a way that feels familiar and accessible, offering a non-threatening platform for individuals to engage in therapeutic activities.

In mental health, social robots have been used to promote psychological wellbeing through techniques such as mindfulness, cognitive-behavioral interventions, and relaxation exercises. Mindfulness, which involves paying full attention to the present moment with acceptance and without judgment, has been shown to reduce symptoms of stress and anxiety. Given the growing demand for accessible mental health interventions, the idea of using autonomous humanoid robots to deliver such practices is particularly appealing. These robots can provide a scalable, cost-effective solution that offers consistent support, overcoming barriers like limited availability of human therapists and stigma related to seeking help.

Mindfulness and Wellbeing Training via Robots

Mindfulness-based interventions (MBIs) have been found to be effective in promoting mental health and reducing psychological distress. Techniques such as mindful breathing, which focuses on controlling one’s breath to calm the mind and body, have been particularly highlighted for their simplicity and effectiveness. The delivery of such techniques through a social robot could potentially enhance their accessibility by allowing individuals to practice mindfulness at their own pace and in their own space.

Research on the use of robots to deliver mindfulness training is still in its early stages. While there have been some studies on robots delivering relaxation exercises or guided meditation, there is a lack of in-depth exploration of robots teaching specific wellbeing techniques, such as mindful breathing. The few studies that have examined robot-delivered mindfulness techniques suggest that social robots can successfully guide users through these exercises. These studies report positive outcomes, such as improved mood, reduced anxiety, and increased engagement with the technique. However, there is still a need for more rigorous research to evaluate the feasibility, effectiveness, and user preferences regarding robot-delivered wellbeing programs.

The Pilot Randomized Controlled Trial: Feasibility and Outcomes

The pilot randomized controlled trial in question aimed to explore the feasibility of using a humanoid social robot to deliver a brief mindful breathing technique as a wellbeing intervention. This study involved two conditions: a ‘Technique’ group that received the mindful breathing training and a ‘Simple Rapport’ group that engaged in a basic relationship-building conversation with the robot. The study recruited 230 participants, primarily higher education students with a mean age of 29 years, using convenience sampling. The trial’s results shed light on several important aspects of robot-delivered wellbeing interventions.

First, the recruitment uptake rate was high, with 53% of individuals agreeing to participate, indicating a positive interest in using robots for wellbeing interventions. Participants reported moderate levels of enjoyment, perceived usefulness, and likelihood to repeat the technique. This suggests that robot-delivered wellbeing programs, particularly in the form of a brief mindfulness technique, are well-received by users and could be an effective way to engage people in mental health practices.

The study also found interaction effects based on gender and distress levels, with males experiencing higher distress and females with lower distress being more comfortable discussing non-health-related topics with the robot. These findings point to the importance of tailoring robot-delivered interventions based on individual characteristics such as distress levels and gender. It may be necessary to customize the content and interaction style of robot-delivered interventions to maximize comfort and engagement.

Willingness to Discuss Health-Related Topics with Robots

An interesting component of this trial was the exploration of participants' willingness to discuss health-related topics with a robot. While robots have shown promise in delivering wellbeing training, one of the challenges in integrating them into clinical or therapeutic settings is overcoming potential discomfort or reluctance from users to engage with non-human entities about sensitive topics. The results of this trial indicate that individuals were generally comfortable engaging with the robot in discussing wellbeing techniques, but the level of comfort varied according to individual characteristics such as gender and distress levels. These findings suggest that while humanoid robots may have a place in health-related conversations, further investigation is needed to understand the factors that influence willingness to engage in discussions about mental health.

Risks and Concerns in Robot-Delivered Interventions

Despite the promising results, there are some risks and concerns associated with using robots to deliver wellbeing interventions. One concern is the potential for over-reliance on robots as a primary source of mental health support, which could limit the effectiveness of traditional therapeutic relationships. Furthermore, the use of robots raises ethical considerations regarding privacy, autonomy, and the appropriate boundaries between human and robot interactions. It is important that robots are used to complement, rather than replace, human therapists and that ethical guidelines are established for their use in mental health contexts.

4.Perceived safety in physical human–robot interaction—A survey 

As robots continue to move beyond industrial settings and into everyday environments, the notion of perceived safety in human-robot interactions (HRI) has become a critical area of research. Perceived safety refers to how safe individuals feel when interacting with autonomous robots, and it plays a crucial role in determining the success of these interactions, especially as robots are increasingly used in contexts where they share physical spaces with humans. While safety in HRI has traditionally focused on preventing physical harm, perceived safety encompasses a broader range of psychological and emotional factors, including trust, comfort, stress, fear, and anxiety. This literature review examines various studies and approaches in the domain of perceived safety in physical human–robot interactions, offering insights into how this concept has been assessed and the influence of robot characteristics on safety perception.

Conceptualizing Perceived Safety

Perceived safety is not a single, unified construct but instead a complex, multifaceted concept that can be defined in terms of psychological safety, trust, comfort, and emotional responses such as stress, fear, and anxiety. Psychological safety involves individuals' feelings of security in the presence of a robot, while trust pertains to the robot's ability to behave predictably and reliably in human-centric environments. Comfort is linked to the physical and emotional ease individuals feel when interacting with a robot, which in turn influences their willingness to engage in HRI. Stress, fear, and anxiety arise when robots exhibit unexpected, erratic, or untrustworthy behaviors, negatively impacting the overall experience of interaction. The balance between these various emotional and cognitive factors contributes to how safe a person perceives the interaction to be.

In addition to these emotional responses, the concept of perceived safety extends to physical safety—whether the robot’s behavior is deemed non-threatening to the individual’s well-being. This distinction highlights the importance of assessing both the emotional and physical dimensions of safety in HRI.

Methods for Assessing Perceived Safety

Several methods have been employed to measure perceived safety in human-robot interactions. These methods include:

1. Questionnaires: Self-reported assessments are one of the most common ways to gather data on perceived safety. Instruments such as the Safety Behavior Scale, the Trust in Automation Scale, and the Perceived Safety and Comfort Scale provide insight into how individuals feel about interacting with robots. These questionnaires focus on subjective factors like emotional comfort, fear, and trust, allowing researchers to gauge participants’ perceptions and attitudes toward robot interactions.

2. Physiological Measurements: Physiological responses such as heart rate, skin conductance, and facial expressions are used to measure emotional responses during human-robot interactions. These measurements can provide objective data on stress levels, anxiety, and excitement, offering a more nuanced understanding of how individuals react to robots beyond self-reported feelings.

3. Behavioral Assessment: Behavioral observations, such as body language, gaze direction, and movement patterns, offer another method of assessing perceived safety. Changes in behavior can reveal discomfort, hesitation, or confidence, shedding light on participants’ unconscious responses to robots during interactions.

4. Direct Input Devices: Tools like joysticks, touchscreens, or voice input systems allow users to directly interact with robots while simultaneously providing data on their comfort level and engagement. The interaction style can also be analyzed to determine how safely individuals feel when guiding or communicating with robots.

Each of these methods offers distinct advantages, but they are often used in combination to provide a comprehensive understanding of perceived safety in HRI.

Autonomous Systems and Perceived Safety

Different types of autonomous systems present unique challenges and considerations when it comes to perceived safety. The following six categories of autonomous systems have been extensively studied in relation to HRI:

1. Industrial Poly-Articulated Manipulators: These robots, commonly used in manufacturing and assembly, pose significant risks of injury due to their large, heavy moving parts. The design and motion characteristics of these robots influence safety perceptions, with factors like speed, size, and the presence of safety barriers playing key roles. Research has shown that participants are more likely to feel safe interacting with these robots when they are designed with clear motion limits and fail-safes that reduce unpredictability.

2. Indoor Mobile Robots: These robots, often used in service or healthcare applications, interact with humans in enclosed spaces. Factors such as their size, speed, and ability to navigate obstacles influence users' sense of safety. Slow-moving robots with clear, predictable movements are generally perceived as safer, while robots that move erratically or too quickly may evoke anxiety and fear.

3. Mobile Manipulators: Combining both mobility and manipulation capabilities, these robots can perform a wide range of tasks but also present unique safety concerns. Their movement and ability to manipulate objects in dynamic environments require precise control and careful design to avoid causing harm. Studies indicate that users' perceptions of safety are influenced by the robot’s smoothness of motion and its ability to avoid collisions with humans.

4. Humanoid Robots: Humanoid robots, designed to resemble human beings in appearance and behavior, are particularly interesting in the context of perceived safety due to their potential to evoke strong emotional responses. The "uncanny valley" phenomenon, where robots that are almost human-like but not quite perfect create feelings of discomfort or unease, is a key factor influencing safety perceptions. Researchers have found that humanoid robots that display more human-like behaviors, such as gaze, facial expressions, and body language, tend to increase trust and comfort, while robotic behaviors that seem unnatural or unpredictable reduce perceived safety.

5. Drones: Unmanned aerial vehicles (UAVs), commonly known as drones, have become increasingly used in various applications, from delivery services to surveillance. The perceived safety of drones depends on factors such as their proximity to humans, the noise they produce, and their ability to maintain a stable flight path. Studies show that drones are generally perceived as more threatening when they operate close to individuals or in environments where they are unexpected, leading to an increase in stress and anxiety.

6. Autonomous Vehicles: Autonomous cars and other self-driving vehicles are becoming a major focus in robotics research due to their potential to revolutionize transportation. Perceived safety in autonomous vehicles is influenced by the vehicle’s reliability, decision-making algorithms, and the way it interacts with human drivers or pedestrians. Research indicates that public trust in autonomous vehicles is often low due to concerns about their ability to handle emergency situations or complex driving environments.

Motion and Characteristics of the System

The design and motion characteristics of robots are key factors in shaping perceptions of safety. Smooth, predictable, and slow movements tend to increase comfort, while rapid, jerky, or erratic movements often raise anxiety. The level of transparency in the robot’s actions—such as indicating its intentions or trajectory—also plays a significant role in enhancing trust and reducing fear. Additionally, robots with more human-like characteristics, such as facial expressions and voice cues, may enhance perceived safety by fostering a sense of familiarity and empathy.

Perceived Safety and Safety Standards

The connection between perceived safety and safety standards is also an important area of focus. While safety standards are primarily concerned with minimizing physical risks to humans, perceived safety involves the broader psychological and emotional dimensions of interaction. There is a growing need to establish safety standards that address both the physical and psychological aspects of HRI. Many researchers advocate for the development of universal guidelines that take into account users’ emotional reactions to robots, ensuring that robots are not only physically safe but also emotionally comfortable to interact with.

5.Mental stress and safety awareness during human-robot collaboration - Review 

Human-robot collaboration (HRC) is an evolving research field that has seen increasing attention in both academic and industrial contexts. The integration of robots into shared workspaces with human workers holds the potential to improve productivity, efficiency, and precision in tasks that are complex or hazardous. However, the introduction of robots into these environments has raised concerns, particularly regarding the safety of workers. The issue of mental stress and safety awareness during human-robot collaboration has gained prominence, as it can directly influence both individual well-being and the overall effectiveness of HRC. This literature review examines studies that explore the relationships between HRC and workers' mental stress and safety awareness, focusing on robot-related factors, measurement techniques, and potential interventions to mitigate these issues.

Robot-Related Factors Influencing Mental Stress and Safety Awareness

Several robot-related factors have been identified as having an impact on workers' mental stress and safety awareness during HRC. These factors include the robot's characteristics, the nature of social interactions such as social touching, and the robot’s trajectory or motion patterns.

1. Robot Characteristics: The design and behavior of robots have a significant influence on human workers' mental stress and their awareness of safety risks. Key characteristics, such as the robot’s size, shape, movement speed, and predictability, affect how comfortable workers feel when sharing a workspace with these machines. Large robots or those with erratic movements tend to increase stress levels, while smaller, more predictable robots are generally perceived as less threatening. Additionally, humanoid robots that closely resemble human beings may evoke higher levels of discomfort or stress in some workers due to the "uncanny valley" effect, where near-human features that are imperfect or ambiguous cause unease.

2. Social Touching: In certain applications, robots may be designed to physically interact with human workers, such as through social touching or handshakes. These types of physical interactions can influence mental stress and safety awareness. Positive social interactions, such as collaborative tasks where robots assist with lifting or guiding movements, may reduce perceived stress and improve safety perceptions. Conversely, unexpected or uncontrolled physical interactions, such as robots inadvertently touching workers, can create anxiety and increase the risk of safety concerns. Thus, clear and predictable physical interactions are crucial in minimizing stress and enhancing trust.

3. Trajectory and Motion Patterns: The robot’s motion trajectory also plays a critical role in shaping the mental state of workers. Robots that move erratically or too quickly may cause alarm or anxiety in workers, while robots that follow predictable, smooth, and well-timed motions are generally perceived as safer. The predictability of a robot's path helps workers anticipate its actions, leading to a decrease in stress and an increase in confidence in the robot's ability to operate safely in shared environments. Research has shown that more intuitive robot motions (e.g., a robot that stops in time when approaching a human worker) reduce the cognitive load and stress levels of workers, improving safety awareness.

Measuring Mental Stress and Safety Awareness

Understanding the mental stress and safety awareness of workers in HRC scenarios requires effective measurement methods. Researchers have employed a variety of approaches to evaluate these factors, each with its strengths and weaknesses.

1. Mental Stress Measurement: Various tools have been used to assess mental stress during HRC, including physiological measurements, self-reported surveys, and behavioral observations. Physiological measures such as heart rate variability, skin conductance, and EEG (electroencephalography) provide real-time, objective data on stress levels. These methods are useful for detecting autonomic nervous system responses, which are closely linked to stress. For example, an increased heart rate or elevated skin conductance often signals heightened stress. Behavioral assessments, such as eye-tracking, body posture, and movement patterns, offer indirect indicators of stress. A worker’s avoidance behaviors or signs of discomfort during an interaction with a robot may indicate heightened stress levels.
   Self-reported surveys and questionnaires are commonly used to assess workers' subjective experiences of stress. These instruments, such as the State-Trait Anxiety Inventory (STAI) or the NASA Task Load Index (NASA-TLX), ask workers to rate their stress, anxiety, and overall comfort during robot interactions. Though subjective, these surveys provide valuable insights into workers' perceptions of their stress levels during HRC and can help identify the emotional and psychological factors contributing to stress.

2. Safety Awareness Measurement: Safety awareness is another crucial aspect that influences how effectively humans and robots can collaborate. Methods for measuring safety awareness include questionnaires, interviews, and observational techniques. Surveys such as the Safety Climate Questionnaire (SCQ) or the Safety Awareness Scale assess workers’ general attitudes toward safety and their understanding of risks in the work environment. These self-reported assessments provide insights into how workers perceive safety within the context of human-robot collaboration.
   Additionally, observational studies and behavioral analysis during real-time robot interaction can offer insights into workers' proactive and reactive behaviors in response to potential safety hazards. For instance, how often workers check the robot's movements or how quickly they move away from the robot when it approaches them too closely can provide indicators of their safety awareness. Furthermore, feedback systems that allow workers to communicate their safety concerns in real time can offer valuable data on how aware and vigilant workers are about potential hazards.

Co-Robot Actions to Reduce Stress and Improve Safety Awareness

To mitigate mental stress and enhance safety awareness, researchers have explored the potential for robots to take proactive actions that help workers feel more secure in collaborative environments. These co-robot actions may involve both physical and behavioral strategies.

1. Collaborative Actions: Robots that can predict and adjust their behavior in response to human workers’ actions may reduce stress levels and foster a sense of safety. For example, a robot that can sense a worker’s proximity and slow down or stop its movements accordingly helps to prevent accidents and reduces anxiety. Additionally, robots that provide feedback about their intentions (e.g., a robot informing a worker about upcoming actions through visual or auditory cues) can increase transparency and enhance trust.

2. Personalization of Interaction: The ability to customize robot interactions based on individual worker preferences and stress levels can improve safety awareness. For instance, robots could adapt their motion speed or interaction style depending on a worker’s comfort level or emotional state, which could be assessed through physiological sensors or subjective feedback.

3. Training and Education: Robots that assist in training workers on safety protocols, such as demonstrating correct safety behaviors or offering reminders about hazardous areas, can enhance safety awareness in collaborative environments. By actively participating in safety education, robots contribute to the mental preparedness of workers and reduce the likelihood of safety violations.