Abstract-In general, the applications of robots have shifted rapidly from industrial uses to social uses. This provides robots with the ability to naturally interact with human beings and socially fit into the human environment. The deployment of social robots in the healthcare system is becoming extensive as a result of the shortage of healthcare professionals, rising costs of healthcare and the exponential growth in the number of vulnerable populations such as the sick, the aged and children with developmental disabilities. Consequently, social robots are used in healthcare for providing health education and entertainment for patients in the hospital and for providing aids for the sick and aged. They are also used for dispensing drugs and providing rehabilitation as well as emotional and aging care. Hence, social robots improve the efficiency and quality of healthcare services. The interaction between social robots and human beings is known as human-robot interaction. Human-robot interaction in healthcare is faced with numerous challenges such as the fear of displacement of caregivers by robots, safety, usefulness, acceptability as well as appropriateness. These challenges ultimately lead to a low rate of acceptance of the robotic technology. Consequently, this paper extensively appraises humanrobot interaction in healthcare, their applications and challenges. Design, ethical and usability issues such as privacy, trust, safety, users' attitude, culture, robot morphology as well as emotions and deception arising from the interaction between humans and robots in healthcare are also reviewed in this paper.
In recent times, there is a paradigm shift from the use of paper based systems to the use of software systems in all spheres of life. However, the development of high quality, cost effective and useable software systems is a major challenge. One of the major obstacles confronting the successful implementation of software systems is the inability to implement all stakeholders' requirements in software development projects. This constraint is usually due to limited human resources, budget and time. Thus, most software systems have failed. It, therefore, becomes pertinent to prioritize software requirements. Requirement prioritization involves the selection of requirements that are considered more important from an accumulated list of stakeholders' requirements. There are two techniques that are used for categorizing software requirements. These techniques include the requirement prioritization methods and the negotiation methods. Requirement prioritization methods are based on different scales which include nominal scale, ordinal scale and ratio scale. The accuracy of these methods, however, is a challenge especially when prioritizing large number of requirements. Aims: Hence, this paper reviews different techniques for prioritizing requirements by highlighting their strengths and weaknesses. Techniques such as binary search tree, AHP, hierarchy AHP, priority group/Numerical Analysis, bubble sort, MoSoW, simple ranking and Planning Game were analyzed and compared in this study. Methodology: The study is based on previous literature on requirement prioritization. Results: The study showed that numerical assignment and simple ranking methods require less time in the prioritization process and they also have low scalability and reliability. The study also showed that the analytic hierarchy process requires more time for requirement prioritization; it is reliable but it is not scalable. The study also revealed that it is difficult to prioritize requirements with the existing prioritization techniques when multiple stakeholders are involved. Conclusion: The study suggests that future researches should be based on the design of requirement prioritization techniques that will have the ability to accommodate large stakeholders and requirements.
Advances in robotics have paved the way for a novel approach of organizing large numbers of robots, otherwise referred to as multi-robots. Multi-robots can either be homogenous or heterogeneous. Nevertheless, a group of autonomous and relatively homogenous robots that interacts with one another as well as with their environment is referred to as swarm robots. Swarm robots are biologically inspired by natural swarms as found in animal societies such as birds and fishes as well as social insects such as honey bees, wasps, termites and ants. Hence, they exhibit certain properties which are similar to those found in these creatures such as aggregation, self-organization, foraging as well as flocking. Swarm robots work together to achieve a desired goal, which is usually too complex for a single robot to accomplish. They are typically characterized by simplicity of individuals, fault tolerance, autonomy, parallelism, high reliability, scalability as well as robustness. They can be used for mining, military, medical and agricultural activities. They can also be used for search and rescue missions, toxic waste cleanup, and for piling sandbags along coastlines in preparation for floods or hurricane. Nevertheless, swarm robots are plagued with the stigma of widespread, interference, uncertainty, safety and lack of reliable communication. Furthermore, studies in swarm robotics are practically limited to virtual reality simulations. Hence, the principles of swarm robotics are rarely applied to real-life problems. It is against this background that this study systematically explores swarm robots. This study reviewed eighty literatures relating to swarm robots. These literatures were obtained from journal articles, technical reports, books, and conference proceedings. The selection of these literatures was based on their relevance to the research problem. This study revealed that the application of swarm robots to real life problems would promote the development of systems that are robust, fault tolerant and scalable.
Brain-Computer Interface (BCI) otherwise known as a Brain-Machine Interface (BMI) is an emergent technology whose goal is to create a real-time and direct communication pathway between the brain and external devices such as computers, robots, artificial limbs and wheelchairs. In BCI, cerebral or brain activities control these devices by transmitting and receiving signals from the brain. BCI is applied in healthcare to improve the communication capabilities of people living with disabilities or locked in syndrome such as traumatic brain disorders, Amyotrophic Lateral Sclerosis (ALS), spinal cord injury, brain stem stroke and other severe motor disabilities. BCI also increases the independence of disabled individuals by improving their muscle control. Consequently, BCI improves the quality of life of disabled persons by allowing this group of people to live a normal and comfortable life. In spite of the benefits of BCI, the technology is not widely deployed in healthcare. This is because of the numerous challenges associated with it. One of the basic limitations of BCI is that the signals received from the brain are prone to interference. Furthermore, legal and ethical concerns such as the risk of infection or hemorrhage, psychological
Abstract-Requirements engineering (RE) addresses the first software development step and lays the foundation for a successful system. Consequently, ability to identify problems and suggestions for improvements in the RE process opens up significant potential for increasing the success of software projects. Since RE process is naturally collaborative in nature, the intensiveness from both knowledge and human perspectives opens up the problem of decision making on requirements that can be facilitated by requirements prioritisation. In this regard, the paper opined the need for requirements prioritization techniques that will help the developers to obtain consensus among stakeholders using a suitable technique. In particular, the paper proposed a RE process model using Delphi technique. The Delphi technique was suggested in this paper to facilitate and enhance the process of requirements prioritisation in a multilevel prioritisation dimension. Therefore, the proposed model on implementation will contribute to the formulation of an interactive framework for requirements prioritisation to produce a requirement ordering which complies with the existing priorities.
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