Background The COVID-19 pandemic is affecting the mental and emotional well-being of patients, family members, and health care workers. Patients in the isolation ward may have psychological problems due to long-term hospitalization, the development of the epidemic, and the inability to see their families. A medical assistive robot (MAR), acting as an intermediary of communication, can be deployed to address these mental pressures. Objective CareDo, a MAR with telepresence and teleoperation functions, was developed in this work for remote health care. The aim of this study was to investigate its practical performance in the isolation ward during the pandemic. Methods Two systems were integrated into the CareDo robot. For the telepresence system, a web real-time communications solution is used for the multiuser chat system and a convolutional neural network is used for expression recognition. For the teleoperation system, an incremental motion mapping method is used for operating the robot remotely. A clinical trial of this system was conducted at First Affiliated Hospital, Zhejiang University. Results During the clinical trials, tasks such as video chatting, emotion detection, and medical supplies delivery were performed via the CareDo robot. Seven voice commands were set for performing system wakeup, video chatting, and system exiting. Durations from 1 to 3 seconds of common commands were set to improve voice command detection. The facial expression was recorded 152 times for a patient in 1 day for the psychological intervention. The recognition accuracy reached 95% and 92.8% for happy and neutral expressions, respectively. Conclusions Patients and health care workers can use this MAR in the isolation ward for telehealth care during the COVID-19 pandemic. This can be a useful approach to break the chains of virus transmission and can also be an effective way to conduct remote psychological intervention.

A Medical Assistive Robot for Telehealth Care During the COVID-19 Pandemic: Development and Usability Study in an Isolation Ward

The relevancy of food and beverage business will never fade. With that in mind, using the tech in order to improve its process will allow the business to thrive and improve its efficiency. Customer service is a fitting role for tech to work, as artificial intelligence might prove to be able to do the job efficiently and effectively. This paper tries to implement a customer service chatbot for restaurants so they may leverage its advantages in order to improve in terms of performance and efficiency. The implementation is done using the LSTM model which has proven to have decent results in chatbot implementation.

Chatbot Application to Automate Services in FnB Business Using Seq2Seq LSTM

Recently, chatbot technology has been employed in several customer services and support roles. These conversational agents have become valuable assets to companies and organizations because of their ability to communicate with humans and process large amounts of data. Furthermore, since most customers are using online shopping to fulfill their requirements instead of traditional methods, they expect to get a full 24-hour service. This survey provides an overview of different studies that used chatbots as a tool to provide customer service and analyzes the techniques applied to it. In this survey, we divided the studies into two parts, the algorithms, techniques used in creating a chatbot, and the influence of the chatbot's use on marketing. Research shows most of the studies used Deep learning techniques for building chatbots. In addition, chatbot provides services that enable customers to have better communication with the brand and affect their long-term relationships. 

A Survey on the Impact of Chatbots on Marketing Activities

Recently, chatbot technology has been employed in several customer services and support roles. These conversational agents have become valuable assets to companies and organizations because of their ability to communicate with humans and process large amounts of data. Furthermore, since most customers are using online shopping to fulfill their requirements instead of traditional methods, they expect to get a full 24-hour service. This survey provides an overview of different studies that used chatbots as a tool to provide customer service and analyzes the techniques applied to it. In this survey, we divided the studies into two parts, the algorithms, techniques used in creating a chatbot, and the influence of the chatbot's use on marketing. Research shows most of the studies used Deep learning techniques for building chatbots. In addition, chatbot provides services that enable customers to have better communication with the brand and affect their long-term relationships.

<sec> <title>BACKGROUND</title> The COVID-19 pandemic is affecting the mental and emotional well-being of patients, family members, and health care workers. Patients in the isolation ward may have psychological problems due to long-term hospitalization, the development of the epidemic, and the inability to see their families. A medical assistive robot (MAR), acting as an intermediary of communication, can be deployed to address these mental pressures. </sec> <sec> <title>OBJECTIVE</title> CareDo, a MAR with telepresence and teleoperation functions, was developed in this work for remote health care. The aim of this study was to investigate its practical performance in the isolation ward during the pandemic. </sec> <sec> <title>METHODS</title> Two systems were integrated into the CareDo robot. For the telepresence system, a web real-time communications solution is used for the multiuser chat system and a convolutional neural network is used for expression recognition. For the teleoperation system, an incremental motion mapping method is used for operating the robot remotely. A clinical trial of this system was conducted at First Affiliated Hospital, Zhejiang University. </sec> <sec> <title>RESULTS</title> During the clinical trials, tasks such as video chatting, emotion detection, and medical supplies delivery were performed via the CareDo robot. Seven voice commands were set for performing system wakeup, video chatting, and system exiting. Durations from 1 to 3 seconds of common commands were set to improve voice command detection. The facial expression was recorded 152 times for a patient in 1 day for the psychological intervention. The recognition accuracy reached 95% and 92.8% for happy and neutral expressions, respectively. </sec> <sec> <title>CONCLUSIONS</title> Patients and health care workers can use this MAR in the isolation ward for telehealth care during the COVID-19 pandemic. This can be a useful approach to break the chains of virus transmission and can also be an effective way to conduct remote psychological intervention. </sec> 

A Medical Assistive Robot for Telehealth Care During the COVID-19 Pandemic: Development and Usability Study in an Isolation Ward (Preprint)

The use of intelligent machines such as chatbot have been increasing each day. The main idea that we wanted to address in our paper is that with the capabilities that intelligent machines have it will be able to replace humans in doing a certain task and be able to bring better advantages in the long run. The focus of this study is that we are able to manipulate the ability of chatbot to impersonate how humans interact with each other and will enable it to play a role as to handle the customer service in e-commerce websites or applications which will be an alternative to replace the traditional customer service

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Helen Clarissa

Papers

The Application of Chatbot for Customer Service in E-Commerce