Survey on Physiological Computing in Human–Robot Collaboration

Abstract

Human–robot collaboration has emerged as a prominent research topic in recent years. To enhance collaboration and ensure safety between humans and robots, researchers employ a variety of methods. One such method is physiological computing, which aims to estimate a human’s psycho-physiological state by measuring various physiological signals such as galvanic skin response (GSR), electrocardiograph (ECG), heart rate variability (HRV), and electroencephalogram (EEG). This information is then used to provide feedback to the robot. In this paper, we present the latest state-of-the-art methods in physiological computing for human–robot collaboration. Our goal is to provide a comprehensive guide for new researchers to understand the commonly used physiological signals, data collection methods, and data labeling techniques. Additionally, we have categorized and tabulated relevant research to further aid in understanding this area of study.

Physiological data for affective computing in HRI with anthropomorphic service robots: the AFFECT-HRI data set

“…Nonetheless, the available data sets used to develop those emotion recognition methods and capabilities came from general human-machine interaction research and, thus, are not suited in real settings with robots 3 . In line with this, recent publications claim that the lack of open data hinders further development of affective computing in HRI, utilizing physiological data [3][4][5][6] .…”

Um Estudo Sobre as Percepções Dos Profissionais De Publicidade E Propaganda Sobre O Neuromarketing

“…Esse avanço tecnológico foi fundamental para o desenvolvimento de técnicas de medição das respostas emocionais dos consumidores no contexto do Neuromarketing. Willem Einthoven criou o primeiro dispositivo para medir a atividade cardíaca em 1902, chamado eletrocardiograma (ECG), tornando o monitoramento da atividade cardíaca uma ferramenta valiosa, uma vez que as emoções muitas vezes se refletem em alterações no ritmo cardíaco (Savur;Sahin, 2023). Essa capacidade de medir as respostas emocionais com base na atividade cardíaca foi um avanço importante na pesquisa de mercado.…”

“…Hans Berger registrou a primeira medição eletroencefalográfica em 1924, um método para medir a atividade elétrica dos neurônios no cérebro (Savur;Sahin, 2023). Essa descoberta permitiu aos pesquisadores de Neuromarketing explorar como o cérebro dos consumidores responde aos estímulos de marketing (Bos;Pizzato;Zaro, 2019).…”

“…Royo-Vela; Varga (2022) informam que na década de 1930 foi criado o primeiro medidor de rastreamento óptico não invasivo. A atenção visual humana pode ser detectada por meio dos movimentos oculares, uma informação fundamental para pesquisas em Neuromarketing e psicologia, pois permite avaliar com precisão as respostas aos estímulos visuais, como publicidade, produtos, embalagens e interfaces de usuário (Savur;Sahin, 2023).…”

A Review on Human-Robot Interaction and User Experience in Smart Robotic Wheelchairs

“…Gesture recognition interfaces are an emerging technology in the field of human-robot interaction (HRI) for smart robotic wheelchairs. These interfaces allow users to control and interact with the wheelchair through natural hand and body movements, offering an intuitive and accessible means of operation (Savur and Sahin, 2023). Gesture recognition interfaces utilize computer vision and machine learning techniques to interpret and understand user gestures, enabling the wheelchair to respond accordingly.…”