On-body sensing technologies and signal processing techniques in addressing safety of human machine collaboration

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Publicat a:Human-Intelligent Systems Integration vol. 6, no. 1 (Dec 2024), p. 103
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Springer Nature B.V.
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022 |a 2524-4876 
022 |a 2524-4884 
024 7 |a 10.1007/s42454-024-00057-5  |2 doi 
035 |a 3157769939 
045 2 |b d20241201  |b d20241231 
245 1 |a On-body sensing technologies and signal processing techniques in addressing safety of human machine collaboration 
260 |b Springer Nature B.V.  |c Dec 2024 
513 |a Journal Article 
520 3 |a Safety is a challenge in human machine collaboration despite of the advantages in achieving efficiency, cost reduction and productivity in a collaborative scenario between human and machine/robot. During collaboration with machines, the user might not be able to follow the collaborative tasks as expected due to the cognitive burden causing potential safety concerns such as collision. Addressing this challenge, the aim of this paper is to explore the potential of on-body sensing systems in study of user experience and the psychological condition during the collaboration between machines and human. As the psychological condition is reflected in physiological signals, sensing technologies and signal processing techniques to extract features from physiological signals are explored with applicability in human machine collaboration scenarios. An experiment is designed utilising an industrial collaborative robot arm while quantitative and qualitative data is gathered for this purpose exploring the problem to study user experience and impact of mental strain and cognitive workload on user performance and experience during human machine collaboration. Results show that an adaptive machine to user experience measured by on-body sensing systems during the collaboration has the potential to address safety in human machine collaboration while improving performance and user experience. 
653 |a Physiology 
653 |a Collaboration 
653 |a User experience 
653 |a Blood vessels 
653 |a Electrodes 
653 |a Signal processing 
653 |a Human performance 
653 |a Laboratories 
653 |a Robots 
653 |a ISO standards 
653 |a Cognitive ability 
653 |a Electroencephalography 
653 |a Cardiovascular system 
653 |a Workloads 
653 |a Cognitive tasks 
653 |a Cognition & reasoning 
653 |a Asymmetry 
653 |a Qualitative analysis 
653 |a Adaptive systems 
653 |a Fourier transforms 
653 |a Robot arms 
653 |a Sensors 
653 |a Design 
653 |a Nervous system 
653 |a Information processing 
653 |a Spinal cord 
653 |a Human body 
773 0 |t Human-Intelligent Systems Integration  |g vol. 6, no. 1 (Dec 2024), p. 103 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
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856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3157769939/fulltext/embedded/75I98GEZK8WCJMPQ?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3157769939/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch