Hand–object interaction recognition based on visual attention using multiscopic cyber-physical-social system

(1) * Adnan Rachmat Anom Besari Mail (Politeknik Elektronika Negeri Surabaya (PENS), Indonesia, and Graduate School of Systems Design,Tokyo Metropolitan University, Japan)
(2) Azhar Aulia Saputra Mail (Graduate School of Systems Design, Tokyo Metropolitan University, Japan)
(3) Wei Hong Chin Mail (Graduate School of Systems Design, Tokyo Metropolitan University, Japan)
(4) Kurnianingsih Kurnianingsih Mail (Department of Electrical Engineering, Politeknik Negeri Semarang, Indonesia)
(5) Naoyuki Kubota Mail (Graduate School of Systems Design, Tokyo Metropolitan University, Japan)
*corresponding author

Abstract


Computer vision-based cyber-physical-social systems (CPSS) are predicted to be the future of independent hand rehabilitation. However, there is a link between hand function and cognition in the elderly that this technology has not adequately supported. To investigate this issue, this paper proposes a multiscopic CPSS framework by developing hand–object interaction (HOI) based on visual attention. First, we use egocentric vision to extract features from hand posture at the microscopic level. With 94.87% testing accuracy, we use three layers of graph neural network (GNN) based on hand skeletal features to categorize 16 grasp postures. Second, we use a mesoscopic active perception ability to validate the HOI with eye tracking in the task-specific reach-to-grasp cycle. With 90.75% testing accuracy, the distance between the fingertips and the center of an object is used as input to a multi-layer gated recurrent unit based on recurrent neural network architecture. Third, we incorporate visual attention into the cognitive ability for classifying multiple objects at the macroscopic level. In two scenarios with four activities, we use GNN with three convolutional layers to categorize some objects. The outcome demonstrates that the system can successfully separate objects based on related activities. Further research and development are expected to support the CPSS application in independent rehabilitation.

Keywords


Telemedicine; First-person vision; Hand-eye coordination; Independent rehabilitation; Occupational therapy

   

DOI

https://doi.org/10.26555/ijain.v9i2.901
      

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