Human cognitive and motor abilities in the aging workforce: An information-based model

Salvatore Digiesi, Daniela Cavallo, Andrea Lucchese, Carlotta Mummolo

Research output: Contribution to journalArticlepeer-review

Abstract

In the digital society, individuals are in charge of performing tasks based on the information gathered by huge amount of data and effectively use them to manifest their cognitive and motor abilities. In this paper, on the basis of experimental studies available in literature concerning lab tests on motor or cognitive abilities of differently aged subjects, an information-based theoretical model is proposed. The model allows to quantify the information content of a motor or a cognitive task and provides estimates of information processing time of individuals of different age and sex in accomplishing tasks with prevalent motor or cognitive nature, in spite of the fact that a "pure" cognitive or a "pure" motor task are rarely observed in practical cases. The model is then applied to a case study from automotive industry in which workforce aging phenomenon is experienced. Potential applications of the model go beyond the case study developed. Quantifying the information content of a general motor-cognitive task paves the way to new understanding and modelling of movements and performance time of both natural and artificial systems with applications in industrial robotics (e.g., human-robot cooperation), biomechanics, and neurorehabilitation.

Original languageEnglish (US)
Article number5958
JournalApplied Sciences (Switzerland)
Volume10
Issue number17
DOIs
StatePublished - Sep 2020

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

Keywords

  • Aging
  • Cognitive-motor tasks
  • Human processing time
  • Shannon entropy

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