Title
A multi-modal architecture for non-intrusive analysis of performance in the workplace.
Abstract
Human performance, in all its different dimensions, is a very complex and interesting topic. In this paper we focus on performance in the workplace which, asides from complex is often controversial. While organizations and generally competitive working conditions push workers into increasing performance demands, this does not necessarily correlates positively to productivity. Moreover, existing performance monitoring approaches (electronic or not) are often dreaded by workers since they either threat their privacy or are based on productivity measures, with specific side effects. We present a new approach for the problem of performance monitoring that is not based on productivity measures but on the workers' movements while sitting and on the performance of their interaction with the machine. We show that these features correlate with mental fatigue and provide a distributed architecture for the non-intrusive and transparent collection of this data. The easiness in deploying this architecture, its non-intrusive nature, the potential advantages for better human resources management and the fact that it is not based on productivity measures will, in our belief, increase the willingness of both organizations and workers to implement this kind of performance management initiatives.
Year
DOI
Venue
2017
10.1016/j.neucom.2016.05.105
Neurocomputing
Keywords
Field
DocType
Performance,Monitoring,Neural network,Non-intrusive
Architecture,Human resource management,Mental fatigue,Performance monitoring,Computer science,Knowledge management,Performance management,Modal
Journal
Volume
Issue
ISSN
231
C
0925-2312
Citations 
PageRank 
References 
1
0.37
6
Authors
4
Name
Order
Citations
PageRank
Davide Carneiro123632.47
André Pimenta2417.77
José Neves393.01
Paulo Novais4883171.45