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|| Lux, E.; Adam, M.; Dorner, V.; Helming, S.; Knierim, M. & Weinhardt, C. (2018), "Live Biofeedback as a User Interface Design Element: A Review of the Literature", Communications of the Association for Information Systems, pp. 257-296. 10.17705/1CAIS.04318
With the advances in sensor technology and real-time processing of neurophysiological data, a growing body of
academic literature has begun to explore how live biofeedback can be integrated into information systems for
everyday use. While researchers have traditionally studied live biofeedback in the clinical domain, the proliferation of
affordable mobile sensor technology enables researchers and practitioners to consider live biofeedback as a user
interface element in contexts such as decision support, education, and gaming. In order to establish the current state
of research on live biofeedback, we conducted a literature review on studies that examine self and foreign live
biofeedback based on neurophysiological data for healthy subjects in an information systems context. By integrating a
body of highly fragmented work from computer science, engineering and technology, information systems, medical
science, and psychology, this paper synthesizes results from existing research, identifies knowledge gaps, and
suggests directions for future research. In this vein, this review can serve as a reference guide for researchers and
practitioners on how to integrate self and foreign live biofeedback into information systems for everyday use.
| [ 2 ]
|| Buergin, J.; Helming, S.; Blaettchen, P.; Schweizer, Y.; Bitte, F.; Haefner, B. & Lanza, G. (2018), "Local order scheduling for mixed-model assembly lines in the aircraft manufacturing industry", Production Engineering Research and Development, pp. 1-9.
Multi-variant products to be assembled on mixed-model assembly lines at locations within a production network need to be
scheduled locally. Scheduling is a highly complex task especially if it simultaneously covers the assignment of orders, which
are product variants to be assembled within a production period, to assembly lines as well as their sequencing on the lines.
However, this is required if workers can flexibly fulfill tasks across stations of several lines and, thus, capacity of workers is
shared among the lines. As this is the case for final assembly of the Airbus A320 Family, this paper introduces an optimization
model for local order scheduling for mixed-model assembly lines covering both assignment to lines as well as sequencing.
The model integrates the planning approaches mixed-model sequencing and level scheduling in order to minimize work
overload in final assembly and to level material demand with regard to suppliers. The presented model is validated in the
industrial application of the final assembly of the Airbus A320 Family. The results demonstrate significant improvement in
terms of less work overload and a more even material demand compared to current planning.