10 Guidelines for ASP

trix [524] (see also Chapter 7).

Each of these approaches enables processing of multi-modal data, which allows researchers to incorporate a range of characteristics (e.g., context, personality, and signals possible to record) [464]. This makes them promising for ASP applications, even outside the scope of user identification.

10.4 Conclusion

The signal processing guidelines taken together: physical sensing characteristics, temporal aspects, normalization, and context, all need to be taken into account when processing affective signals. Subsequently, the affective signals need to be classified using pattern recognition techniques. For this phase, the guidelines validation, triangulation, and user identification should be taken into account.

The guidelines presented in this chapter were derived from the author’s research conducted on ASP. Part of this research can be found in this monograph. Careful processing of all issues mentioned in the guidelines should always be warranted as they provide the input for the core of the closed loop model that forms the core of emotion-aware systems (see Figure 1.1). As such, I hope that this concise set of directives will aid future research in affective computing. With the next chapter, I will close this monograph.

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