**8. Conclusions**

Research on mobile and wearable technologies that track behavioral, psychological, and contextual signals has recently gained momentum in the field of mental health. At the same time, the rise of personal sensing has garnered the interest of HCI research. In this paper, we approached the design of sensing-actuation experiences intended for rich embodied interactions with relevance to affective health. To achieve this, we adopted first-person soma design to integrate biosignals that are commonly used in ubiquitous low-cost personal sensing together with actuation mechanisms studied in HCI. Our design exploration, giving special attention to the sentient body and acknowledging alternative ways to address affect within interaction, culminated with a set of coupling examples, in which we demonstrate data mapping strategies between various devices in the context of bodily and emotion awareness. The soma design approach applied to the creation of biosensing-actuation couplings for affective and self-awareness experiences is the main contribution of this paper. Through the couplings, we arrived at the concept of orchestration, defining the ways in which body input-output systems and meanings are put in place, the range of mappings and how they unfold. Soma design is a theoretically robust design approach that helps us sketch experiences to develop a (not necessarily dialogue-oriented) toolkit to facilitate creating affective technologies grounded on the body and enhanced by biosignals that are made available as design material. As a design toolkit, the examples created so far are instances of a wider collection of tools. The findings of our design explorations have unveiled a set of research directions (or requirements) to pursue in order to achieve broader orchestration mechanisms:


This insight aims to inspire developments in affective technologies and invites the joint work of engineering, interaction design, or even clinical disciplines that are traditionally disconnected from one another. Moreover, our discussion points at current limitations and paves the way for future research. We indicate sensing-actuation modalities that have been underexplored, then we consider the potential benefits of integrating refined machine learning algorithms and (developing) new orchestration interfaces to assist and democratize the crafting and customization process. As somatic perspectives are becoming more incorporated in areas of interaction design (research) and embraced with rigor, we foresee valuable intersections in other research domains.

**Author Contributions:** Authors H.G. and M.A. conceptualized and framed the paper; M.A., W.P. and N.C. curated the description of biosignals; M.U., W.P., C.W., P.K. and P.S. carried out the research on actuation mechanisms; C.W., P.K., P.S., M.U. and M.A. presented the results on first-person design combining the reported technologies; C.W., P.K., N.C., D.B. and M.A. carried out the discussion on further directions, orchestration and

ethical underpinnings of the current multidisciplinary research; H.G., C.E., C.S. and K.H. reviewed and supervised the paper; All authors contributed to the original draft preparation and subsequent editing. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work has been supported by Marie Skłodowska Curie Actions ITN AffecTech (ERC H2020 Project ID: 722022).

**Acknowledgments:** Authors would like to thank the whole AffecTech consortium for valuable scientific discussion and in particular researcher A.Patanè on the potential use of Deep Learning techniques. This paper would not have been possible without the useful criticism and input received from the design session's participants.

**Conflicts of Interest:** Authors M.A. and W.P are employed by PLUX Wireless Biosignals, a company manufacturing biosensensing devices. The rest of the authors declare no conflict of interest.
