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Document VersionPublisher's PDF, also known as Version of Record (includes final page, issue and volume numbers)Please check the document version of this publication:• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Abstract-Inertial and magnetic sensors offers a sourceless and mobile option to obtain body posture and motion for personal sports or healthcare assistants, if sensors could be unobtrusively integrated in casual garments and accessories. We present in this paper design, implementation, and evaluation results for a novel miniature attitude and heading reference system (AHRS) named ETHOS using current off-the-shelf technologies.ETHOS has a unit size of 2.5cm 3 , which is substantially below most currently marketed attitude heading reference systems, while the unit contains processing resources to estimate its orientation online. Results on power consumption in relation to sampling frequency and sensor use are presented. Moreover two sensor fusion algorithms to estimate orientation: a quaternionbased Kalman-, and a complementary filter. Evaluations of orientation estimation accuracy in static and dynamic conditions revealed that complementary filtering reached sufficient accuracy while consuming 46% of a Kalman's power. The system runtime of ETHOS was found to be 10 hours at a complementary filter update rate of 128Hz. Furthermore, we found that a ETHOS prototype functioned with a sufficient accuracy in estimating human movement in real-life conditions using an arm rehabilitation robot.

In this work, we introduce methods for studying psychological arousal in naturalistic daily living. We present an activityaware arousal phase modeling approach that incorporates the additional heart rate (AHR) algorithm to estimate arousal onsets (activations) in the presence of physical activity (PA). In particular, our method filters spurious PA-induced activations from AHR activations, e.g., caused by changes in body posture, using activity primitive patterns and their distributions. Furthermore, our approach includes algorithms for estimating arousal duration and intensity, which are key to arousal assessment. We analyzed the modeling procedure in a participant study with 180 h of unconstrained daily life recordings using a multimodal wearable system comprising two acceleration sensors, a heart rate monitor, and a belt computer. We show how participants' sensor-based arousal phase estimations can be evaluated in relation to daily activity and self-report information. For example, participant-specific arousal was frequently estimated during conversations and yielded highest intensities during office work. We believe that our activity-aware arousal modeling can be used to investigate personal arousal characteristics and introduce novel options for studying human behavior in daily living.

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