In this paper we introduce two new methods for real-time sonification of head movements and head gestures. Head gestures such as nodding or shaking the head are important non-verbal back-channelling signals which facilitate coordination and alignment of communicating interaction partners. Visually impaired persons cannot interpret such non-verbal signals, same as people in mediated communication (e.g. on the phone), or cooperating users whose visual attention is focused elsewhere. We introduce our approach to tackle these issues, our sensing setup and two di↵erent sonification methods. A first preliminary study on the recognition of signals shows that subjects understand the gesture type even without prior explanation and can estimate gesture intensity and frequency with no or little training.

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Intra-hemispheric interference has been often observed when body parts with neighboring representations within the same hemisphere are stimulated. However, patterns of interference in early and late somatosensory processing stages due to the stimulation of different body parts have not been explored. Here, we explore functional similarities and differences between attention modulation of the somatosensory N140 and P300 elicited at the fingers vs. cheeks. In an active oddball paradigm, 22 participants received vibrotactile intensity deviant stimulation either ipsilateral (within-hemisphere) or contralateral (between-hemisphere) at the fingers or cheeks. The ipsilateral deviant always covered a larger area of skin than the contralateral deviant. Overall, both N140 and P300 amplitudes were higher following stimulation at the cheek and N140 topographies differed between fingers and cheek stimulation. For the N140, results showed higher deviant ERP amplitudes following contralateral than ipsilateral stimulation, regardless of the stimulated body part. N140 peak latency differed between stimulated body parts with shorter latencies for the stimulation at the fingers. Regarding P300 amplitudes, contralateral deviant stimulation at the fingers replicated the N140 pattern, showing higher responses and shorter latencies than ipsilateral stimulation at the fingers. For the stimulation at the cheeks, ipsilateral deviants elicited higher P300 amplitudes and longer latencies than contralateral ones. These findings indicate that at the fingers ipsilateral deviant stimulation leads to intra-hemispheric interference, with significantly smaller ERP amplitudes than in contralateral stimulation, both at early and late processing stages. By contrast, at the cheeks, intra-hemispheric interference is selective for early processing stages. Therefore, the mechanisms of intra-hemispheric processing differ from inter-hemispheric ones and the pattern of intra-hemispheric interference in early and late processing stages is body-part specific.

Abstract:The concept of packet acknowledgement in wireless communication networks is crucial for reliable data transmission. However, reliability comes with the cost of an increased duty cycle of the network. This is due to the additional acknowledgement time for every single data packet sent. Therefore, energy consumption and latency of all sensor nodes is increased whilst the overall throughput in the network decreases. This paper contributes an adaptive acknowledgement on-demand protocol for wireless sensor networks with star network topology. The goal is to tackle the trade-off between energy efficiency and reliable data transmission. The proposed protocol is able to detect network congestion in real time by constantly monitoring the overall packet delivery ratio for each sensor node. In case the packet delivery ratio of any sensor nodes in the network is dropped significantly (e.g. due to environmental changes), the protocol switches automatically to a more reliable data transmission mode utilizing acknowledgements concerning the affected sensor nodes. Our proposed method is tested and evaluated based on a specific hardware implementation and the corresponding results are discussed in this paper.