A first step towards on-device monitoring of body sounds in the wild

Body sounds provide rich information about the state of the human body and can be useful in many medical applications. Auscultation, the practice of listening to body sounds, has been used for centuries in respiratory and cardiac medicine to diagnose or track disease progression. To date, however, its use has been confined to clinical and highly controlled settings. Our work addresses this limitation: we devise a chest-mounted wearable for continuous monitoring of body sounds, that leverages data processing algorithms that run on-device. We concentrate on the detection of heart sounds to perform heart rate monitoring. To improve robustness to ambient noise and motion artefacts, our device uses an algorithm that explicitly segments the collected audio into the phases of the cardiac cycle. Our pilot study with 9 users demonstrates that it is possible to obtain heart rate estimates that are competitive with commercial heart rate monitors, with low enough power consumption for continuous use.ER

Primate drum kit: A system for studying acoustic pattern production by non-human primates using acceleration and strain sensors

The possibility of achieving experimentally controlled, non-vocal acoustic production in non-human primates is a key step to enable the testing of a number of hypotheses on primate behavior and cognition. However, no device or solution is currently available, with the use of sensors in non-human animals being almost exclusively devoted to applications in food industry and animal surveillance. Specifically, no device exists which simultaneously allows: (i) spontaneous production of sound or music by non-human animals via object manipulation, (ii) systematical recording of data sensed from these movements, (iii) the possibility to alter the acoustic feedback properties of the object using remote control. We present two prototypes we developed for application with chimpanzees (Pan troglodytes) which, while fulfilling the aforementioned requirements, allow to arbitrarily associate sounds to physical object movements. The prototypes differ in sensing technology, costs, intended use and construction requirements. One prototype uses four piezoelectric elements embedded between layers of Plexiglas and foam. Strain data is sent to a computer running Python through an Arduino board. A second prototype consists in a modified Wii Remote contained in a gum toy. Acceleration data is sent via Bluetooth to a computer running Max/MSP. We successfully pilot tested the first device with a group of chimpanzees. We foresee using these devices for a range of cognitive experiments. © 2013 by the authors; licensee MDPI, Basel, Switzerland

Towards robust paralinguistic assessment for real-world mobile health (mHealth) monitoring: an initial study of reverberation effects on speech

Speech is promising as an objective, convenient tool to monitor health remotely over time using mobile devices. Numerous paralinguistic features have been demonstrated to contain salient information related to an individual's health. However, mobile device specification and acoustic environments vary widely, risking the reliability of the extracted features. In an initial step towards quantifying these effects, we report the variability of 13 exemplar paralinguistic features commonly reported in the speech-health literature and extracted from the speech of 42 healthy volunteers recorded consecutively in rooms with low and high reverberation with one budget and two higher-end smartphones, and a condenser microphone. Our results show reverberation has a clear effect on several features, in particular voice quality markers. They point to new research directions investigating how best to record and process in-the-wild speech for reliable longitudinal health state assessment

Integrating passive ubiquitous surfaces into human-computer interaction

Mobile technologies enable people to interact with computers ubiquitously. This dissertation investigates how ordinary, ubiquitous surfaces can be integrated into human-computer interaction to extend the interaction space beyond the edge of the display. It turns out that acoustic and tactile features generated during an interaction can be combined to identify input events, the user, and the surface. In addition, it is shown that a heterogeneous distribution of different surfaces is particularly suitable for realizing versatile interaction modalities. However, privacy concerns must be considered when selecting sensors, and context can be crucial in determining whether and what interaction to perform.Mobile Technologien ermöglichen den Menschen eine allgegenwärtige Interaktion mit Computern. Diese Dissertation untersucht, wie gewöhnliche, allgegenwärtige Oberflächen in die Mensch-Computer-Interaktion integriert werden können, um den Interaktionsraum über den Rand des Displays hinaus zu erweitern. Es stellt sich heraus, dass akustische und taktile Merkmale, die während einer Interaktion erzeugt werden, kombiniert werden können, um Eingabeereignisse, den Benutzer und die Oberfläche zu identifizieren. Darüber hinaus wird gezeigt, dass eine heterogene Verteilung verschiedener Oberflächen besonders geeignet ist, um vielfältige Interaktionsmodalitäten zu realisieren. Bei der Auswahl der Sensoren müssen jedoch Datenschutzaspekte berücksichtigt werden, und der Kontext kann entscheidend dafür sein, ob und welche Interaktion durchgeführt werden soll