Figure 1: To measure respiration with an in-ear headphone IMU, we capture 3D acceleration and gyroscope data at 50 Hz (A). We record the ground truth with a pressure transducer. Data is processed as illustrated in (B): we split the data into 20-second windows and interpolate using cubic splines, resampling at 256 Hz. Our pipeline discards windows with too much movement. We apply a Butterworth bandpass filter to remove noise and a triangle filter for further smoothening without loss of timing information. Finally, we use FFT with zero padding in (C) and compute the maximum to calculate the respiratory rate.
Earables have emerged as a unique platform for ubiquitous computing by augmenting ear-worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new research exploring what can be detected on a wearable, small form factor. As a sensing platform, the ears are less susceptible to motion artifacts and are located in close proximity to a number of important anatomical structures including the brain, blood vessels, and facial muscles which reveal a wealth of information. They can be easily reached by the hands and the ear canal itself is affected by mouth, face, and head movements. We have conducted a systematic literature review of 271 earable publications from the ACM and IEEE libraries. These were synthesized into an open-ended taxonomy of 47 different phenomena that can be sensed in, on, or around the ear. Through analysis, we identify 13 fundamental phenomena from which all other phenomena can be derived, and discuss the different sensors and sensing principles used to detect them. We comprehensively review the phenomena in four main areas of (i) physiological monitoring and health, (ii) movement and activity, (iii) interaction, and (iv) authentication and identification. This breadth highlights the potential that earables have to offer as a ubiquitous, general-purpose platform.
Creating a public understanding of the dynamics of a pandemic, such as COVID-19, is vital for introducing restrictive regulations. Gathering diverse data responsibly and sharing it with experts and citizens in a timely manner is challenging. This article reviews methodologies of COVID-19 dashboard design and discusses both technical and non-technical challenges associated. Advice and lessons learned from building a citizen-focused, automated county-precision dashboard for Germany are shared. Within four months, the web-based tool had 5 million unique visitors and 70 million sessions. Three developers set up the basic version in less than one week. Early on, data was screen scraped. An iterative process improved timeliness by adding more fine-grained data sources. A collaborative online table editor enabled near real-time corrections. Alerting was setup for errors, and statistics apply for sanity checking. Static site generation and a content delivery network help to serve large user loads in a timely manner. The flexible design allowed to iteratively integrate more complex statistics based on expert knowledge built on top of the collected data and secondary data sources such as ICU beds and citizen movement. CCS Concepts: • Software and its engineering → Software prototyping; • Computer systems organization → Data flow architectures; • Human-centered computing → Geographic visualization;
Figure 1: We present EarRumble, a technique that uses "ear rumbling" for interaction. (a) The tensor tympani muscle can be contracted voluntarily which displaces the eardrum and induces a pressure change within the sealed ear canal; (b) Custombuilt earables detect ear rumbling using an in-ear pressure sensor; (c) Eyes-and hands-free discreet input can be provided by performing diferent rumbling gestures by voluntarily contracting the tensor tympani muscle.
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