No abstract

Respiration monitoring is helpful in disease prevention and diagnosis. Traditional respiration monitoring requires users to wear devices on their bodies, which is inconvenient for them. In this paper, we aim to design a noncontact respiration rate detection system utilizing off-the-shelf smartphones. We utilize the single-frequency ultrasound as the media to detect the respiration activity. By analyzing the ultrasound signals received by the built-in microphone sensor in a smartphone, our system can derive the respiration rate of the user. The advantage of our method is that the transmitted signal is easy to generate and the signal analysis is simple, which has lower power consumption and thus is suitable for long-term monitoring in daily life. The experimental result shows that our system can achieve accurate respiration rate estimation under various scenarios.

Accurate device motion tracking enables many applications like Virtual Reality (VR) and Augmented Reality (AR). To make these applications available in people's daily life, low-cost acoustic-based motion tracking methods are proposed. However, existing acoustic-based methods are all based on distance estimation. These methods measure the distance between a speaker and a microphone. With a speaker or microphone array, it can get multiple estimated distances and further achieve multidimensional motion tracking. The weakness of distance-based motion tracking methods is that they need large array size to get accurate results. Some systems even require an array larger than 1 m. This weakness limits the adoption of existing solutions in a single device like a smart speaker. To solve this problem, we propose Acoustic Strength-based Angle Tracking (ASAT) System and further implement a motion tracking system based on ASAT. ASAT achieves angle tracking by creating a periodically changing sound field. A device with a microphone will sense the periodically changing sound strength in the sound field. When the device moves, the period of received sound strength will change. Thus we can derive the angle change and achieve angle tracking. The ASAT-based system can obtain the localization accuracy as 5 cm when the distance between the speaker and the microphone is in the range of 3 m.

No abstract