Vital Signs Monitoring During Sleep
WiFi based Approach
This work based on acoustic signals captured from smartphone earphone aims to achieve the fine-grained non-invasive sleep monitoring at a minimal cost by exploiting the off-the-shelf smartphone and its earphone. The proposed system captures the breathing sound generated by the air flow for breathing rate detection. The airway flow is correlated with the amplitude of the respiratory sound during normal breathing. It is thus possible to monitor the breathing rate based on the extracting the breathing sound from the smartphone earphone as shown in Figure 2. Moreover, the benefit of using earphone is four-fold. First, the microphone on earphone has a higher recording quality than that of the smartphone built-in microphone, resulting in more reliable recorded breathing sound. Second, many users are resistant to place the smartphone close to them during sleep but tend to leave the earphone plugged into their ears or put it aside on their pillows during sleep. Third, the earbuds on earphone could be used as microphones, which helps to enhance the recording ability of the breathing sound. Fourth, using earphone can also capture other sleep related events easily such as snoring, coughing, turn-over and get up.
WiFi based Approach
Smart phone based Approach
The sleep monitoring using smartphone takes as input the recorded acoustic sound from the earphone. The sound can be further enhanced by using the input from the earbuds after connecting the earbuds with the output of the microphone by using off-the-shelf connecters. This system then performs noise estimation and subtraction to reduce the impact of background noise. The high correlation between a user’s breathing cycles is exploited to make the breathing rate detection method adaptive to different users. Finally, the acoustic features extracted from acoustic sound are used for sleep event (e.g., snoring, coughing, turn-over and get up) detection. By combining breathing rate and sleep events, the proposed system can provide continuous and noninvasive fine-grained sleep monitoring for healthcare related applications (such as sleep apnea monitoring).
Results To Date & Future Work Plan
journal paper in IEEE IOT. The project is reported by MIT Technology Review, Fierce Mobile Healthcare, Digital Journal and Yahoo News, etc. Figure 3 shows the breathing rate estimation performance using off-the-shelf WiFi with different distances between WiFi devices and AP. Figure 4 presents the sample results of using smartphone earphone to detect breathing rate during sleep.
Prof. Yingying Chen
yingying.chen (AT) rutgers (.) edu
Jian Liu, Yan Wang, Yingying Chen, Jie Yang, Xu Chen, Jerry Cheng. Tracking Vital Signs During Sleep Leveraging Off-the-shelf WiFi. In Proceedings of the 16th ACM Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc 2015), Hangzhou, China, June 2015.
Yanzhi Ren, Chen Wang, Jie Yang, Yingying Chen. Fine-grained Sleep Monitoring: Hearing Your Breathing with Smartphones. In Proceedings of the IEEE International Conference on Computer Communications (IEEE INFOCOM 2015), pp. 1194–1202, 2015.
Jian Liu, Yingying Chen, Yan Wang, Xu Chen, Jerry Cheng, Jie Yang. Monitoring Vital Signs and Postures During Sleep Using WiFi Signals, IEEE Internet of Things Journal (IEEE IoT). vol. 5, pp. 2071-2084, 2018.
Smartphone App to Prevent Life-threatening, Expensive Emergencies [Fierce Mobile Healthcare]
Smartphone soon to track sleep disorders [Yahoo News]
Your Smartphone Could Soon Listen for Sleep Disorders [MIT Technology Review]