RF-ECG

As an important indicator of autonomic regulation for circulatory function, Heart Rate Variability (HRV) is widely used for general health evaluation. Apart from using dedicated devices (e.g, ECG) in a wired manner, current methods search for a ubiquitous manner by either using wearable devices, which suffer from low accuracy and limited battery life, or applying wireless techniques (e.g., FMCW), which usually utilize dedicated devices (e.g., USRP) for the measurement. To address these issues, we present RF-ECG based on Commercial-Off-The-Shelf (COTS) RFID, a wireless approach to sense the human heartbeat through an RFID tag array attached on the chest area in the clothes. In particular, as the RFID reader continuously interrogates the tag array, two main effects are captured by the tag array: the reflection effect representing the RF-signal reflected from the heart movement due to heartbeat; the moving effect representing the tag movement caused by chest movement due to respiration. To extract the reflection signal from the noisy RF-signals, we develop a mechanism to capture the RF-signal variation of the tag array caused by the moving effect, aiming to eliminate the signals related to respiration. To estimate the HRV from the reflection signal, we propose a signal reflection model to depict the relationship between the RF-signal variation from the tag array and the reflection effect associated with the heartbeat. A fusing technique is developed to combine multiple reflection signals from the tag array for accurate estimation of HRV. Experiments with 15 volunteers show that RF-ECG can achieve a median error of 3% of Inter-Beat Interval (IBI), which is comparable to existing wired techniques.

[1]  Paul Tseng,et al.  Robust wavelet denoising , 2001, IEEE Trans. Signal Process..

[2]  D. Dobkin The RF in RFID : UHF RFID in Practice Ed. 2 , 2012 .

[3]  Shaojie Tang,et al.  Contactless Respiration Monitoring Via Off-the-Shelf WiFi Devices , 2016, IEEE Transactions on Mobile Computing.

[4]  Xinyu Zhang,et al.  Continuous and fine-grained breathing volume monitoring from afar using wireless signals , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[5]  Wei Xi,et al.  Device-free detection of approach and departure behaviors using backscatter communication , 2016, UbiComp.

[6]  Lei Yang,et al.  Tagoram: real-time tracking of mobile RFID tags to high precision using COTS devices , 2014, MobiCom.

[7]  Min Chen,et al.  Tag-compass: Determining the spatial direction of an object with small dimensions , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.

[8]  W. Zareba,et al.  Heart rate variability. , 2013, Handbook of clinical neurology.

[9]  Peyman Servati,et al.  A Blind Source Separation Framework for Monitoring Heart Beat Rate Using Nanofiber-Based Strain Sensors , 2016, IEEE Sensors Journal.

[10]  Yuxiang Zhang,et al.  Battery-free RFID heart rate monitoring system , 2016, 2016 IEEE Wireless Health (WH).

[11]  L. Gallo Cardiovascular Disease , 1995, GWUMC Department of Biochemistry Annual Spring Symposia.

[12]  Anand Sivasubramaniam,et al.  HB-Phone: A Bed-Mounted Geophone-Based Heartbeat Monitoring System , 2017, 2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

[13]  Longfei Shangguan,et al.  Leveraging Electromagnetic Polarization in a Two-Antenna Whiteboard in the Air , 2016, CoNEXT.

[14]  Xia Wang,et al.  RF-scanner: Shelf scanning with robot-assisted RFID systems , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.

[15]  Xinyu Zhang,et al.  Gyro in the air: tracking 3D orientation of batteryless internet-of-things , 2016, MobiCom.

[16]  Lei Yang,et al.  See Through Walls with COTS RFID System! , 2015, MobiCom.

[17]  Sachin Katti,et al.  WiDeo: Fine-grained Device-free Motion Tracing using RF Backscatter , 2015, NSDI.

[18]  Haruki Kawanaka,et al.  Estimating heart rate using wrist-type Photoplethysmography and acceleration sensor while running , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[19]  Fadel Adib,et al.  Emotion recognition using wireless signals , 2018, Commun. ACM.

[20]  Mo Li,et al.  Precise Power Delay Profiling with Commodity Wi-Fi , 2015, IEEE Transactions on Mobile Computing.

[21]  Liliana Ferreira,et al.  Using the smartphone camera to monitor heart rate and rhythm in heart failure patients , 2014, IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI).

[22]  O. Boric-Lubecke,et al.  Signal-to-Noise Ratio in Doppler Radar System for Heart and Respiratory Rate Measurements , 2009, IEEE Transactions on Microwave Theory and Techniques.

[23]  Martina Mueller,et al.  Research Article Development and Validation of a Smartphone Heart Rate Acquisition Application for Health Promotion and Wellness Telehealth Applications , 2011 .

[24]  Jue Wang,et al.  RF-IDraw: virtual touch screen in the air using RF signals , 2015, SIGCOMM 2015.

[25]  Wei Xi,et al.  FEMO: A Platform for Free-weight Exercise Monitoring with RFIDs , 2015, SenSys.

[26]  Fadel Adib,et al.  Multi-Person Motion Tracking via RF Body Reflections , 2014 .

[27]  Alper Bozkurt,et al.  Wearable Heart Rate Sensor Systems for Wireless Canine Health Monitoring , 2016, IEEE Sensors Journal.

[28]  K. Banitsas,et al.  A novel method to detect Heart Beat Rate using a mobile phone , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[29]  Yong Gyu Lim,et al.  REM Sleep Classification with Respiration Rates , 2007, 2007 6th International Special Topic Conference on Information Technology Applications in Biomedicine.

[30]  O. Boric-Lubecke,et al.  Assessment of Heart Rate Variability and Respiratory Sinus Arrhythmia via Doppler Radar , 2009, IEEE Transactions on Microwave Theory and Techniques.

[31]  Rob Miller,et al.  Smart Homes that Monitor Breathing and Heart Rate , 2015, CHI.

[32]  José María Sierra,et al.  A light-weight authentication scheme for wireless sensor networks , 2011, Ad Hoc Networks.

[33]  Dan Wu,et al.  Human respiration detection with commodity wifi devices: do user location and body orientation matter? , 2016, UbiComp.

[34]  Fadel Adib,et al.  Multi-Person Localization via RF Body Reflections , 2015, NSDI.

[35]  Xu Chen,et al.  Tracking Vital Signs During Sleep Leveraging Off-the-shelf WiFi , 2015, MobiHoc.