Physiological Parameter Sensing with Wearable Devices and Non Contact Doppler RadarDate: 2017-04-20 Add to Google Calendar
Location: Holmes Hall 389
Speaker: Alexander Lee, EE MS Candidate
Vital sign measurement with wearable devices is an important need in the paradigm shift occurring with health care. The Internet of things (IoT) is a concept that will allow healthcare providers to keep up to date continuously on the health of their patients through accurate wearable sensors and non-contact sensing in their homes. In order to meet this growing need for robust sensors, there are currently many devices that sense physiological parameters through photo-plethysmography (PPG) and piezoelectric methods. These methods of sensing have their own inherent limitations which include low flexibility, inaccuracy at higher rates, and susceptibility to motion artifact. Elastomeric sensors are another material being explored because of its potential for higher flexibility than piezoelectric pressure sensors. A wearable elastomeric arm sensor, that was designed and tested on the upper arm of 3 subjects, showed capability of measuring respiratory and heart rate with a low voltage DC power source.
In addition to wearable sensors, there is a need for non-contact sensing in home health monitoring. Previous research with Doppler radar physiological sensing has focused mostly on measuring respiratory rate and displacement accurately. Recent work with radar cross-section (RCS) measurements, have shown that it is possible to determine body position of a subject based on the RCS. A study was done to investigate the dynamic RCS of a human subject during varying respiration depth. Measurement with a retro-reflective infrared camera marker on the sternum of the subject was used as a reference and compared with a 2.4GHz continuous wave Doppler radar system. Results showed that the RCS of a subject facing the radar changed between deep and shallow breathing. A further study with 13 reference markers revealed that there were two main areas, sternum and abdomen, that contributed to the overall dynamic RCS. The implications of this study are important for accurately determining subject position, medical diagnosis, and unique identification with Doppler radar.