Monitoring of the physical properties of the tissues provides valuable information for the clinical diagnosis and evaluation. However, one of the challenges of an ultrasonic method for continuous monitoring of a tissue motion using a conventional clinical ultrasonic image system could be motion artifacts due to the weight and size of its handheld ultrasonic probe employed. A wearable ultrasonic sensor, made of a polyvinylidene fluoride (PVDF) polymer piezoelectric film, may be able to reduce the motion artifacts due to its lightweight and flexible properties. However, the PVDF ultrasonic sensor has a relatively weak transmitting acoustic signal strength which causes poor signal-to-noise ratio of the ultrasonic signal acquired in pulse-echo measurements, particularly for the signal reflected from deeper tissue. This paper investigated an improvement of the ultrasonic performance of the WUS using double-layer PVDF films. The sensor was constructed using two 52-μm thick PVDF films. The developed double-layer WUS showed the 1.7 times greater ultrasonic signal amplitude compared to the WUS made of a single-layer PVDF having the equivalent PVDF film thickness. Thus, the developed double-layer PVDF WUS improved the depth of the ultrasonic penetration into the tissue. The developed WUS successfully demonstrated to monitor the contractions of biceps muscles in an upper arm. In addition, a cardiac tissue motion was clearly observed in the M-mode measurement corresponding with the cardiac cycles obtained from the ECG measurement.

Additional Metadata
Keywords Cardiac monitoring, Double-layer PVDF films, Skeletal muscle monitoring, Tissue motion, Wearable and flexible ultrasonic sensor
Persistent URL dx.doi.org/10.1109/CCECE.2018.8447859
Conference 2018 IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2018
Citation
Almohimeed, I. (Ibrahim), Agarwal, M. (Manas), & Ono, Y. (2018). Wearable Ultrasonic Sensor Using Double-Layer PVDF Films for Monitoring Tissue Motion. In Canadian Conference on Electrical and Computer Engineering. doi:10.1109/CCECE.2018.8447859