Wearable Healthcare System
Early Detection of Cardiovascular Diseases Using Wearable Ultrasound Device
Published in IEEE Consumer Electronics Magazine, 2019. Recipient of best poster award in HOST 2017.
Overview: Early detection of symptoms is considered an effective approach to prevent deaths due to cardiovascular disease (CVD). Routine cardiac check-ups are therefore suggested by clinicians to detect CVD at an early stage. Unfortunately, existing methods for cardiac diagnosis are costly and time-consuming as in most of the cases, these facilities are available only in hospitals or clinics. In this article, a novel wearable ultrasonic imaging assembly is proposed for routine monitoring of the carotid arteries in an easy-to-use and economical way. Using standard B-mode ultrasound, which is suitable for wearable form factors, the device monitors intima–media thickness (IMT), which is a proven indicator of cardiovascular disease. The design parameters for all the essential hardware components of the proposed wearable imaging system along with an efficient algorithm for predicting IMT anomalies from ultrasound images are proposed. Finally, we describe a custom-designed prototype of the proposed system and demonstrate its capability in acquiring ultrasound images.
Fig: Placement of the ultrasound assembly: (a) nozzle placement while releasing ultrasound gel, and (b) transducer array placement at strategic locations during diagnosis. (c) Rear of the device showing the locations of transmit and receive circuitry and the power module. (d) Three variants of the detection framework, in which the built-in image-acquisition module sends the image for CVD detection to a local or external (mobile/cloud) image-analysis module.
According to the figure, the proposed device is worn like a neck brace (see Fig. a, b, c). The bench top setup is shown in Fig. d which denotes the individual components enclosed in the neck brace. Once the brace is worn by a user, the image of carotid artery is taken and sent to the cloud for checking the health of the artery. With the proposed automatic anomaly detection algorithm (comprising of several image processing techniques), the presence/absence of plaque is determined and the decision is sent to the user.