3D-printed bioinspired microsensors for biomedical flow sensing applications

Kamat, A. & Kottapalli, A. G. P., 30-Sep-2019.

Research output: Contribution to conferencePosterProfessional

The recent trends of personalized healthcare, autonomous sensor networks, digital technology, and the Internet of Things (IoT) have made microsensors essential to the healthcare industry. For example, accurate flow sensing is a key requirement in many biomedical applications including infusion pumps, insulin pumps, respiratory monitoring, and urine flow monitoring. This can enable continuous monitoring of vital patient signs, medicinal flow rate verification to avoid potential adverse drug events (ADEs), reduction in nurse workload through automated flow rate measurements, prediction of device malfunctions, and so on, paving the path towards ‘smart wards’ in hospitals powered by digital technology. Current methods of flow microsensor manufacturing involve standard microelectromechanical systems (MEMS) ‘cleanroom’ fabrication techniques which are expensive, tedious, and restricted to a limited number of materials, resulting in microsensors that are often prohibitively expensive for medical applications. To solve this problem, we propose the use of high-resolution 3D printing, soft lithography, and the use of piezoresistive nanomaterials to develop biomimetic flow microsensors inspired by the ultrasensitive ‘hair-like’ neuromast flow sensors found in the blind cave fish lateral line. Using designs compatible with high-volume manufacturing methods such as injection molding, our idea can thus be used to develop sensitive, low-cost (< €1), and disposable microsensors geared towards flow sensing applications in the healthcare industry.
Original languageEnglish
Publication statusPublished - 30-Sep-2019
EventUG Meet&Greet XL: Digital Society - Groningen, Netherlands
Duration: 30-Sep-2019 → …


OtherUG Meet&Greet XL: Digital Society
Period30/09/2019 → …


UG Meet&Greet XL: Digital Society

30/09/2019 → …

Groningen, Netherlands

Event: Other


  • biomedical applications, Flow Sensor, 3D printing

View graph of relations

ID: 99452609