SMART launches project researching wearable ultrasound system for elderly care | Healthcare Asia Magazine
, Singapore
Prototype of Device via SMART

SMART launches project researching wearable ultrasound system for elderly care

MIT, Singapore partners project invests millions on groundbreaking health tech innovation

Singapore-MIT Alliance for Research and Technology (SMART) launched a new research centre to develop the world's first wearable ultrasound imaging system for real-time monitoring of chronic conditions.

The Wearable Imaging for Transforming Elderly Care (WITEC) collaborative research project aims to develop the world’s first wearable ultrasound imaging system for real-time monitoring and personalised diagnosis of conditions such as hypertension and heart failure.

WITEC will provide continuous, real-time imaging, which allows doctors to detect early deterioration, personalise treatment, reduce hospitalisations, and improve long-term care for elderly patients.

The initiative brings together researchers from the Massachusetts Institute of Technology, Nanyang Technological University and the National University of Singapore, with Tan Tock Seng Hospital as its clinical collaborator.

To support this work, WITEC’s laboratory is equipped with tools, including Southeast Asia’s first Nanoscribe Quantum X sub-micrometre 3D printer and the latest Verasonics Vantage NXT 256 ultrasonic imaging system, which is the first unit of its kind in Singapore.

Unlike conventional 3D printers that operate at millimetre or micrometre scales, WITEC’s 3D printer can achieve sub‑micrometre resolution, allowing components to be made at the level of single cells or tissue structures.

With this capability, WITEC researchers can prototype bioadhesive materials and device interfaces with unprecedented accuracy.

Adding to this is the Verasonics ultrasonic imaging system, which gives researchers the freedom to test highly customised imaging methods.

This allows more complex beamforming, higher‑resolution image capture, and integration with AI‑based diagnostic models.

 

 

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