| EPSRC Reference: |
EP/X034690/1 |
| Title: |
SNOW: Wearable Nano-Opto-electro-mechanic Systems |
| Principal Investigator: |
Heidari, Professor H |
| Other Investigators: |
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| Project Partners: |
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| Department: |
School of Engineering |
| Organisation: |
University of Glasgow |
| Scheme: |
Standard Research - NR1 |
| Starts: |
01 May 2023 |
Ends: |
30 April 2026 |
Value (£): |
246,179
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| EPSRC Research Topic Classifications: |
| Optoelect. Devices & Circuits |
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Summary on Grant Application Form |
Health and fitness wearables present mobile solutions for ICT in public wellbeing by providing personal remote control and clinical intervention through telemedicine networks. Due to their noninvasive and continuous vital sign monitoring, wearables are incorporated in several studies to identify the onset and progression of the Coronavirus pandemic, and institutions deployed patient surveillance networks based on them. However, today's consumer wearables rely on sensing technologies vulnerable to motion artifacts due to discontinuous skin contact or insufficient motion artefact reduction mechanisms that prevent them from being a reliable source of vital signs.
The SNOW project specifically aims to heterogeneously integrate the best options of different disciplines to offer a complete ICT solution based on a Nano-Opto-Electro-Mechanical system (NOEMS) that is mechanically flexible and energy-efficient. The combination of optical and mechano-acoustic sensors into a single platform and consequent manipulation of the light signal via mechanical input and integrated electronics offers accurate heart rate and respiration rate extractions. With the combination of material and flexible-electronics-based technologies, our project aims to provide a wearable solution for ICT to contribute to a decent level of personal and public health. By benefiting from the proven expertise of the interdisciplinary consortium, here we propose to realize the next-generation wearable devices that can continuously monitor and provide instant feedback on the user's personal health parameters.
Our hybrid approach provides artefact compensation by using the heart rate signal from both optical and mechano-acoustic sensors. Integrating these sensors into a neuromorphic processor yields strict control on the actively extracted data and creates instant feedback in the case of abnormalities. The energy and data communication requirement of the proposed mobile sensing unit will be realized by a specific wireless communication that provides an efficient capacitive coupling to operate the sensors and circuitry components bypassing the need for an additional battery and bulky readout systems. Capacitive coupling with a smartwatch module will also provide transmission of the processed signal back to the final smart devices such as smartphone, laptops, and the smartwatch itself. The final system integration work package will employ a heterogenous integration methodology to pack these technologies in a wearable device form factor suitable for user experience and validation. Systematic validation of the final wearable device prototypes will be provided to reach reliable device deployment. Active user experience will be investigated to improve design aspects and the measurement methodologies.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.gla.ac.uk |