Eddie NG Yin-Kwee, PhD, FEASA, FASME, FIETI, FIET, DFIDSAI, NTU; Bi Renzhe, PhD; Huang Weiting, MBBS, MRCP, MMeEd, MCI, NHCS; Ee Ying Hui Dina, MBBS, MRCP, NUHS; Ken Lee, PhD, NTU; Mark Wong Kei Fong, B.Eng., NTU; Suchitra Kataria, MD, MBBS; Tan Hong Chang, MBBS, MRCP, MMed, MCI, SGH
Competition Sponsor: Ministry of Health and National Research Foundation of Singapore
Awardee year: 2021
Sensors in modern smartwatches and fitness trackers can measure resting heartrate, which has proven to be an important indicator of cardiovascular health Unfortunately, the absence of sufficient computational power to analyze biosignal waveforms in situ on a wearable prevents the full potential of wearables to be realized for clinical applications. Today, 25% of adults suffer from hypertension and associated secondary pathologies, and by 2050, Singapore projects that there will be 1 million sufferers of diabetes, accounting for 10% of the disease burden in Singapore. This problem is especially pertinent in our aging population. Unfortunately, today’s blood pressure and blood glucose meters are obtrusive and inconvenient, leading to poor compliance and resurgence of the disease in chronic sufferers. In previous work, we have accomplished Blood Pressure (BP) and Blood Glucose Level (BGL) estimation without the compressing the arm or blood sampling with a novel sensor and signal computing method. Although our technology provides good assessment of BP and BGL changes, this novel modality has not yet been validated on everyday individual lifestyles and the goal of this proposal is to enhance our existing technology for everyday use.