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AN OPTICAL SENSOR AND ALGORITHM FRAMEWORK FOR CARDIAC WEARABLES

October 17 @ 2:00 pm - 3:00 pm

Date17th  October, 2017

Time:  2.00 PM

Venue: ESB 244

Speaker: Payal Monapatra (EE15S049)

Guide: Dr. Mohanasankar. S


DC members:

 Dr. Arun D Mahindrakar( Chairperson)

Dr. Ramasubba Reddy (M)(AM)

Dr. Bharath Bhikkaji (M)


Abstract

The growing demands of individual-centred healthcare and hence, continuous yet unobtrusive physiological monitoring, necessitates a systemwith high reliability and accuracy.Wearables used for continuous cardiological parameter estimation fromwrist use reflective photoplethysmography (PPG) technique that has certain limitations which areimperative. One such constraint is skin pigmentation of the subject. An accomodating sensor topologyemploying a 590 nm wavelength scheme that addresses the anomalies due to optical properties of skinis suitably tailored to maximize the quality of signal acquired, relatively insensitive to skin-pigmentation levels. The proposed set-up is tested on a conglomeration of subjects in terms of age, gender, skin tone etc. against a well-accepted optical choice (528 nm).Generous agreement between coherent measures for signal quality shows that the longer wavelengthholds an advantage over its shorter counterpart when subjected to varied skin pigmentation levels. Acomprehensive wrist wearable is prototyped encompassing this sensor design. Another constraint opticalwrist-wearablesface, is the temporal deformation of the desired waveform due to artifacts induced by eventhe slightest movement. This hinders their applicability in most of the practical cases. An algorithm isdeveloped addressing this issue by adaptively cancelling channel-noise. Dual PPG channels and 3-axisaccelerometer is used to estimate an average heart rate (HR). This Independent Channel Adaptive NoiseCancellation (ICANC) framework can be employed for both on-line as well as off-line measurement of HR.ICANC is compared against the existing benchmark algorithms using the accepted metrics forperformance. The wearable in conjunction with ICANC framework is validated on various subjects withdifferent skin-tone, age and gender under heterogeneous activities. Additionally, Heart Rate Variability(HRV), one of the most important biomarkers of physical and psychological well-being can be convenientlymeasured using the developed hardware. Such minimally intrusive methodology for HRV measurement isadvantageous.The developed wearable in alliance with a gateway device is capable of picking up high-fidelity PPG signals from the measurement site, allowing estimation of HRV-indices within a confidence of 5% from standard reference. Electrical and biological non-interference and ease ofusage of the proposed design simplify stationary and ambulatory monitoring of HRV.

Thus, the developedwearable integrated with contextual algorithms is capable of estimating HR under intense conditions ofmotion and short-term HRV in stationary conditions for subjects with wide variations in skin-pigmentationlevels.

All are cordially invited.

Details

Date:
October 17
Time:
2:00 pm - 3:00 pm
Event Category:

Venue

ESB 244
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