University of Puerto Rico

Contacts

University of Puerto Rico Resource Center for Science and Engineering PO Box 23334 San Juan, PR 00931-3334

cawt@upr.edu

RP - (787) 765-5170 - Ext. 2117
MA - (787) 832-4040 - Ext. 3766

December 2021
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// CAWT

Wearable Health Technologies

// CAWT Highlights

Research Highlights

DEVELOPMENT AND DESIGN OF A WEARABLE OPTICAL SETUP TO IMPROVE MEASUREMENTS OF HEMOGLOBIN CONTENT

OUTCOME OR ACCOMPLISHMENT: A general lay-out of the configuration of wearable optical device for the detection of functional and non-functional forms of hemoglobin using three wavelengths was developed to characterize the spectral range, time response and power requirements needed to enhance the specificity and resolution of oxygen levels measured from scattered light through the skin.

IMPACT: The removal of the signal generated by the non-functional forms of hemoglobin in optical sensors will lead to accurate measurements of blood oxygen saturation.
GRAPHENE-LMNCO CATHODE MATERIAL FOR LI-ION BATTERIES

OUTCOME OR ACCOMPLISHMENT: Development of a rechargeable lithium-ion battery electrode through the homogeneous mixing of 10% of graphene powder into the active LMNCO cathode material for enhanced electrochemical performance.

IMPACT: The gravimetric energy density of the composite Graphene-LMNCO cathode material exceeds that of the LMNCO alone in lithium-ion batteries, and the addition of graphene into the active material is anticipated to be advantageous in applications in which weight per unit volume is a critical factor.

PREDICTION OF ELECTRONIC CONDUCTIVITY AND CHEMICAL STRUCTURES

OUTCOME OR ACCOMPLISHMENT: IRG 3 is developing models to predict electronic conductivity and chemical structures of materials by applying Natural Language Processing techniques. This transforms chemical structures and properties into a vector or matrix that can be fed to neural networks. This first step is essential to advance design of materials for energy storage in wearable devices.

IMPACT: The accomplishments during this first year will lead the project towards its main goal of impacting innovation and development of materials enabled by big data analytics and machine learning for applications of global interest in the health wearable technology sector with the input of experts from different fields.

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