Emmanuel Akinrintoyo

Emmanuel Akinrintoyo

Robotics and AI for health Researcher

Publications

Co-Designing iCST with Social Robots for Long-Term in-Home Deployment for Persons with Dementia

Published in Proceedings of the Human Robot Interaction 2024 Workshop on Ageing in Place, 2024

Individual cognitive stimulation therapy (iCST) is an effective therapeutic intervention that has been explored for aiding the cognitive ability of persons with dementia (PwDs). Despite its significant benefits, research evidence shows that it has been limited due to the burdens of caregivers, thus leading to low adherence. Therefore, this work explores the development of a social robot by co-designing with the key stakeholders for a 4-week in-home deployment in the homes of 10 PwDs. The system’s effectiveness will be evaluated by assessing changes in the quality of life of the users and the caregiving burdens of their carers.

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Reconfigurable topology testbeds: A new approach to optical system experiments

Published in Optical Fiber Technology, 2023

(Invited)Optical transmission systems provide high capacity, low latency and jitter, and high reliability for city-scale networks. Recirculating loop experiments have facilitated the study of signal propagation in long-haul optical transmission systems. However, they are unsuited for developing control and management software for city-scale optical networks with dozens or hundreds of reconfigurable optical add drop multiplexer (ROADM) units, diverse interconnection topologies, and dynamic traffic patterns….

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Optical Signal Spectrum Prediction Using Machine Learning and In-line Channel Monitors in a Multi-span ROADM System

Published in European Conference and Exhibition on Optical Communication, 2022

We measure the performance of separately characterized machine learning-based EDFA models for predicting the optical power spectrum evolution in a 5-span system with six ROADM nodes deployed in the COSMOS testbed, which achieve a mean absolute error of 0.6–0.7 dB after 10 EDFAs under varying channel loading configurations.

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