Plinio Morita

University of Waterloo
Project Title: Wire-free continuous respiratory monitoring using functional bed sheet
Industry Partner: Studio 1 Labs
Project Title: Cloud‐based data analytic platform for real‐world evidence generation
Industry Partner: Roche Canada
Project Partner: Helen Chen
Platforms: Agile Computing, Cloud Analytics, Large Memory System

Advanced Manufacturing Cybersecurity Health

Wire-free continuous respiratory monitoring using functional bed sheet

Apnea is a temporary stop in breathing and the most common type of apnea is Obstructive Sleep Apnea (OSA), which is a disturbance in sleep that is a leading cause in health problems such as heart disease, diabetes, high blood pressure, and Parkinson’s Disease if left unnoticed or untreated. Importantly, 80% of people affected by Obstructive Sleep Apnea remain undiagnosed. In infants, a stop in breathing for 20 seconds becomes fatal. Current methods of detection of respiration in hospital settings are either quite invasive, with wires and electrodes attached on the body, or are very time-consuming, such as manual counting method and listening of changes in breathing patterns. What if abnormal respiratory patterns can be detected non-invasively and provide early prediction of emergencies before they occur? This is the goal of Studio 1 Labs, a health technology company that has developed a responsive bed sheet using a noninvasive method of monitoring respiration patterns and changes in respiratory rate. Capturing millions of data points across a range of sensors, Studio 1 Labs is collaborating with Dr. Plinio Morita from the University of Waterloo, to develop a machine-learning algorithm for detection of respiration changes and to translate big data analysis into useful information, to provide patient-centred care for hospitals and homes.

Cloud‐based data analytic platform for real‐world evidence generation

Randomized controlled trials (RCTs) are considered the gold standard for supportive clinical evidence, however RCTs rarely describe the effectiveness of an intervention in real life practice. As such, regulators, payers, and health‐care providers are turning towards real world data (RWD) to understand how well an intervention performs in clinical practice. The best source of RWD is source data – that is, data that are collected at the interface of the patient and the health care system, as well patient monitoring and self‐reported data captured directly within the patients’ home environment.

Unfortunately, these data are stored in different and distinct systems that are not well integrated and in formats that do not allow for rapid analytic capabilities. The University of Waterloo in partnership with Roche Canada, are therefore proposing to develop the “CARE” (Clinical Analytics for Real‐World Evidence) platform. The “CARE” platform will be a holistic cloud‐based data analytic solution featuring a large central repository for consolidating data obtained from disparate data systems (including data from electronic medical records, lab data, physician transcriptions, and patient monitoring devices and self‐reported surveys).

The “CARE” platform will serve as a central hub for researchers that includes integrated and sophisticated data analytics, access control, security and study management tools in order to curate data for research and clinical purposes. This project begins the initial steps to address relevant research objectives in lung cancer by providing the tool and infrastructure required to process and analyze the enormous amount of scattered oncology data within an institution and across multiple institutions. Ultimately, this work will make it possible to mine currently siloed and/or unstructured data across the system and produce data‐driven insights in order to deliver the right care to the right patient at the right time through scientific innovation and research excellence.