We are thrilled to announce that our customer’s product Verisense by Shimmer monitoring platform, is selected by the Letterkenny Institute of Technology (LYIT) and Letterkenny University Hospital (LUH) to study breast cancer fatigue. We are proud to have developed the platform and contributed to improving the quality of research in global healthcare.
Irish research lecturers Dr. James Connoly and Dr. William Scott, together with the research oncology nurse Mary Grace Kelly and oncologist Dr. Karen Duffy, will lead the study on atypical tiredness caused by breast cancer disease. They will use a completely new solution for clinical trials and research designed by our team for Shimmer.
Cancer-related fatigue also referred to as CRF, should be differentiated from common exhaustion, burnout, or weariness. CRF is a symptom of a malignant tumor in the breast. According to Dr. Scott, up to 70% of people undergoing treatment or being in remission suffer from fatigue. He says that CRF can arise unexpectedly and worsen patients’ quality of life significantly. That’s why the study is significant for exploring concurrent predictors of tiredness.
Dr. Connoly considers that the findings of previous studies on modulations in plasma and salivary markers are often conflicting. That’s the main reason for starting new research on predictive models, pharmacological, and psychological involvements. Dr. Scott has also added that previous studies failed because the results were mainly based on subjective data from patients. The objective of the current research is to create an accurate data foundation for people who have breast cancer to find out the correlation between daily and sleep activities, fatigue markers, and subjective indicators.
For this purpose, participants of the study will wear Verisense Inertial Measurable Unit (IMU) that looks pretty much like a fitness tracker. People don’t have to charge the device regularly as its battery life lasts for over six months. The data from the sensor is transmitted to the cloud platform seamlessly, without participants’ assistance. Researchers can get and check the data, monitor patients’ activity and sleep periods, for instance.
Our team has developed a cloud-based platform that supports continuous raw data and remote monitoring. The solution is fully customizable and is easy to set up and implement on a clinical trial site. We contributed to the advancement of data science algorithms and are proud to be a part of such a worthwhile project for healthcare.